Page MenuHomePhabricator

No OneTemporary

File Metadata

Fri, Jan 24, 4:17 PM
This file is larger than 256 KB, so syntax highlighting was skipped.
Index: llvm/trunk/lib/Transforms/IPO/FunctionImport.cpp
--- llvm/trunk/lib/Transforms/IPO/FunctionImport.cpp (revision 273046)
+++ llvm/trunk/lib/Transforms/IPO/FunctionImport.cpp (revision 273047)
@@ -1,775 +1,775 @@
//===- FunctionImport.cpp - ThinLTO Summary-based Function Import ---------===//
// The LLVM Compiler Infrastructure
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
// This file implements Function import based on summaries.
#include "llvm/Transforms/IPO/FunctionImport.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/ADT/Statistic.h"
#include "llvm/ADT/StringSet.h"
#include "llvm/ADT/Triple.h"
#include "llvm/IR/AutoUpgrade.h"
#include "llvm/IR/DiagnosticPrinter.h"
#include "llvm/IR/IntrinsicInst.h"
#include "llvm/IR/Module.h"
#include "llvm/IRReader/IRReader.h"
#include "llvm/Linker/Linker.h"
#include "llvm/Object/IRObjectFile.h"
#include "llvm/Object/ModuleSummaryIndexObjectFile.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/SourceMgr.h"
#include "llvm/Transforms/IPO/Internalize.h"
#include "llvm/Transforms/Utils/FunctionImportUtils.h"
#define DEBUG_TYPE "function-import"
using namespace llvm;
STATISTIC(NumImported, "Number of functions imported");
/// Limit on instruction count of imported functions.
static cl::opt<unsigned> ImportInstrLimit(
"import-instr-limit", cl::init(100), cl::Hidden, cl::value_desc("N"),
cl::desc("Only import functions with less than N instructions"));
static cl::opt<float>
ImportInstrFactor("import-instr-evolution-factor", cl::init(0.7),
cl::Hidden, cl::value_desc("x"),
cl::desc("As we import functions, multiply the "
"`import-instr-limit` threshold by this factor "
"before processing newly imported functions"));
static cl::opt<bool> PrintImports("print-imports", cl::init(false), cl::Hidden,
cl::desc("Print imported functions"));
// Temporary allows the function import pass to disable always linking
// referenced discardable symbols.
static cl::opt<bool>
cl::init(false), cl::Hidden);
// Load lazily a module from \p FileName in \p Context.
static std::unique_ptr<Module> loadFile(const std::string &FileName,
LLVMContext &Context) {
SMDiagnostic Err;
DEBUG(dbgs() << "Loading '" << FileName << "'\n");
// Metadata isn't loaded until functions are imported, to minimize
// the memory overhead.
std::unique_ptr<Module> Result =
getLazyIRFileModule(FileName, Err, Context,
/* ShouldLazyLoadMetadata = */ true);
if (!Result) {
Err.print("function-import", errs());
return Result;
namespace {
// Return true if the Summary describes a GlobalValue that can be externally
// referenced, i.e. it does not need renaming (linkage is not local) or renaming
// is possible (does not have a section for instance).
static bool canBeExternallyReferenced(const GlobalValueSummary &Summary) {
if (!Summary.needsRenaming())
return true;
if (Summary.hasSection())
// Can't rename a global that needs renaming if has a section.
return false;
return true;
// Return true if \p GUID describes a GlobalValue that can be externally
// referenced, i.e. it does not need renaming (linkage is not local) or
// renaming is possible (does not have a section for instance).
static bool canBeExternallyReferenced(const ModuleSummaryIndex &Index,
GlobalValue::GUID GUID) {
auto Summaries = Index.findGlobalValueSummaryList(GUID);
if (Summaries == Index.end())
return true;
if (Summaries->second.size() != 1)
// If there are multiple globals with this GUID, then we know it is
// not a local symbol, and it is necessarily externally referenced.
return true;
// We don't need to check for the module path, because if it can't be
// externally referenced and we call it, it is necessarilly in the same
// module
return canBeExternallyReferenced(**Summaries->second.begin());
// Return true if the global described by \p Summary can be imported in another
// module.
static bool eligibleForImport(const ModuleSummaryIndex &Index,
const GlobalValueSummary &Summary) {
if (!canBeExternallyReferenced(Summary))
// Can't import a global that needs renaming if has a section for instance.
// FIXME: we may be able to import it by copying it without promotion.
return false;
// Check references (and potential calls) in the same module. If the current
// value references a global that can't be externally referenced it is not
// eligible for import.
bool AllRefsCanBeExternallyReferenced =
llvm::all_of(Summary.refs(), [&](const ValueInfo &VI) {
return canBeExternallyReferenced(Index, VI.getGUID());
if (!AllRefsCanBeExternallyReferenced)
return false;
if (auto *FuncSummary = dyn_cast<FunctionSummary>(&Summary)) {
bool AllCallsCanBeExternallyReferenced = llvm::all_of(
FuncSummary->calls(), [&](const FunctionSummary::EdgeTy &Edge) {
return canBeExternallyReferenced(Index, Edge.first.getGUID());
if (!AllCallsCanBeExternallyReferenced)
return false;
return true;
/// Given a list of possible callee implementation for a call site, select one
/// that fits the \p Threshold.
/// FIXME: select "best" instead of first that fits. But what is "best"?
/// - The smallest: more likely to be inlined.
/// - The one with the least outgoing edges (already well optimized).
/// - One from a module already being imported from in order to reduce the
/// number of source modules parsed/linked.
/// - One that has PGO data attached.
/// - [insert you fancy metric here]
static const GlobalValueSummary *
selectCallee(const ModuleSummaryIndex &Index,
const GlobalValueSummaryList &CalleeSummaryList,
unsigned Threshold) {
auto It = llvm::find_if(
[&](const std::unique_ptr<GlobalValueSummary> &SummaryPtr) {
auto *GVSummary = SummaryPtr.get();
if (GlobalValue::isInterposableLinkage(GVSummary->linkage()))
// There is no point in importing these, we can't inline them
return false;
if (auto *AS = dyn_cast<AliasSummary>(GVSummary)) {
GVSummary = &AS->getAliasee();
// Alias can't point to "available_externally". However when we import
// linkOnceODR the linkage does not change. So we import the alias
// and aliasee only in this case.
// FIXME: we should import alias as available_externally *function*,
// the destination module does need to know it is an alias.
if (!GlobalValue::isLinkOnceODRLinkage(GVSummary->linkage()))
return false;
auto *Summary = cast<FunctionSummary>(GVSummary);
if (Summary->instCount() > Threshold)
return false;
if (!eligibleForImport(Index, *Summary))
return false;
return true;
if (It == CalleeSummaryList.end())
return nullptr;
return cast<GlobalValueSummary>(It->get());
/// Return the summary for the function \p GUID that fits the \p Threshold, or
/// null if there's no match.
static const GlobalValueSummary *selectCallee(GlobalValue::GUID GUID,
unsigned Threshold,
const ModuleSummaryIndex &Index) {
auto CalleeSummaryList = Index.findGlobalValueSummaryList(GUID);
if (CalleeSummaryList == Index.end())
return nullptr; // This function does not have a summary
return selectCallee(Index, CalleeSummaryList->second, Threshold);
/// Mark the global \p GUID as export by module \p ExportModulePath if found in
/// this module. If it is a GlobalVariable, we also mark any referenced global
/// in the current module as exported.
static void exportGlobalInModule(const ModuleSummaryIndex &Index,
StringRef ExportModulePath,
GlobalValue::GUID GUID,
FunctionImporter::ExportSetTy &ExportList) {
auto FindGlobalSummaryInModule =
[&](GlobalValue::GUID GUID) -> GlobalValueSummary *{
auto SummaryList = Index.findGlobalValueSummaryList(GUID);
if (SummaryList == Index.end())
// This global does not have a summary, it is not part of the ThinLTO
// process
return nullptr;
auto SummaryIter = llvm::find_if(
[&](const std::unique_ptr<GlobalValueSummary> &Summary) {
return Summary->modulePath() == ExportModulePath;
if (SummaryIter == SummaryList->second.end())
return nullptr;
return SummaryIter->get();
auto *Summary = FindGlobalSummaryInModule(GUID);
if (!Summary)
// We found it in the current module, mark as exported
auto GVS = dyn_cast<GlobalVarSummary>(Summary);
if (!GVS)
// FunctionImportGlobalProcessing::doPromoteLocalToGlobal() will always
// trigger importing the initializer for `constant unnamed addr` globals that
// are referenced. We conservatively export all the referenced symbols for
// every global to workaround this, so that the ExportList is accurate.
// FIXME: with a "isConstant" flag in the summary we could be more targetted.
for (auto &Ref : GVS->refs()) {
auto GUID = Ref.getGUID();
auto *RefSummary = FindGlobalSummaryInModule(GUID);
if (RefSummary)
// Found a ref in the current module, mark it as exported
using EdgeInfo = std::pair<const FunctionSummary *, unsigned /* Threshold */>;
/// Compute the list of functions to import for a given caller. Mark these
/// imported functions and the symbols they reference in their source module as
/// exported from their source module.
static void computeImportForFunction(
const FunctionSummary &Summary, const ModuleSummaryIndex &Index,
unsigned Threshold, const GVSummaryMapTy &DefinedGVSummaries,
SmallVectorImpl<EdgeInfo> &Worklist,
FunctionImporter::ImportMapTy &ImportsForModule,
StringMap<FunctionImporter::ExportSetTy> *ExportLists = nullptr) {
for (auto &Edge : Summary.calls()) {
auto GUID = Edge.first.getGUID();
DEBUG(dbgs() << " edge -> " << GUID << " Threshold:" << Threshold << "\n");
if (DefinedGVSummaries.count(GUID)) {
DEBUG(dbgs() << "ignored! Target already in destination module.\n");
auto *CalleeSummary = selectCallee(GUID, Threshold, Index);
if (!CalleeSummary) {
DEBUG(dbgs() << "ignored! No qualifying callee with summary found.\n");
// "Resolve" the summary, traversing alias,
const FunctionSummary *ResolvedCalleeSummary;
if (isa<AliasSummary>(CalleeSummary)) {
ResolvedCalleeSummary = cast<FunctionSummary>(
GlobalValue::isLinkOnceODRLinkage(ResolvedCalleeSummary->linkage()) &&
"Unexpected alias to a non-linkonceODR in import list");
} else
ResolvedCalleeSummary = cast<FunctionSummary>(CalleeSummary);
assert(ResolvedCalleeSummary->instCount() <= Threshold &&
"selectCallee() didn't honor the threshold");
auto ExportModulePath = ResolvedCalleeSummary->modulePath();
auto &ProcessedThreshold = ImportsForModule[ExportModulePath][GUID];
/// Since the traversal of the call graph is DFS, we can revisit a function
/// a second time with a higher threshold. In this case, it is added back to
/// the worklist with the new threshold.
if (ProcessedThreshold && ProcessedThreshold >= Threshold) {
DEBUG(dbgs() << "ignored! Target was already seen with Threshold "
<< ProcessedThreshold << "\n");
// Mark this function as imported in this module, with the current Threshold
ProcessedThreshold = Threshold;
// Make exports in the source module.
if (ExportLists) {
auto &ExportList = (*ExportLists)[ExportModulePath];
// Mark all functions and globals referenced by this function as exported
// to the outside if they are defined in the same source module.
for (auto &Edge : ResolvedCalleeSummary->calls()) {
auto CalleeGUID = Edge.first.getGUID();
exportGlobalInModule(Index, ExportModulePath, CalleeGUID, ExportList);
for (auto &Ref : ResolvedCalleeSummary->refs()) {
auto GUID = Ref.getGUID();
exportGlobalInModule(Index, ExportModulePath, GUID, ExportList);
// Insert the newly imported function to the worklist.
Worklist.push_back(std::make_pair(ResolvedCalleeSummary, Threshold));
/// Given the list of globals defined in a module, compute the list of imports
/// as well as the list of "exports", i.e. the list of symbols referenced from
/// another module (that may require promotion).
static void ComputeImportForModule(
const GVSummaryMapTy &DefinedGVSummaries, const ModuleSummaryIndex &Index,
FunctionImporter::ImportMapTy &ImportsForModule,
StringMap<FunctionImporter::ExportSetTy> *ExportLists = nullptr) {
// Worklist contains the list of function imported in this module, for which
// we will analyse the callees and may import further down the callgraph.
SmallVector<EdgeInfo, 128> Worklist;
// Populate the worklist with the import for the functions in the current
// module
for (auto &GVSummary : DefinedGVSummaries) {
auto *Summary = GVSummary.second;
if (auto *AS = dyn_cast<AliasSummary>(Summary))
Summary = &AS->getAliasee();
auto *FuncSummary = dyn_cast<FunctionSummary>(Summary);
if (!FuncSummary)
// Skip import for global variables
DEBUG(dbgs() << "Initalize import for " << GVSummary.first << "\n");
computeImportForFunction(*FuncSummary, Index, ImportInstrLimit,
DefinedGVSummaries, Worklist, ImportsForModule,
while (!Worklist.empty()) {
auto FuncInfo = Worklist.pop_back_val();
auto *Summary = FuncInfo.first;
auto Threshold = FuncInfo.second;
// Process the newly imported functions and add callees to the worklist.
// Adjust the threshold
Threshold = Threshold * ImportInstrFactor;
computeImportForFunction(*Summary, Index, Threshold, DefinedGVSummaries,
Worklist, ImportsForModule, ExportLists);
} // anonymous namespace
/// Compute all the import and export for every module using the Index.
void llvm::ComputeCrossModuleImport(
const ModuleSummaryIndex &Index,
const StringMap<GVSummaryMapTy> &ModuleToDefinedGVSummaries,
StringMap<FunctionImporter::ImportMapTy> &ImportLists,
StringMap<FunctionImporter::ExportSetTy> &ExportLists) {
// For each module that has function defined, compute the import/export lists.
for (auto &DefinedGVSummaries : ModuleToDefinedGVSummaries) {
auto &ImportsForModule = ImportLists[DefinedGVSummaries.first()];
DEBUG(dbgs() << "Computing import for Module '"
<< DefinedGVSummaries.first() << "'\n");
ComputeImportForModule(DefinedGVSummaries.second, Index, ImportsForModule,
#ifndef NDEBUG
DEBUG(dbgs() << "Import/Export lists for " << ImportLists.size()
<< " modules:\n");
for (auto &ModuleImports : ImportLists) {
auto ModName = ModuleImports.first();
auto &Exports = ExportLists[ModName];
DEBUG(dbgs() << "* Module " << ModName << " exports " << Exports.size()
<< " functions. Imports from " << ModuleImports.second.size()
<< " modules.\n");
for (auto &Src : ModuleImports.second) {
auto SrcModName = Src.first();
DEBUG(dbgs() << " - " << Src.second.size() << " functions imported from "
<< SrcModName << "\n");
/// Compute all the imports for the given module in the Index.
void llvm::ComputeCrossModuleImportForModule(
StringRef ModulePath, const ModuleSummaryIndex &Index,
FunctionImporter::ImportMapTy &ImportList) {
// Collect the list of functions this module defines.
// GUID -> Summary
GVSummaryMapTy FunctionSummaryMap;
Index.collectDefinedFunctionsForModule(ModulePath, FunctionSummaryMap);
// Compute the import list for this module.
DEBUG(dbgs() << "Computing import for Module '" << ModulePath << "'\n");
ComputeImportForModule(FunctionSummaryMap, Index, ImportList);
#ifndef NDEBUG
DEBUG(dbgs() << "* Module " << ModulePath << " imports from "
<< ImportList.size() << " modules.\n");
for (auto &Src : ImportList) {
auto SrcModName = Src.first();
DEBUG(dbgs() << " - " << Src.second.size() << " functions imported from "
<< SrcModName << "\n");
/// Compute the set of summaries needed for a ThinLTO backend compilation of
/// \p ModulePath.
void llvm::gatherImportedSummariesForModule(
StringRef ModulePath,
const StringMap<GVSummaryMapTy> &ModuleToDefinedGVSummaries,
const StringMap<FunctionImporter::ImportMapTy> &ImportLists,
std::map<std::string, GVSummaryMapTy> &ModuleToSummariesForIndex) {
// Include all summaries from the importing module.
ModuleToSummariesForIndex[ModulePath] =
auto ModuleImports = ImportLists.find(ModulePath);
if (ModuleImports != ImportLists.end()) {
// Include summaries for imports.
for (auto &ILI : ModuleImports->second) {
auto &SummariesForIndex = ModuleToSummariesForIndex[ILI.first()];
const auto &DefinedGVSummaries =
for (auto &GI : ILI.second) {
const auto &DS = DefinedGVSummaries.find(GI.first);
assert(DS != DefinedGVSummaries.end() &&
"Expected a defined summary for imported global value");
SummariesForIndex[GI.first] = DS->second;
/// Emit the files \p ModulePath will import from into \p OutputFilename.
std::error_code llvm::EmitImportsFiles(
StringRef ModulePath, StringRef OutputFilename,
const StringMap<FunctionImporter::ImportMapTy> &ImportLists) {
auto ModuleImports = ImportLists.find(ModulePath);
std::error_code EC;
raw_fd_ostream ImportsOS(OutputFilename, EC, sys::fs::OpenFlags::F_None);
if (EC)
return EC;
if (ModuleImports != ImportLists.end())
for (auto &ILI : ModuleImports->second)
ImportsOS << ILI.first() << "\n";
return std::error_code();
/// Fixup WeakForLinker linkages in \p TheModule based on summary analysis.
void llvm::thinLTOResolveWeakForLinkerModule(
Module &TheModule, const GVSummaryMapTy &DefinedGlobals) {
auto updateLinkage = [&](GlobalValue &GV) {
if (!GlobalValue::isWeakForLinker(GV.getLinkage()))
// See if the global summary analysis computed a new resolved linkage.
const auto &GS = DefinedGlobals.find(GV.getGUID());
if (GS == DefinedGlobals.end())
auto NewLinkage = GS->second->linkage();
if (NewLinkage == GV.getLinkage())
DEBUG(dbgs() << "ODR fixing up linkage for `" << GV.getName() << "` from "
<< GV.getLinkage() << " to " << NewLinkage << "\n");
// Process functions and global now
for (auto &GV : TheModule)
for (auto &GV : TheModule.globals())
for (auto &GV : TheModule.aliases())
/// Run internalization on \p TheModule based on symmary analysis.
void llvm::thinLTOInternalizeModule(Module &TheModule,
const GVSummaryMapTy &DefinedGlobals) {
// Parse inline ASM and collect the list of symbols that are not defined in
// the current module.
StringSet<> AsmUndefinedRefs;
Triple(TheModule.getTargetTriple()), TheModule.getModuleInlineAsm(),
[&AsmUndefinedRefs](StringRef Name, object::BasicSymbolRef::Flags Flags) {
if (Flags & object::BasicSymbolRef::SF_Undefined)
// Declare a callback for the internalize pass that will ask for every
// candidate GlobalValue if it can be internalized or not.
auto MustPreserveGV = [&](const GlobalValue &GV) -> bool {
// Can't be internalized if referenced in inline asm.
if (AsmUndefinedRefs.count(GV.getName()))
return true;
// Lookup the linkage recorded in the summaries during global analysis.
const auto &GS = DefinedGlobals.find(GV.getGUID());
GlobalValue::LinkageTypes Linkage;
if (GS == DefinedGlobals.end()) {
// Must have been promoted (possibly conservatively). Find original
// name so that we can access the correct summary and see if it can
// be internalized again.
// FIXME: Eventually we should control promotion instead of promoting
// and internalizing again.
StringRef OrigName =
std::string OrigId = GlobalValue::getGlobalIdentifier(
OrigName, GlobalValue::InternalLinkage,
const auto &GS = DefinedGlobals.find(GlobalValue::getGUID(OrigId));
if (GS == DefinedGlobals.end()) {
// Also check the original non-promoted non-globalized name. In some
// cases a preempted weak value is linked in as a local copy because
// it is referenced by an alias (IRLinker::linkGlobalValueProto).
// In that case, since it was originally not a local value, it was
// recorded in the index using the original name.
// FIXME: This may not be needed once PR27866 is fixed.
const auto &GS = DefinedGlobals.find(GlobalValue::getGUID(OrigName));
assert(GS != DefinedGlobals.end());
Linkage = GS->second->linkage();
} else {
Linkage = GS->second->linkage();
} else
Linkage = GS->second->linkage();
return !GlobalValue::isLocalLinkage(Linkage);
// FIXME: See if we can just internalize directly here via linkage changes
// based on the index, rather than invoking internalizeModule.
llvm::internalizeModule(TheModule, MustPreserveGV);
// Automatically import functions in Module \p DestModule based on the summaries
// index.
bool FunctionImporter::importFunctions(
Module &DestModule, const FunctionImporter::ImportMapTy &ImportList,
bool ForceImportReferencedDiscardableSymbols) {
DEBUG(dbgs() << "Starting import for Module "
<< DestModule.getModuleIdentifier() << "\n");
unsigned ImportedCount = 0;
// Linker that will be used for importing function
Linker TheLinker(DestModule);
// Do the actual import of functions now, one Module at a time
std::set<StringRef> ModuleNameOrderedList;
for (auto &FunctionsToImportPerModule : ImportList) {
for (auto &Name : ModuleNameOrderedList) {
// Get the module for the import
const auto &FunctionsToImportPerModule = ImportList.find(Name);
assert(FunctionsToImportPerModule != ImportList.end());
std::unique_ptr<Module> SrcModule = ModuleLoader(Name);
assert(&DestModule.getContext() == &SrcModule->getContext() &&
"Context mismatch");
// If modules were created with lazy metadata loading, materialize it
// now, before linking it (otherwise this will be a noop).
auto &ImportGUIDs = FunctionsToImportPerModule->second;
// Find the globals to import
DenseSet<const GlobalValue *> GlobalsToImport;
for (auto &GV : *SrcModule) {
if (!GV.hasName())
auto GUID = GV.getGUID();
auto Import = ImportGUIDs.count(GUID);
DEBUG(dbgs() << (Import ? "Is" : "Not") << " importing function " << GUID
<< " " << GV.getName() << " from "
<< SrcModule->getSourceFileName() << "\n");
if (Import) {
for (auto &GV : SrcModule->globals()) {
if (!GV.hasName())
auto GUID = GV.getGUID();
auto Import = ImportGUIDs.count(GUID);
DEBUG(dbgs() << (Import ? "Is" : "Not") << " importing global " << GUID
<< " " << GV.getName() << " from "
<< SrcModule->getSourceFileName() << "\n");
if (Import) {
for (auto &GV : SrcModule->aliases()) {
if (!GV.hasName())
auto GUID = GV.getGUID();
auto Import = ImportGUIDs.count(GUID);
DEBUG(dbgs() << (Import ? "Is" : "Not") << " importing alias " << GUID
<< " " << GV.getName() << " from "
<< SrcModule->getSourceFileName() << "\n");
if (Import) {
// Alias can't point to "available_externally". However when we import
// linkOnceODR the linkage does not change. So we import the alias
// and aliasee only in this case. This has been handled by
// computeImportForFunction()
GlobalObject *GO = GV.getBaseObject();
assert(GO->hasLinkOnceODRLinkage() &&
"Unexpected alias to a non-linkonceODR in import list");
#ifndef NDEBUG
if (!GlobalsToImport.count(GO))
DEBUG(dbgs() << " alias triggers importing aliasee " << GO->getGUID()
<< " " << GO->getName() << " from "
<< SrcModule->getSourceFileName() << "\n");
// Link in the specified functions.
if (renameModuleForThinLTO(*SrcModule, Index, &GlobalsToImport))
return true;
if (PrintImports) {
for (const auto *GV : GlobalsToImport)
dbgs() << DestModule.getSourceFileName() << ": Import " << GV->getName()
<< " from " << SrcModule->getSourceFileName() << "\n";
// Instruct the linker that the client will take care of linkonce resolution
unsigned Flags = Linker::Flags::None;
if (!ForceImportReferencedDiscardableSymbols)
Flags |= Linker::Flags::DontForceLinkLinkonceODR;
if (TheLinker.linkInModule(std::move(SrcModule), Flags, &GlobalsToImport))
report_fatal_error("Function Import: link error");
ImportedCount += GlobalsToImport.size();
NumImported += ImportedCount;
DEBUG(dbgs() << "Imported " << ImportedCount << " functions for Module "
<< DestModule.getModuleIdentifier() << "\n");
return ImportedCount;
/// Summary file to use for function importing when using -function-import from
/// the command line.
static cl::opt<std::string>
cl::desc("The summary file to use for function importing."));
static void diagnosticHandler(const DiagnosticInfo &DI) {
raw_ostream &OS = errs();
DiagnosticPrinterRawOStream DP(OS);
OS << '\n';
/// Parse the summary index out of an IR file and return the summary
/// index object if found, or nullptr if not.
-static std::unique_ptr<ModuleSummaryIndex>
-getModuleSummaryIndexForFile(StringRef Path, std::string &Error,
- DiagnosticHandlerFunction DiagnosticHandler) {
+static std::unique_ptr<ModuleSummaryIndex> getModuleSummaryIndexForFile(
+ StringRef Path, std::string &Error,
+ const DiagnosticHandlerFunction &DiagnosticHandler) {
std::unique_ptr<MemoryBuffer> Buffer;
ErrorOr<std::unique_ptr<MemoryBuffer>> BufferOrErr =
if (std::error_code EC = BufferOrErr.getError()) {
Error = EC.message();
return nullptr;
Buffer = std::move(BufferOrErr.get());
ErrorOr<std::unique_ptr<object::ModuleSummaryIndexObjectFile>> ObjOrErr =
if (std::error_code EC = ObjOrErr.getError()) {
Error = EC.message();
return nullptr;
return (*ObjOrErr)->takeIndex();
namespace {
/// Pass that performs cross-module function import provided a summary file.
class FunctionImportPass : public ModulePass {
/// Optional module summary index to use for importing, otherwise
/// the summary-file option must be specified.
const ModuleSummaryIndex *Index;
/// Pass identification, replacement for typeid
static char ID;
/// Specify pass name for debug output
const char *getPassName() const override { return "Function Importing"; }
explicit FunctionImportPass(const ModuleSummaryIndex *Index = nullptr)
: ModulePass(ID), Index(Index) {}
bool runOnModule(Module &M) override {
if (skipModule(M))
return false;
if (SummaryFile.empty() && !Index)
report_fatal_error("error: -function-import requires -summary-file or "
"file from frontend\n");
std::unique_ptr<ModuleSummaryIndex> IndexPtr;
if (!SummaryFile.empty()) {
if (Index)
report_fatal_error("error: -summary-file and index from frontend\n");
std::string Error;
IndexPtr =
getModuleSummaryIndexForFile(SummaryFile, Error, diagnosticHandler);
if (!IndexPtr) {
errs() << "Error loading file '" << SummaryFile << "': " << Error
<< "\n";
return false;
Index = IndexPtr.get();
// First step is collecting the import list.
FunctionImporter::ImportMapTy ImportList;
ComputeCrossModuleImportForModule(M.getModuleIdentifier(), *Index,
// Next we need to promote to global scope and rename any local values that
// are potentially exported to other modules.
if (renameModuleForThinLTO(M, *Index, nullptr)) {
errs() << "Error renaming module\n";
return false;
// Perform the import now.
auto ModuleLoader = [&M](StringRef Identifier) {
return loadFile(Identifier, M.getContext());
FunctionImporter Importer(*Index, ModuleLoader);
return Importer.importFunctions(
M, ImportList, !DontForceImportReferencedDiscardableSymbols);
} // anonymous namespace
char FunctionImportPass::ID = 0;
INITIALIZE_PASS_BEGIN(FunctionImportPass, "function-import",
"Summary Based Function Import", false, false)
INITIALIZE_PASS_END(FunctionImportPass, "function-import",
"Summary Based Function Import", false, false)
namespace llvm {
Pass *createFunctionImportPass(const ModuleSummaryIndex *Index = nullptr) {
return new FunctionImportPass(Index);
Index: llvm/trunk/lib/Transforms/Vectorize/LoopVectorize.cpp
--- llvm/trunk/lib/Transforms/Vectorize/LoopVectorize.cpp (revision 273046)
+++ llvm/trunk/lib/Transforms/Vectorize/LoopVectorize.cpp (revision 273047)
@@ -1,6452 +1,6452 @@
//===- LoopVectorize.cpp - A Loop Vectorizer ------------------------------===//
// The LLVM Compiler Infrastructure
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
// This is the LLVM loop vectorizer. This pass modifies 'vectorizable' loops
// and generates target-independent LLVM-IR.
// The vectorizer uses the TargetTransformInfo analysis to estimate the costs
// of instructions in order to estimate the profitability of vectorization.
// The loop vectorizer combines consecutive loop iterations into a single
// 'wide' iteration. After this transformation the index is incremented
// by the SIMD vector width, and not by one.
// This pass has three parts:
// 1. The main loop pass that drives the different parts.
// 2. LoopVectorizationLegality - A unit that checks for the legality
// of the vectorization.
// 3. InnerLoopVectorizer - A unit that performs the actual
// widening of instructions.
// 4. LoopVectorizationCostModel - A unit that checks for the profitability
// of vectorization. It decides on the optimal vector width, which
// can be one, if vectorization is not profitable.
// The reduction-variable vectorization is based on the paper:
// D. Nuzman and R. Henderson. Multi-platform Auto-vectorization.
// Variable uniformity checks are inspired by:
// Karrenberg, R. and Hack, S. Whole Function Vectorization.
// The interleaved access vectorization is based on the paper:
// Dorit Nuzman, Ira Rosen and Ayal Zaks. Auto-Vectorization of Interleaved
// Data for SIMD
// Other ideas/concepts are from:
// A. Zaks and D. Nuzman. Autovectorization in GCC-two years later.
// S. Maleki, Y. Gao, M. Garzaran, T. Wong and D. Padua. An Evaluation of
// Vectorizing Compilers.
#include "llvm/ADT/DenseMap.h"
#include "llvm/ADT/Hashing.h"
#include "llvm/ADT/MapVector.h"
#include "llvm/ADT/SetVector.h"
#include "llvm/ADT/SmallPtrSet.h"
#include "llvm/ADT/SmallSet.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/ADT/Statistic.h"
#include "llvm/ADT/StringExtras.h"
#include "llvm/Analysis/AliasAnalysis.h"
#include "llvm/Analysis/AssumptionCache.h"
#include "llvm/Analysis/BasicAliasAnalysis.h"
#include "llvm/Analysis/BlockFrequencyInfo.h"
#include "llvm/Analysis/CodeMetrics.h"
#include "llvm/Analysis/DemandedBits.h"
#include "llvm/Analysis/GlobalsModRef.h"
#include "llvm/Analysis/LoopAccessAnalysis.h"
#include "llvm/Analysis/LoopInfo.h"
#include "llvm/Analysis/LoopIterator.h"
#include "llvm/Analysis/LoopPass.h"
#include "llvm/Analysis/ScalarEvolution.h"
#include "llvm/Analysis/ScalarEvolutionExpander.h"
#include "llvm/Analysis/ScalarEvolutionExpressions.h"
#include "llvm/Analysis/TargetTransformInfo.h"
#include "llvm/Analysis/ValueTracking.h"
#include "llvm/Analysis/VectorUtils.h"
#include "llvm/IR/Constants.h"
#include "llvm/IR/DataLayout.h"
#include "llvm/IR/DebugInfo.h"
#include "llvm/IR/DerivedTypes.h"
#include "llvm/IR/DiagnosticInfo.h"
#include "llvm/IR/Dominators.h"
#include "llvm/IR/Function.h"
#include "llvm/IR/IRBuilder.h"
#include "llvm/IR/Instructions.h"
#include "llvm/IR/IntrinsicInst.h"
#include "llvm/IR/LLVMContext.h"
#include "llvm/IR/Module.h"
#include "llvm/IR/PatternMatch.h"
#include "llvm/IR/Type.h"
#include "llvm/IR/Value.h"
#include "llvm/IR/ValueHandle.h"
#include "llvm/IR/Verifier.h"
#include "llvm/Pass.h"
#include "llvm/Support/BranchProbability.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Transforms/Scalar.h"
#include "llvm/Transforms/Utils/BasicBlockUtils.h"
#include "llvm/Transforms/Utils/Local.h"
#include "llvm/Transforms/Utils/LoopUtils.h"
#include "llvm/Transforms/Utils/LoopVersioning.h"
#include "llvm/Transforms/Vectorize.h"
#include <algorithm>
#include <functional>
#include <map>
#include <tuple>
using namespace llvm;
using namespace llvm::PatternMatch;
#define LV_NAME "loop-vectorize"
STATISTIC(LoopsVectorized, "Number of loops vectorized");
STATISTIC(LoopsAnalyzed, "Number of loops analyzed for vectorization");
static cl::opt<bool>
EnableIfConversion("enable-if-conversion", cl::init(true), cl::Hidden,
cl::desc("Enable if-conversion during vectorization."));
/// We don't vectorize loops with a known constant trip count below this number.
static cl::opt<unsigned> TinyTripCountVectorThreshold(
"vectorizer-min-trip-count", cl::init(16), cl::Hidden,
cl::desc("Don't vectorize loops with a constant "
"trip count that is smaller than this "
static cl::opt<bool> MaximizeBandwidth(
"vectorizer-maximize-bandwidth", cl::init(false), cl::Hidden,
cl::desc("Maximize bandwidth when selecting vectorization factor which "
"will be determined by the smallest type in loop."));
/// This enables versioning on the strides of symbolically striding memory
/// accesses in code like the following.
/// for (i = 0; i < N; ++i)
/// A[i * Stride1] += B[i * Stride2] ...
/// Will be roughly translated to
/// if (Stride1 == 1 && Stride2 == 1) {
/// for (i = 0; i < N; i+=4)
/// A[i:i+3] += ...
/// } else
/// ...
static cl::opt<bool> EnableMemAccessVersioning(
"enable-mem-access-versioning", cl::init(true), cl::Hidden,
cl::desc("Enable symbolic stride memory access versioning"));
static cl::opt<bool> EnableInterleavedMemAccesses(
"enable-interleaved-mem-accesses", cl::init(false), cl::Hidden,
cl::desc("Enable vectorization on interleaved memory accesses in a loop"));
/// Maximum factor for an interleaved memory access.
static cl::opt<unsigned> MaxInterleaveGroupFactor(
"max-interleave-group-factor", cl::Hidden,
cl::desc("Maximum factor for an interleaved access group (default = 8)"),
/// We don't interleave loops with a known constant trip count below this
/// number.
static const unsigned TinyTripCountInterleaveThreshold = 128;
static cl::opt<unsigned> ForceTargetNumScalarRegs(
"force-target-num-scalar-regs", cl::init(0), cl::Hidden,
cl::desc("A flag that overrides the target's number of scalar registers."));
static cl::opt<unsigned> ForceTargetNumVectorRegs(
"force-target-num-vector-regs", cl::init(0), cl::Hidden,
cl::desc("A flag that overrides the target's number of vector registers."));
/// Maximum vectorization interleave count.
static const unsigned MaxInterleaveFactor = 16;
static cl::opt<unsigned> ForceTargetMaxScalarInterleaveFactor(
"force-target-max-scalar-interleave", cl::init(0), cl::Hidden,
cl::desc("A flag that overrides the target's max interleave factor for "
"scalar loops."));
static cl::opt<unsigned> ForceTargetMaxVectorInterleaveFactor(
"force-target-max-vector-interleave", cl::init(0), cl::Hidden,
cl::desc("A flag that overrides the target's max interleave factor for "
"vectorized loops."));
static cl::opt<unsigned> ForceTargetInstructionCost(
"force-target-instruction-cost", cl::init(0), cl::Hidden,
cl::desc("A flag that overrides the target's expected cost for "
"an instruction to a single constant value. Mostly "
"useful for getting consistent testing."));
static cl::opt<unsigned> SmallLoopCost(
"small-loop-cost", cl::init(20), cl::Hidden,
"The cost of a loop that is considered 'small' by the interleaver."));
static cl::opt<bool> LoopVectorizeWithBlockFrequency(
"loop-vectorize-with-block-frequency", cl::init(false), cl::Hidden,
cl::desc("Enable the use of the block frequency analysis to access PGO "
"heuristics minimizing code growth in cold regions and being more "
"aggressive in hot regions."));
// Runtime interleave loops for load/store throughput.
static cl::opt<bool> EnableLoadStoreRuntimeInterleave(
"enable-loadstore-runtime-interleave", cl::init(true), cl::Hidden,
"Enable runtime interleaving until load/store ports are saturated"));
/// The number of stores in a loop that are allowed to need predication.
static cl::opt<unsigned> NumberOfStoresToPredicate(
"vectorize-num-stores-pred", cl::init(1), cl::Hidden,
cl::desc("Max number of stores to be predicated behind an if."));
static cl::opt<bool> EnableIndVarRegisterHeur(
"enable-ind-var-reg-heur", cl::init(true), cl::Hidden,
cl::desc("Count the induction variable only once when interleaving"));
static cl::opt<bool> EnableCondStoresVectorization(
"enable-cond-stores-vec", cl::init(false), cl::Hidden,
cl::desc("Enable if predication of stores during vectorization."));
static cl::opt<unsigned> MaxNestedScalarReductionIC(
"max-nested-scalar-reduction-interleave", cl::init(2), cl::Hidden,
cl::desc("The maximum interleave count to use when interleaving a scalar "
"reduction in a nested loop."));
static cl::opt<unsigned> PragmaVectorizeMemoryCheckThreshold(
"pragma-vectorize-memory-check-threshold", cl::init(128), cl::Hidden,
cl::desc("The maximum allowed number of runtime memory checks with a "
"vectorize(enable) pragma."));
static cl::opt<unsigned> VectorizeSCEVCheckThreshold(
"vectorize-scev-check-threshold", cl::init(16), cl::Hidden,
cl::desc("The maximum number of SCEV checks allowed."));
static cl::opt<unsigned> PragmaVectorizeSCEVCheckThreshold(
"pragma-vectorize-scev-check-threshold", cl::init(128), cl::Hidden,
cl::desc("The maximum number of SCEV checks allowed with a "
"vectorize(enable) pragma"));
namespace {
// Forward declarations.
class LoopVectorizeHints;
class LoopVectorizationLegality;
class LoopVectorizationCostModel;
class LoopVectorizationRequirements;
/// \brief This modifies LoopAccessReport to initialize message with
/// loop-vectorizer-specific part.
class VectorizationReport : public LoopAccessReport {
VectorizationReport(Instruction *I = nullptr)
: LoopAccessReport("loop not vectorized: ", I) {}
/// \brief This allows promotion of the loop-access analysis report into the
/// loop-vectorizer report. It modifies the message to add the
/// loop-vectorizer-specific part of the message.
explicit VectorizationReport(const LoopAccessReport &R)
: LoopAccessReport(Twine("loop not vectorized: ") + R.str(),
R.getInstr()) {}
/// A helper function for converting Scalar types to vector types.
/// If the incoming type is void, we return void. If the VF is 1, we return
/// the scalar type.
static Type *ToVectorTy(Type *Scalar, unsigned VF) {
if (Scalar->isVoidTy() || VF == 1)
return Scalar;
return VectorType::get(Scalar, VF);
/// A helper function that returns GEP instruction and knows to skip a
/// 'bitcast'. The 'bitcast' may be skipped if the source and the destination
/// pointee types of the 'bitcast' have the same size.
/// For example:
/// bitcast double** %var to i64* - can be skipped
/// bitcast double** %var to i8* - can not
static GetElementPtrInst *getGEPInstruction(Value *Ptr) {
if (isa<GetElementPtrInst>(Ptr))
return cast<GetElementPtrInst>(Ptr);
if (isa<BitCastInst>(Ptr) &&
isa<GetElementPtrInst>(cast<BitCastInst>(Ptr)->getOperand(0))) {
Type *BitcastTy = Ptr->getType();
Type *GEPTy = cast<BitCastInst>(Ptr)->getSrcTy();
if (!isa<PointerType>(BitcastTy) || !isa<PointerType>(GEPTy))
return nullptr;
Type *Pointee1Ty = cast<PointerType>(BitcastTy)->getPointerElementType();
Type *Pointee2Ty = cast<PointerType>(GEPTy)->getPointerElementType();
const DataLayout &DL = cast<BitCastInst>(Ptr)->getModule()->getDataLayout();
if (DL.getTypeSizeInBits(Pointee1Ty) == DL.getTypeSizeInBits(Pointee2Ty))
return cast<GetElementPtrInst>(cast<BitCastInst>(Ptr)->getOperand(0));
return nullptr;
/// InnerLoopVectorizer vectorizes loops which contain only one basic
/// block to a specified vectorization factor (VF).
/// This class performs the widening of scalars into vectors, or multiple
/// scalars. This class also implements the following features:
/// * It inserts an epilogue loop for handling loops that don't have iteration
/// counts that are known to be a multiple of the vectorization factor.
/// * It handles the code generation for reduction variables.
/// * Scalarization (implementation using scalars) of un-vectorizable
/// instructions.
/// InnerLoopVectorizer does not perform any vectorization-legality
/// checks, and relies on the caller to check for the different legality
/// aspects. The InnerLoopVectorizer relies on the
/// LoopVectorizationLegality class to provide information about the induction
/// and reduction variables that were found to a given vectorization factor.
class InnerLoopVectorizer {
InnerLoopVectorizer(Loop *OrigLoop, PredicatedScalarEvolution &PSE,
LoopInfo *LI, DominatorTree *DT,
const TargetLibraryInfo *TLI,
const TargetTransformInfo *TTI, AssumptionCache *AC,
unsigned VecWidth, unsigned UnrollFactor)
: OrigLoop(OrigLoop), PSE(PSE), LI(LI), DT(DT), TLI(TLI), TTI(TTI),
AC(AC), VF(VecWidth), UF(UnrollFactor),
Builder(PSE.getSE()->getContext()), Induction(nullptr),
OldInduction(nullptr), WidenMap(UnrollFactor), TripCount(nullptr),
VectorTripCount(nullptr), Legal(nullptr), AddedSafetyChecks(false) {}
// Perform the actual loop widening (vectorization).
// MinimumBitWidths maps scalar integer values to the smallest bitwidth they
// can be validly truncated to. The cost model has assumed this truncation
// will happen when vectorizing.
void vectorize(LoopVectorizationLegality *L,
- MapVector<Instruction *, uint64_t> MinimumBitWidths) {
- MinBWs = MinimumBitWidths;
+ const MapVector<Instruction *, uint64_t> &MinimumBitWidths) {
+ MinBWs = &MinimumBitWidths;
Legal = L;
// Create a new empty loop. Unlink the old loop and connect the new one.
// Widen each instruction in the old loop to a new one in the new loop.
// Use the Legality module to find the induction and reduction variables.
// Return true if any runtime check is added.
bool areSafetyChecksAdded() { return AddedSafetyChecks; }
virtual ~InnerLoopVectorizer() {}
/// A small list of PHINodes.
typedef SmallVector<PHINode *, 4> PhiVector;
/// When we unroll loops we have multiple vector values for each scalar.
/// This data structure holds the unrolled and vectorized values that
/// originated from one scalar instruction.
typedef SmallVector<Value *, 2> VectorParts;
// When we if-convert we need to create edge masks. We have to cache values
// so that we don't end up with exponential recursion/IR.
typedef DenseMap<std::pair<BasicBlock *, BasicBlock *>, VectorParts>
/// Create an empty loop, based on the loop ranges of the old loop.
void createEmptyLoop();
/// Set up the values of the IVs correctly when exiting the vector loop.
void fixupIVUsers(PHINode *OrigPhi, const InductionDescriptor &II,
Value *CountRoundDown, Value *EndValue,
BasicBlock *MiddleBlock);
/// Create a new induction variable inside L.
PHINode *createInductionVariable(Loop *L, Value *Start, Value *End,
Value *Step, Instruction *DL);
/// Copy and widen the instructions from the old loop.
virtual void vectorizeLoop();
/// Fix a first-order recurrence. This is the second phase of vectorizing
/// this phi node.
void fixFirstOrderRecurrence(PHINode *Phi);
/// \brief The Loop exit block may have single value PHI nodes where the
/// incoming value is 'Undef'. While vectorizing we only handled real values
/// that were defined inside the loop. Here we fix the 'undef case'.
/// See PR14725.
void fixLCSSAPHIs();
/// Shrinks vector element sizes based on information in "MinBWs".
void truncateToMinimalBitwidths();
/// A helper function that computes the predicate of the block BB, assuming
/// that the header block of the loop is set to True. It returns the *entry*
/// mask for the block BB.
VectorParts createBlockInMask(BasicBlock *BB);
/// A helper function that computes the predicate of the edge between SRC
/// and DST.
VectorParts createEdgeMask(BasicBlock *Src, BasicBlock *Dst);
/// A helper function to vectorize a single BB within the innermost loop.
void vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV);
/// Vectorize a single PHINode in a block. This method handles the induction
/// variable canonicalization. It supports both VF = 1 for unrolled loops and
/// arbitrary length vectors.
void widenPHIInstruction(Instruction *PN, VectorParts &Entry, unsigned UF,
unsigned VF, PhiVector *PV);
/// Insert the new loop to the loop hierarchy and pass manager
/// and update the analysis passes.
void updateAnalysis();
/// This instruction is un-vectorizable. Implement it as a sequence
/// of scalars. If \p IfPredicateStore is true we need to 'hide' each
/// scalarized instruction behind an if block predicated on the control
/// dependence of the instruction.
virtual void scalarizeInstruction(Instruction *Instr,
bool IfPredicateStore = false);
/// Vectorize Load and Store instructions,
virtual void vectorizeMemoryInstruction(Instruction *Instr);
/// Create a broadcast instruction. This method generates a broadcast
/// instruction (shuffle) for loop invariant values and for the induction
/// value. If this is the induction variable then we extend it to N, N+1, ...
/// this is needed because each iteration in the loop corresponds to a SIMD
/// element.
virtual Value *getBroadcastInstrs(Value *V);
/// This function adds (StartIdx, StartIdx + Step, StartIdx + 2*Step, ...)
/// to each vector element of Val. The sequence starts at StartIndex.
virtual Value *getStepVector(Value *Val, int StartIdx, Value *Step);
/// This function adds (StartIdx, StartIdx + Step, StartIdx + 2*Step, ...)
/// to each vector element of Val. The sequence starts at StartIndex.
/// Step is a SCEV. In order to get StepValue it takes the existing value
/// from SCEV or creates a new using SCEVExpander.
virtual Value *getStepVector(Value *Val, int StartIdx, const SCEV *Step);
/// Create a vector induction variable based on an existing scalar one.
/// Currently only works for integer induction variables with a constant
/// step.
/// If TruncType is provided, instead of widening the original IV, we
/// widen a version of the IV truncated to TruncType.
void widenInductionVariable(const InductionDescriptor &II, VectorParts &Entry,
IntegerType *TruncType = nullptr);
/// When we go over instructions in the basic block we rely on previous
/// values within the current basic block or on loop invariant values.
/// When we widen (vectorize) values we place them in the map. If the values
/// are not within the map, they have to be loop invariant, so we simply
/// broadcast them into a vector.
VectorParts &getVectorValue(Value *V);
/// Try to vectorize the interleaved access group that \p Instr belongs to.
void vectorizeInterleaveGroup(Instruction *Instr);
/// Generate a shuffle sequence that will reverse the vector Vec.
virtual Value *reverseVector(Value *Vec);
/// Returns (and creates if needed) the original loop trip count.
Value *getOrCreateTripCount(Loop *NewLoop);
/// Returns (and creates if needed) the trip count of the widened loop.
Value *getOrCreateVectorTripCount(Loop *NewLoop);
/// Emit a bypass check to see if the trip count would overflow, or we
/// wouldn't have enough iterations to execute one vector loop.
void emitMinimumIterationCountCheck(Loop *L, BasicBlock *Bypass);
/// Emit a bypass check to see if the vector trip count is nonzero.
void emitVectorLoopEnteredCheck(Loop *L, BasicBlock *Bypass);
/// Emit a bypass check to see if all of the SCEV assumptions we've
/// had to make are correct.
void emitSCEVChecks(Loop *L, BasicBlock *Bypass);
/// Emit bypass checks to check any memory assumptions we may have made.
void emitMemRuntimeChecks(Loop *L, BasicBlock *Bypass);
/// Add additional metadata to \p To that was not present on \p Orig.
/// Currently this is used to add the noalias annotations based on the
/// inserted memchecks. Use this for instructions that are *cloned* into the
/// vector loop.
void addNewMetadata(Instruction *To, const Instruction *Orig);
/// Add metadata from one instruction to another.
/// This includes both the original MDs from \p From and additional ones (\see
/// addNewMetadata). Use this for *newly created* instructions in the vector
/// loop.
void addMetadata(Instruction *To, const Instruction *From);
/// \brief Similar to the previous function but it adds the metadata to a
/// vector of instructions.
void addMetadata(SmallVectorImpl<Value *> &To, const Instruction *From);
/// This is a helper class that holds the vectorizer state. It maps scalar
/// instructions to vector instructions. When the code is 'unrolled' then
/// then a single scalar value is mapped to multiple vector parts. The parts
/// are stored in the VectorPart type.
struct ValueMap {
/// C'tor. UnrollFactor controls the number of vectors ('parts') that
/// are mapped.
ValueMap(unsigned UnrollFactor) : UF(UnrollFactor) {}
/// \return True if 'Key' is saved in the Value Map.
bool has(Value *Key) const { return MapStorage.count(Key); }
/// Initializes a new entry in the map. Sets all of the vector parts to the
/// save value in 'Val'.
/// \return A reference to a vector with splat values.
VectorParts &splat(Value *Key, Value *Val) {
VectorParts &Entry = MapStorage[Key];
Entry.assign(UF, Val);
return Entry;
///\return A reference to the value that is stored at 'Key'.
VectorParts &get(Value *Key) {
VectorParts &Entry = MapStorage[Key];
if (Entry.empty())
assert(Entry.size() == UF);
return Entry;
/// The unroll factor. Each entry in the map stores this number of vector
/// elements.
unsigned UF;
/// Map storage. We use std::map and not DenseMap because insertions to a
/// dense map invalidates its iterators.
std::map<Value *, VectorParts> MapStorage;
/// The original loop.
Loop *OrigLoop;
/// A wrapper around ScalarEvolution used to add runtime SCEV checks. Applies
/// dynamic knowledge to simplify SCEV expressions and converts them to a
/// more usable form.
PredicatedScalarEvolution &PSE;
/// Loop Info.
LoopInfo *LI;
/// Dominator Tree.
DominatorTree *DT;
/// Alias Analysis.
AliasAnalysis *AA;
/// Target Library Info.
const TargetLibraryInfo *TLI;
/// Target Transform Info.
const TargetTransformInfo *TTI;
/// Assumption Cache.
AssumptionCache *AC;
/// \brief LoopVersioning. It's only set up (non-null) if memchecks were
/// used.
/// This is currently only used to add no-alias metadata based on the
/// memchecks. The actually versioning is performed manually.
std::unique_ptr<LoopVersioning> LVer;
/// The vectorization SIMD factor to use. Each vector will have this many
/// vector elements.
unsigned VF;
/// The vectorization unroll factor to use. Each scalar is vectorized to this
/// many different vector instructions.
unsigned UF;
/// The builder that we use
IRBuilder<> Builder;
// --- Vectorization state ---
/// The vector-loop preheader.
BasicBlock *LoopVectorPreHeader;
/// The scalar-loop preheader.
BasicBlock *LoopScalarPreHeader;
/// Middle Block between the vector and the scalar.
BasicBlock *LoopMiddleBlock;
/// The ExitBlock of the scalar loop.
BasicBlock *LoopExitBlock;
/// The vector loop body.
BasicBlock *LoopVectorBody;
/// The scalar loop body.
BasicBlock *LoopScalarBody;
/// A list of all bypass blocks. The first block is the entry of the loop.
SmallVector<BasicBlock *, 4> LoopBypassBlocks;
/// The new Induction variable which was added to the new block.
PHINode *Induction;
/// The induction variable of the old basic block.
PHINode *OldInduction;
/// Maps scalars to widened vectors.
ValueMap WidenMap;
/// Store instructions that should be predicated, as a pair
/// <StoreInst, Predicate>
SmallVector<std::pair<StoreInst *, Value *>, 4> PredicatedStores;
EdgeMaskCache MaskCache;
/// Trip count of the original loop.
Value *TripCount;
/// Trip count of the widened loop (TripCount - TripCount % (VF*UF))
Value *VectorTripCount;
/// Map of scalar integer values to the smallest bitwidth they can be legally
/// represented as. The vector equivalents of these values should be truncated
/// to this type.
- MapVector<Instruction *, uint64_t> MinBWs;
+ const MapVector<Instruction *, uint64_t> *MinBWs;
LoopVectorizationLegality *Legal;
// Record whether runtime checks are added.
bool AddedSafetyChecks;
class InnerLoopUnroller : public InnerLoopVectorizer {
InnerLoopUnroller(Loop *OrigLoop, PredicatedScalarEvolution &PSE,
LoopInfo *LI, DominatorTree *DT,
const TargetLibraryInfo *TLI,
const TargetTransformInfo *TTI, AssumptionCache *AC,
unsigned UnrollFactor)
: InnerLoopVectorizer(OrigLoop, PSE, LI, DT, TLI, TTI, AC, 1,
UnrollFactor) {}
void scalarizeInstruction(Instruction *Instr,
bool IfPredicateStore = false) override;
void vectorizeMemoryInstruction(Instruction *Instr) override;
Value *getBroadcastInstrs(Value *V) override;
Value *getStepVector(Value *Val, int StartIdx, Value *Step) override;
Value *getStepVector(Value *Val, int StartIdx, const SCEV *StepSCEV) override;
Value *reverseVector(Value *Vec) override;
/// \brief Look for a meaningful debug location on the instruction or it's
/// operands.
static Instruction *getDebugLocFromInstOrOperands(Instruction *I) {
if (!I)
return I;
DebugLoc Empty;
if (I->getDebugLoc() != Empty)
return I;
for (User::op_iterator OI = I->op_begin(), OE = I->op_end(); OI != OE; ++OI) {
if (Instruction *OpInst = dyn_cast<Instruction>(*OI))
if (OpInst->getDebugLoc() != Empty)
return OpInst;
return I;
/// \brief Set the debug location in the builder using the debug location in the
/// instruction.
static void setDebugLocFromInst(IRBuilder<> &B, const Value *Ptr) {
if (const Instruction *Inst = dyn_cast_or_null<Instruction>(Ptr))
#ifndef NDEBUG
/// \return string containing a file name and a line # for the given loop.
static std::string getDebugLocString(const Loop *L) {
std::string Result;
if (L) {
raw_string_ostream OS(Result);
if (const DebugLoc LoopDbgLoc = L->getStartLoc())
// Just print the module name.
OS << L->getHeader()->getParent()->getParent()->getModuleIdentifier();
return Result;
/// \brief Propagate known metadata from one instruction to another.
static void propagateMetadata(Instruction *To, const Instruction *From) {
SmallVector<std::pair<unsigned, MDNode *>, 4> Metadata;
for (auto M : Metadata) {
unsigned Kind = M.first;
// These are safe to transfer (this is safe for TBAA, even when we
// if-convert, because should that metadata have had a control dependency
// on the condition, and thus actually aliased with some other
// non-speculated memory access when the condition was false, this would be
// caught by the runtime overlap checks).
if (Kind != LLVMContext::MD_tbaa && Kind != LLVMContext::MD_alias_scope &&
Kind != LLVMContext::MD_noalias && Kind != LLVMContext::MD_fpmath &&
Kind != LLVMContext::MD_nontemporal)
To->setMetadata(Kind, M.second);
void InnerLoopVectorizer::addNewMetadata(Instruction *To,
const Instruction *Orig) {
// If the loop was versioned with memchecks, add the corresponding no-alias
// metadata.
if (LVer && (isa<LoadInst>(Orig) || isa<StoreInst>(Orig)))
LVer->annotateInstWithNoAlias(To, Orig);
void InnerLoopVectorizer::addMetadata(Instruction *To,
const Instruction *From) {
propagateMetadata(To, From);
addNewMetadata(To, From);
void InnerLoopVectorizer::addMetadata(SmallVectorImpl<Value *> &To,
const Instruction *From) {
for (Value *V : To)
if (Instruction *I = dyn_cast<Instruction>(V))
addMetadata(I, From);
/// \brief The group of interleaved loads/stores sharing the same stride and
/// close to each other.
/// Each member in this group has an index starting from 0, and the largest
/// index should be less than interleaved factor, which is equal to the absolute
/// value of the access's stride.
/// E.g. An interleaved load group of factor 4:
/// for (unsigned i = 0; i < 1024; i+=4) {
/// a = A[i]; // Member of index 0
/// b = A[i+1]; // Member of index 1
/// d = A[i+3]; // Member of index 3
/// ...
/// }
/// An interleaved store group of factor 4:
/// for (unsigned i = 0; i < 1024; i+=4) {
/// ...
/// A[i] = a; // Member of index 0
/// A[i+1] = b; // Member of index 1
/// A[i+2] = c; // Member of index 2
/// A[i+3] = d; // Member of index 3
/// }
/// Note: the interleaved load group could have gaps (missing members), but
/// the interleaved store group doesn't allow gaps.
class InterleaveGroup {
InterleaveGroup(Instruction *Instr, int Stride, unsigned Align)
: Align(Align), SmallestKey(0), LargestKey(0), InsertPos(Instr) {
assert(Align && "The alignment should be non-zero");
Factor = std::abs(Stride);
assert(Factor > 1 && "Invalid interleave factor");
Reverse = Stride < 0;
Members[0] = Instr;
bool isReverse() const { return Reverse; }
unsigned getFactor() const { return Factor; }
unsigned getAlignment() const { return Align; }
unsigned getNumMembers() const { return Members.size(); }
/// \brief Try to insert a new member \p Instr with index \p Index and
/// alignment \p NewAlign. The index is related to the leader and it could be
/// negative if it is the new leader.
/// \returns false if the instruction doesn't belong to the group.
bool insertMember(Instruction *Instr, int Index, unsigned NewAlign) {
assert(NewAlign && "The new member's alignment should be non-zero");
int Key = Index + SmallestKey;
// Skip if there is already a member with the same index.
if (Members.count(Key))
return false;
if (Key > LargestKey) {
// The largest index is always less than the interleave factor.
if (Index >= static_cast<int>(Factor))
return false;
LargestKey = Key;
} else if (Key < SmallestKey) {
// The largest index is always less than the interleave factor.
if (LargestKey - Key >= static_cast<int>(Factor))
return false;
SmallestKey = Key;
// It's always safe to select the minimum alignment.
Align = std::min(Align, NewAlign);
Members[Key] = Instr;
return true;
/// \brief Get the member with the given index \p Index
/// \returns nullptr if contains no such member.
Instruction *getMember(unsigned Index) const {
int Key = SmallestKey + Index;
if (!Members.count(Key))
return nullptr;
return Members.find(Key)->second;
/// \brief Get the index for the given member. Unlike the key in the member
/// map, the index starts from 0.
unsigned getIndex(Instruction *Instr) const {
for (auto I : Members)
if (I.second == Instr)
return I.first - SmallestKey;
llvm_unreachable("InterleaveGroup contains no such member");
Instruction *getInsertPos() const { return InsertPos; }
void setInsertPos(Instruction *Inst) { InsertPos = Inst; }
unsigned Factor; // Interleave Factor.
bool Reverse;
unsigned Align;
DenseMap<int, Instruction *> Members;
int SmallestKey;
int LargestKey;
// To avoid breaking dependences, vectorized instructions of an interleave
// group should be inserted at either the first load or the last store in
// program order.
// E.g. %even = load i32 // Insert Position
// %add = add i32 %even // Use of %even
// %odd = load i32
// store i32 %even
// %odd = add i32 // Def of %odd
// store i32 %odd // Insert Position
Instruction *InsertPos;
/// \brief Drive the analysis of interleaved memory accesses in the loop.
/// Use this class to analyze interleaved accesses only when we can vectorize
/// a loop. Otherwise it's meaningless to do analysis as the vectorization
/// on interleaved accesses is unsafe.
/// The analysis collects interleave groups and records the relationships
/// between the member and the group in a map.
class InterleavedAccessInfo {
InterleavedAccessInfo(PredicatedScalarEvolution &PSE, Loop *L,
DominatorTree *DT)
: PSE(PSE), TheLoop(L), DT(DT), RequiresScalarEpilogue(false) {}
~InterleavedAccessInfo() {
SmallSet<InterleaveGroup *, 4> DelSet;
// Avoid releasing a pointer twice.
for (auto &I : InterleaveGroupMap)
for (auto *Ptr : DelSet)
delete Ptr;
/// \brief Analyze the interleaved accesses and collect them in interleave
/// groups. Substitute symbolic strides using \p Strides.
void analyzeInterleaving(const ValueToValueMap &Strides);
/// \brief Check if \p Instr belongs to any interleave group.
bool isInterleaved(Instruction *Instr) const {
return InterleaveGroupMap.count(Instr);
/// \brief Return the maximum interleave factor of all interleaved groups.
unsigned getMaxInterleaveFactor() const {
unsigned MaxFactor = 1;
for (auto &Entry : InterleaveGroupMap)
MaxFactor = std::max(MaxFactor, Entry.second->getFactor());
return MaxFactor;
/// \brief Get the interleave group that \p Instr belongs to.
/// \returns nullptr if doesn't have such group.
InterleaveGroup *getInterleaveGroup(Instruction *Instr) const {
if (InterleaveGroupMap.count(Instr))
return InterleaveGroupMap.find(Instr)->second;
return nullptr;
/// \brief Returns true if an interleaved group that may access memory
/// out-of-bounds requires a scalar epilogue iteration for correctness.
bool requiresScalarEpilogue() const { return RequiresScalarEpilogue; }
/// A wrapper around ScalarEvolution, used to add runtime SCEV checks.
/// Simplifies SCEV expressions in the context of existing SCEV assumptions.
/// The interleaved access analysis can also add new predicates (for example
/// by versioning strides of pointers).
PredicatedScalarEvolution &PSE;
Loop *TheLoop;
DominatorTree *DT;
/// True if the loop may contain non-reversed interleaved groups with
/// out-of-bounds accesses. We ensure we don't speculatively access memory
/// out-of-bounds by executing at least one scalar epilogue iteration.
bool RequiresScalarEpilogue;
/// Holds the relationships between the members and the interleave group.
DenseMap<Instruction *, InterleaveGroup *> InterleaveGroupMap;
/// \brief The descriptor for a strided memory access.
struct StrideDescriptor {
StrideDescriptor(int Stride, const SCEV *Scev, unsigned Size,
unsigned Align)
: Stride(Stride), Scev(Scev), Size(Size), Align(Align) {}
StrideDescriptor() : Stride(0), Scev(nullptr), Size(0), Align(0) {}
int Stride; // The access's stride. It is negative for a reverse access.
const SCEV *Scev; // The scalar expression of this access
unsigned Size; // The size of the memory object.
unsigned Align; // The alignment of this access.
/// \brief Create a new interleave group with the given instruction \p Instr,
/// stride \p Stride and alignment \p Align.
/// \returns the newly created interleave group.
InterleaveGroup *createInterleaveGroup(Instruction *Instr, int Stride,
unsigned Align) {
assert(!InterleaveGroupMap.count(Instr) &&
"Already in an interleaved access group");
InterleaveGroupMap[Instr] = new InterleaveGroup(Instr, Stride, Align);
return InterleaveGroupMap[Instr];
/// \brief Release the group and remove all the relationships.
void releaseGroup(InterleaveGroup *Group) {
for (unsigned i = 0; i < Group->getFactor(); i++)
if (Instruction *Member = Group->getMember(i))
delete Group;
/// \brief Collect all the accesses with a constant stride in program order.
void collectConstStridedAccesses(
MapVector<Instruction *, StrideDescriptor> &StrideAccesses,
const ValueToValueMap &Strides);
/// Utility class for getting and setting loop vectorizer hints in the form
/// of loop metadata.
/// This class keeps a number of loop annotations locally (as member variables)
/// and can, upon request, write them back as metadata on the loop. It will
/// initially scan the loop for existing metadata, and will update the local
/// values based on information in the loop.
/// We cannot write all values to metadata, as the mere presence of some info,
/// for example 'force', means a decision has been made. So, we need to be
/// careful NOT to add them if the user hasn't specifically asked so.
class LoopVectorizeHints {
enum HintKind { HK_WIDTH, HK_UNROLL, HK_FORCE };
/// Hint - associates name and validation with the hint value.
struct Hint {
const char *Name;
unsigned Value; // This may have to change for non-numeric values.
HintKind Kind;
Hint(const char *Name, unsigned Value, HintKind Kind)
: Name(Name), Value(Value), Kind(Kind) {}
bool validate(unsigned Val) {
switch (Kind) {
case HK_WIDTH:
return isPowerOf2_32(Val) && Val <= VectorizerParams::MaxVectorWidth;
return isPowerOf2_32(Val) && Val <= MaxInterleaveFactor;
case HK_FORCE:
return (Val <= 1);
return false;
/// Vectorization width.
Hint Width;
/// Vectorization interleave factor.
Hint Interleave;
/// Vectorization forced
Hint Force;
/// Return the loop metadata prefix.
static StringRef Prefix() { return "llvm.loop."; }
/// True if there is any unsafe math in the loop.
bool PotentiallyUnsafe;
enum ForceKind {
FK_Undefined = -1, ///< Not selected.
FK_Disabled = 0, ///< Forcing disabled.
FK_Enabled = 1, ///< Forcing enabled.
LoopVectorizeHints(const Loop *L, bool DisableInterleaving)
: Width("vectorize.width", VectorizerParams::VectorizationFactor,
Interleave("interleave.count", DisableInterleaving, HK_UNROLL),
Force("vectorize.enable", FK_Undefined, HK_FORCE),
PotentiallyUnsafe(false), TheLoop(L) {
// Populate values with existing loop metadata.
// force-vector-interleave overrides DisableInterleaving.
if (VectorizerParams::isInterleaveForced())
Interleave.Value = VectorizerParams::VectorizationInterleave;
DEBUG(if (DisableInterleaving && Interleave.Value == 1) dbgs()
<< "LV: Interleaving disabled by the pass manager\n");
/// Mark the loop L as already vectorized by setting the width to 1.
void setAlreadyVectorized() {
Width.Value = Interleave.Value = 1;
Hint Hints[] = {Width, Interleave};
bool allowVectorization(Function *F, Loop *L, bool AlwaysVectorize) const {
if (getForce() == LoopVectorizeHints::FK_Disabled) {
DEBUG(dbgs() << "LV: Not vectorizing: #pragma vectorize disable.\n");
vectorizeAnalysisPassName(), *F,
L->getStartLoc(), emitRemark());
return false;
if (!AlwaysVectorize && getForce() != LoopVectorizeHints::FK_Enabled) {
DEBUG(dbgs() << "LV: Not vectorizing: No #pragma vectorize enable.\n");
vectorizeAnalysisPassName(), *F,
L->getStartLoc(), emitRemark());
return false;
if (getWidth() == 1 && getInterleave() == 1) {
// FIXME: Add a separate metadata to indicate when the loop has already
// been vectorized instead of setting width and count to 1.
DEBUG(dbgs() << "LV: Not vectorizing: Disabled/already vectorized.\n");
// FIXME: Add interleave.disable metadata. This will allow
// vectorize.disable to be used without disabling the pass and errors
// to differentiate between disabled vectorization and a width of 1.
F->getContext(), vectorizeAnalysisPassName(), *F, L->getStartLoc(),
"loop not vectorized: vectorization and interleaving are explicitly "
"disabled, or vectorize width and interleave count are both set to "
return false;
return true;
/// Dumps all the hint information.
std::string emitRemark() const {
VectorizationReport R;
if (Force.Value == LoopVectorizeHints::FK_Disabled)
R << "vectorization is explicitly disabled";
else {
R << "use -Rpass-analysis=loop-vectorize for more info";
if (Force.Value == LoopVectorizeHints::FK_Enabled) {
R << " (Force=true";
if (Width.Value != 0)
R << ", Vector Width=" << Width.Value;
if (Interleave.Value != 0)
R << ", Interleave Count=" << Interleave.Value;
R << ")";
return R.str();
unsigned getWidth() const { return Width.Value; }
unsigned getInterleave() const { return Interleave.Value; }
enum ForceKind getForce() const { return (ForceKind)Force.Value; }
const char *vectorizeAnalysisPassName() const {
// If hints are provided that don't disable vectorization use the
// AlwaysPrint pass name to force the frontend to print the diagnostic.
if (getWidth() == 1)
return LV_NAME;
if (getForce() == LoopVectorizeHints::FK_Disabled)
return LV_NAME;
if (getForce() == LoopVectorizeHints::FK_Undefined && getWidth() == 0)
return LV_NAME;
return DiagnosticInfo::AlwaysPrint;
bool allowReordering() const {
// When enabling loop hints are provided we allow the vectorizer to change
// the order of operations that is given by the scalar loop. This is not
// enabled by default because can be unsafe or inefficient. For example,
// reordering floating-point operations will change the way round-off
// error accumulates in the loop.
return getForce() == LoopVectorizeHints::FK_Enabled || getWidth() > 1;
bool isPotentiallyUnsafe() const {
// Avoid FP vectorization if the target is unsure about proper support.
// This may be related to the SIMD unit in the target not handling
// IEEE 754 FP ops properly, or bad single-to-double promotions.
// Otherwise, a sequence of vectorized loops, even without reduction,
// could lead to different end results on the destination vectors.
return getForce() != LoopVectorizeHints::FK_Enabled && PotentiallyUnsafe;
void setPotentiallyUnsafe() { PotentiallyUnsafe = true; }
/// Find hints specified in the loop metadata and update local values.
void getHintsFromMetadata() {
MDNode *LoopID = TheLoop->getLoopID();
if (!LoopID)
// First operand should refer to the loop id itself.
assert(LoopID->getNumOperands() > 0 && "requires at least one operand");
assert(LoopID->getOperand(0) == LoopID && "invalid loop id");
for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
const MDString *S = nullptr;
SmallVector<Metadata *, 4> Args;
// The expected hint is either a MDString or a MDNode with the first
// operand a MDString.
if (const MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i))) {
if (!MD || MD->getNumOperands() == 0)
S = dyn_cast<MDString>(MD->getOperand(0));
for (unsigned i = 1, ie = MD->getNumOperands(); i < ie; ++i)
} else {
S = dyn_cast<MDString>(LoopID->getOperand(i));
assert(Args.size() == 0 && "too many arguments for MDString");
if (!S)
// Check if the hint starts with the loop metadata prefix.
StringRef Name = S->getString();
if (Args.size() == 1)
setHint(Name, Args[0]);
/// Checks string hint with one operand and set value if valid.
void setHint(StringRef Name, Metadata *Arg) {
if (!Name.startswith(Prefix()))
Name = Name.substr(Prefix().size(), StringRef::npos);
const ConstantInt *C = mdconst::dyn_extract<ConstantInt>(Arg);
if (!C)
unsigned Val = C->getZExtValue();
Hint *Hints[] = {&Width, &Interleave, &Force};
for (auto H : Hints) {
if (Name == H->Name) {
if (H->validate(Val))
H->Value = Val;
DEBUG(dbgs() << "LV: ignoring invalid hint '" << Name << "'\n");
/// Create a new hint from name / value pair.
MDNode *createHintMetadata(StringRef Name, unsigned V) const {
LLVMContext &Context = TheLoop->getHeader()->getContext();
Metadata *MDs[] = {MDString::get(Context, Name),
ConstantInt::get(Type::getInt32Ty(Context), V))};
return MDNode::get(Context, MDs);
/// Matches metadata with hint name.
bool matchesHintMetadataName(MDNode *Node, ArrayRef<Hint> HintTypes) {
MDString *Name = dyn_cast<MDString>(Node->getOperand(0));
if (!Name)
return false;
for (auto H : HintTypes)
if (Name->getString().endswith(H.Name))
return true;
return false;
/// Sets current hints into loop metadata, keeping other values intact.
void writeHintsToMetadata(ArrayRef<Hint> HintTypes) {
if (HintTypes.size() == 0)
// Reserve the first element to LoopID (see below).
SmallVector<Metadata *, 4> MDs(1);
// If the loop already has metadata, then ignore the existing operands.
MDNode *LoopID = TheLoop->getLoopID();
if (LoopID) {
for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
MDNode *Node = cast<MDNode>(LoopID->getOperand(i));
// If node in update list, ignore old value.
if (!matchesHintMetadataName(Node, HintTypes))
// Now, add the missing hints.
for (auto H : HintTypes)
MDs.push_back(createHintMetadata(Twine(Prefix(), H.Name).str(), H.Value));
// Replace current metadata node with new one.
LLVMContext &Context = TheLoop->getHeader()->getContext();
MDNode *NewLoopID = MDNode::get(Context, MDs);
// Set operand 0 to refer to the loop id itself.
NewLoopID->replaceOperandWith(0, NewLoopID);
/// The loop these hints belong to.
const Loop *TheLoop;
static void emitAnalysisDiag(const Function *TheFunction, const Loop *TheLoop,
const LoopVectorizeHints &Hints,
const LoopAccessReport &Message) {
const char *Name = Hints.vectorizeAnalysisPassName();
LoopAccessReport::emitAnalysis(Message, TheFunction, TheLoop, Name);
static void emitMissedWarning(Function *F, Loop *L,
const LoopVectorizeHints &LH) {
emitOptimizationRemarkMissed(F->getContext(), LV_NAME, *F, L->getStartLoc(),
if (LH.getForce() == LoopVectorizeHints::FK_Enabled) {
if (LH.getWidth() != 1)
F->getContext(), *F, L->getStartLoc(),
"failed explicitly specified loop vectorization");
else if (LH.getInterleave() != 1)
F->getContext(), *F, L->getStartLoc(),
"failed explicitly specified loop interleaving");
/// LoopVectorizationLegality checks if it is legal to vectorize a loop, and
/// to what vectorization factor.
/// This class does not look at the profitability of vectorization, only the
/// legality. This class has two main kinds of checks:
/// * Memory checks - The code in canVectorizeMemory checks if vectorization
/// will change the order of memory accesses in a way that will change the
/// correctness of the program.
/// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory
/// checks for a number of different conditions, such as the availability of a
/// single induction variable, that all types are supported and vectorize-able,
/// etc. This code reflects the capabilities of InnerLoopVectorizer.
/// This class is also used by InnerLoopVectorizer for identifying
/// induction variable and the different reduction variables.
class LoopVectorizationLegality {
LoopVectorizationLegality(Loop *L, PredicatedScalarEvolution &PSE,
DominatorTree *DT, TargetLibraryInfo *TLI,
AliasAnalysis *AA, Function *F,
const TargetTransformInfo *TTI,
LoopAccessAnalysis *LAA,
LoopVectorizationRequirements *R,
LoopVectorizeHints *H)
: NumPredStores(0), TheLoop(L), PSE(PSE), TLI(TLI), TheFunction(F),
TTI(TTI), DT(DT), LAA(LAA), LAI(nullptr), InterleaveInfo(PSE, L, DT),
Induction(nullptr), WidestIndTy(nullptr), HasFunNoNaNAttr(false),
Requirements(R), Hints(H) {}
/// ReductionList contains the reduction descriptors for all
/// of the reductions that were found in the loop.
typedef DenseMap<PHINode *, RecurrenceDescriptor> ReductionList;
/// InductionList saves induction variables and maps them to the
/// induction descriptor.
typedef MapVector<PHINode *, InductionDescriptor> InductionList;
/// RecurrenceSet contains the phi nodes that are recurrences other than
/// inductions and reductions.
typedef SmallPtrSet<const PHINode *, 8> RecurrenceSet;
/// Returns true if it is legal to vectorize this loop.
/// This does not mean that it is profitable to vectorize this
/// loop, only that it is legal to do so.
bool canVectorize();
/// Returns the Induction variable.
PHINode *getInduction() { return Induction; }
/// Returns the reduction variables found in the loop.
ReductionList *getReductionVars() { return &Reductions; }
/// Returns the induction variables found in the loop.
InductionList *getInductionVars() { return &Inductions; }
/// Return the first-order recurrences found in the loop.
RecurrenceSet *getFirstOrderRecurrences() { return &FirstOrderRecurrences; }
/// Returns the widest induction type.
Type *getWidestInductionType() { return WidestIndTy; }
/// Returns True if V is an induction variable in this loop.
bool isInductionVariable(const Value *V);
/// Returns True if PN is a reduction variable in this loop.
bool isReductionVariable(PHINode *PN) { return Reductions.count(PN); }
/// Returns True if Phi is a first-order recurrence in this loop.
bool isFirstOrderRecurrence(const PHINode *Phi);
/// Return true if the block BB needs to be predicated in order for the loop
/// to be vectorized.
bool blockNeedsPredication(BasicBlock *BB);
/// Check if this pointer is consecutive when vectorizing. This happens
/// when the last index of the GEP is the induction variable, or that the
/// pointer itself is an induction variable.
/// This check allows us to vectorize A[idx] into a wide load/store.
/// Returns:
/// 0 - Stride is unknown or non-consecutive.
/// 1 - Address is consecutive.
/// -1 - Address is consecutive, and decreasing.
int isConsecutivePtr(Value *Ptr);
/// Returns true if the value V is uniform within the loop.
bool isUniform(Value *V);
/// Returns true if this instruction will remain scalar after vectorization.
bool isUniformAfterVectorization(Instruction *I) { return Uniforms.count(I); }
/// Returns the information that we collected about runtime memory check.
const RuntimePointerChecking *getRuntimePointerChecking() const {
return LAI->getRuntimePointerChecking();
const LoopAccessInfo *getLAI() const { return LAI; }
/// \brief Check if \p Instr belongs to any interleaved access group.
bool isAccessInterleaved(Instruction *Instr) {
return InterleaveInfo.isInterleaved(Instr);
/// \brief Return the maximum interleave factor of all interleaved groups.
unsigned getMaxInterleaveFactor() const {
return InterleaveInfo.getMaxInterleaveFactor();
/// \brief Get the interleaved access group that \p Instr belongs to.
const InterleaveGroup *getInterleavedAccessGroup(Instruction *Instr) {
return InterleaveInfo.getInterleaveGroup(Instr);
/// \brief Returns true if an interleaved group requires a scalar iteration
/// to handle accesses with gaps.
bool requiresScalarEpilogue() const {
return InterleaveInfo.requiresScalarEpilogue();
unsigned getMaxSafeDepDistBytes() { return LAI->getMaxSafeDepDistBytes(); }
bool hasStride(Value *V) { return LAI->hasStride(V); }
/// Returns true if the target machine supports masked store operation
/// for the given \p DataType and kind of access to \p Ptr.
bool isLegalMaskedStore(Type *DataType, Value *Ptr) {
return isConsecutivePtr(Ptr) && TTI->isLegalMaskedStore(DataType);
/// Returns true if the target machine supports masked load operation
/// for the given \p DataType and kind of access to \p Ptr.
bool isLegalMaskedLoad(Type *DataType, Value *Ptr) {
return isConsecutivePtr(Ptr) && TTI->isLegalMaskedLoad(DataType);
/// Returns true if the target machine supports masked scatter operation
/// for the given \p DataType.
bool isLegalMaskedScatter(Type *DataType) {
return TTI->isLegalMaskedScatter(DataType);
/// Returns true if the target machine supports masked gather operation
/// for the given \p DataType.
bool isLegalMaskedGather(Type *DataType) {
return TTI->isLegalMaskedGather(DataType);
/// Returns true if vector representation of the instruction \p I
/// requires mask.
bool isMaskRequired(const Instruction *I) { return (MaskedOp.count(I) != 0); }
unsigned getNumStores() const { return LAI->getNumStores(); }
unsigned getNumLoads() const { return LAI->getNumLoads(); }
unsigned getNumPredStores() const { return NumPredStores; }
/// Check if a single basic block loop is vectorizable.
/// At this point we know that this is a loop with a constant trip count
/// and we only need to check individual instructions.
bool canVectorizeInstrs();
/// When we vectorize loops we may change the order in which
/// we read and write from memory. This method checks if it is
/// legal to vectorize the code, considering only memory constrains.
/// Returns true if the loop is vectorizable
bool canVectorizeMemory();
/// Return true if we can vectorize this loop using the IF-conversion
/// transformation.
bool canVectorizeWithIfConvert();
/// Collect the variables that need to stay uniform after vectorization.
void collectLoopUniforms();
/// Return true if all of the instructions in the block can be speculatively
/// executed. \p SafePtrs is a list of addresses that are known to be legal
/// and we know that we can read from them without segfault.
bool blockCanBePredicated(BasicBlock *BB, SmallPtrSetImpl<Value *> &SafePtrs);
/// Updates the vectorization state by adding \p Phi to the inductions list.
/// This can set \p Phi as the main induction of the loop if \p Phi is a
/// better choice for the main induction than the existing one.
- void addInductionPhi(PHINode *Phi, InductionDescriptor ID,
+ void addInductionPhi(PHINode *Phi, const InductionDescriptor &ID,
SmallPtrSetImpl<Value *> &AllowedExit);
/// Report an analysis message to assist the user in diagnosing loops that are
/// not vectorized. These are handled as LoopAccessReport rather than
/// VectorizationReport because the << operator of VectorizationReport returns
/// LoopAccessReport.
void emitAnalysis(const LoopAccessReport &Message) const {
emitAnalysisDiag(TheFunction, TheLoop, *Hints, Message);
/// \brief If an access has a symbolic strides, this maps the pointer value to
/// the stride symbol.
const ValueToValueMap *getSymbolicStrides() {
// FIXME: Currently, the set of symbolic strides is sometimes queried before
// it's collected. This happens from canVectorizeWithIfConvert, when the
// pointer is checked to reference consecutive elements suitable for a
// masked access.
return LAI ? &LAI->getSymbolicStrides() : nullptr;
unsigned NumPredStores;
/// The loop that we evaluate.
Loop *TheLoop;
/// A wrapper around ScalarEvolution used to add runtime SCEV checks.
/// Applies dynamic knowledge to simplify SCEV expressions in the context
/// of existing SCEV assumptions. The analysis will also add a minimal set
/// of new predicates if this is required to enable vectorization and
/// unrolling.
PredicatedScalarEvolution &PSE;
/// Target Library Info.
TargetLibraryInfo *TLI;
/// Parent function
Function *TheFunction;
/// Target Transform Info
const TargetTransformInfo *TTI;
/// Dominator Tree.
DominatorTree *DT;
// LoopAccess analysis.
LoopAccessAnalysis *LAA;
// And the loop-accesses info corresponding to this loop. This pointer is
// null until canVectorizeMemory sets it up.
const LoopAccessInfo *LAI;
/// The interleave access information contains groups of interleaved accesses
/// with the same stride and close to each other.
InterleavedAccessInfo InterleaveInfo;
// --- vectorization state --- //
/// Holds the integer induction variable. This is the counter of the
/// loop.
PHINode *Induction;
/// Holds the reduction variables.
ReductionList Reductions;
/// Holds all of the induction variables that we found in the loop.
/// Notice that inductions don't need to start at zero and that induction
/// variables can be pointers.
InductionList Inductions;
/// Holds the phi nodes that are first-order recurrences.
RecurrenceSet FirstOrderRecurrences;
/// Holds the widest induction type encountered.
Type *WidestIndTy;
/// Allowed outside users. This holds the induction and reduction
/// vars which can be accessed from outside the loop.
SmallPtrSet<Value *, 4> AllowedExit;
/// This set holds the variables which are known to be uniform after
/// vectorization.
SmallPtrSet<Instruction *, 4> Uniforms;
/// Can we assume the absence of NaNs.
bool HasFunNoNaNAttr;
/// Vectorization requirements that will go through late-evaluation.
LoopVectorizationRequirements *Requirements;
/// Used to emit an analysis of any legality issues.
LoopVectorizeHints *Hints;
/// While vectorizing these instructions we have to generate a
/// call to the appropriate masked intrinsic
SmallPtrSet<const Instruction *, 8> MaskedOp;
/// LoopVectorizationCostModel - estimates the expected speedups due to
/// vectorization.
/// In many cases vectorization is not profitable. This can happen because of
/// a number of reasons. In this class we mainly attempt to predict the
/// expected speedup/slowdowns due to the supported instruction set. We use the
/// TargetTransformInfo to query the different backends for the cost of
/// different operations.
class LoopVectorizationCostModel {
LoopVectorizationCostModel(Loop *L, PredicatedScalarEvolution &PSE,
LoopInfo *LI, LoopVectorizationLegality *Legal,
const TargetTransformInfo &TTI,
const TargetLibraryInfo *TLI, DemandedBits *DB,
AssumptionCache *AC, const Function *F,
const LoopVectorizeHints *Hints)
: TheLoop(L), PSE(PSE), LI(LI), Legal(Legal), TTI(TTI), TLI(TLI), DB(DB),
AC(AC), TheFunction(F), Hints(Hints) {}
/// Information about vectorization costs
struct VectorizationFactor {
unsigned Width; // Vector width with best cost
unsigned Cost; // Cost of the loop with that width
/// \return The most profitable vectorization factor and the cost of that VF.
/// This method checks every power of two up to VF. If UserVF is not ZERO
/// then this vectorization factor will be selected if vectorization is
/// possible.
VectorizationFactor selectVectorizationFactor(bool OptForSize);
/// \return The size (in bits) of the smallest and widest types in the code
/// that needs to be vectorized. We ignore values that remain scalar such as
/// 64 bit loop indices.
std::pair<unsigned, unsigned> getSmallestAndWidestTypes();
/// \return The desired interleave count.
/// If interleave count has been specified by metadata it will be returned.
/// Otherwise, the interleave count is computed and returned. VF and LoopCost
/// are the selected vectorization factor and the cost of the selected VF.
unsigned selectInterleaveCount(bool OptForSize, unsigned VF,
unsigned LoopCost);
/// \return The most profitable unroll factor.
/// This method finds the best unroll-factor based on register pressure and
/// other parameters. VF and LoopCost are the selected vectorization factor
/// and the cost of the selected VF.
unsigned computeInterleaveCount(bool OptForSize, unsigned VF,
unsigned LoopCost);
/// \brief A struct that represents some properties of the register usage
/// of a loop.
struct RegisterUsage {
/// Holds the number of loop invariant values that are used in the loop.
unsigned LoopInvariantRegs;
/// Holds the maximum number of concurrent live intervals in the loop.
unsigned MaxLocalUsers;
/// Holds the number of instructions in the loop.
unsigned NumInstructions;
/// \return Returns information about the register usages of the loop for the
/// given vectorization factors.
SmallVector<RegisterUsage, 8> calculateRegisterUsage(ArrayRef<unsigned> VFs);
/// Collect values we want to ignore in the cost model.
void collectValuesToIgnore();
/// The vectorization cost is a combination of the cost itself and a boolean
/// indicating whether any of the contributing operations will actually
/// operate on
/// vector values after type legalization in the backend. If this latter value
/// is
/// false, then all operations will be scalarized (i.e. no vectorization has
/// actually taken place).
typedef std::pair<unsigned, bool> VectorizationCostTy;
/// Returns the expected execution cost. The unit of the cost does
/// not matter because we use the 'cost' units to compare different
/// vector widths. The cost that is returned is *not* normalized by
/// the factor width.
VectorizationCostTy expectedCost(unsigned VF);
/// Returns the execution time cost of an instruction for a given vector
/// width. Vector width of one means scalar.
VectorizationCostTy getInstructionCost(Instruction *I, unsigned VF);
/// The cost-computation logic from getInstructionCost which provides
/// the vector type as an output parameter.
unsigned getInstructionCost(Instruction *I, unsigned VF, Type *&VectorTy);
/// Returns whether the instruction is a load or store and will be a emitted
/// as a vector operation.
bool isConsecutiveLoadOrStore(Instruction *I);
/// Report an analysis message to assist the user in diagnosing loops that are
/// not vectorized. These are handled as LoopAccessReport rather than
/// VectorizationReport because the << operator of VectorizationReport returns
/// LoopAccessReport.
void emitAnalysis(const LoopAccessReport &Message) const {
emitAnalysisDiag(TheFunction, TheLoop, *Hints, Message);
/// Map of scalar integer values to the smallest bitwidth they can be legally
/// represented as. The vector equivalents of these values should be truncated
/// to this type.
MapVector<Instruction *, uint64_t> MinBWs;
/// The loop that we evaluate.
Loop *TheLoop;
/// Predicated scalar evolution analysis.
PredicatedScalarEvolution &PSE;
/// Loop Info analysis.
LoopInfo *LI;
/// Vectorization legality.
LoopVectorizationLegality *Legal;
/// Vector target information.
const TargetTransformInfo &TTI;
/// Target Library Info.
const TargetLibraryInfo *TLI;
/// Demanded bits analysis.
DemandedBits *DB;
/// Assumption cache.
AssumptionCache *AC;
const Function *TheFunction;
/// Loop Vectorize Hint.
const LoopVectorizeHints *Hints;
/// Values to ignore in the cost model.
SmallPtrSet<const Value *, 16> ValuesToIgnore;
/// Values to ignore in the cost model when VF > 1.
SmallPtrSet<const Value *, 16> VecValuesToIgnore;
/// \brief This holds vectorization requirements that must be verified late in
/// the process. The requirements are set by legalize and costmodel. Once
/// vectorization has been determined to be possible and profitable the
/// requirements can be verified by looking for metadata or compiler options.
/// For example, some loops require FP commutativity which is only allowed if
/// vectorization is explicitly specified or if the fast-math compiler option
/// has been provided.
/// Late evaluation of these requirements allows helpful diagnostics to be
/// composed that tells the user what need to be done to vectorize the loop. For
/// example, by specifying #pragma clang loop vectorize or -ffast-math. Late
/// evaluation should be used only when diagnostics can generated that can be
/// followed by a non-expert user.
class LoopVectorizationRequirements {
: NumRuntimePointerChecks(0), UnsafeAlgebraInst(nullptr) {}
void addUnsafeAlgebraInst(Instruction *I) {
// First unsafe algebra instruction.
if (!UnsafeAlgebraInst)
UnsafeAlgebraInst = I;
void addRuntimePointerChecks(unsigned Num) { NumRuntimePointerChecks = Num; }
bool doesNotMeet(Function *F, Loop *L, const LoopVectorizeHints &Hints) {
const char *Name = Hints.vectorizeAnalysisPassName();
bool Failed = false;
if (UnsafeAlgebraInst && !Hints.allowReordering()) {
F->getContext(), Name, *F, UnsafeAlgebraInst->getDebugLoc(),
VectorizationReport() << "cannot prove it is safe to reorder "
"floating-point operations");
Failed = true;
// Test if runtime memcheck thresholds are exceeded.
bool PragmaThresholdReached =
NumRuntimePointerChecks > PragmaVectorizeMemoryCheckThreshold;
bool ThresholdReached =
NumRuntimePointerChecks > VectorizerParams::RuntimeMemoryCheckThreshold;
if ((ThresholdReached && !Hints.allowReordering()) ||
PragmaThresholdReached) {
F->getContext(), Name, *F, L->getStartLoc(),
<< "cannot prove it is safe to reorder memory operations");
DEBUG(dbgs() << "LV: Too many memory checks needed.\n");
Failed = true;
return Failed;
unsigned NumRuntimePointerChecks;
Instruction *UnsafeAlgebraInst;
static void addInnerLoop(Loop &L, SmallVectorImpl<Loop *> &V) {
if (L.empty())
return V.push_back(&L);
for (Loop *InnerL : L)
addInnerLoop(*InnerL, V);
/// The LoopVectorize Pass.
struct LoopVectorize : public FunctionPass {
/// Pass identification, replacement for typeid
static char ID;
explicit LoopVectorize(bool NoUnrolling = false, bool AlwaysVectorize = true)
: FunctionPass(ID), DisableUnrolling(NoUnrolling),
AlwaysVectorize(AlwaysVectorize) {
ScalarEvolution *SE;
LoopInfo *LI;
TargetTransformInfo *TTI;
DominatorTree *DT;
BlockFrequencyInfo *BFI;
TargetLibraryInfo *TLI;
DemandedBits *DB;
AliasAnalysis *AA;
AssumptionCache *AC;
LoopAccessAnalysis *LAA;
bool DisableUnrolling;
bool AlwaysVectorize;
BlockFrequency ColdEntryFreq;
bool runOnFunction(Function &F) override {
if (skipFunction(F))
return false;
SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE();
LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F);
DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
BFI = &getAnalysis<BlockFrequencyInfoWrapperPass>().getBFI();
auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>();
TLI = TLIP ? &TLIP->getTLI() : nullptr;
AA = &getAnalysis<AAResultsWrapperPass>().getAAResults();
AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F);
LAA = &getAnalysis<LoopAccessAnalysis>();
DB = &getAnalysis<DemandedBitsWrapperPass>().getDemandedBits();
// Compute some weights outside of the loop over the loops. Compute this
// using a BranchProbability to re-use its scaling math.
const BranchProbability ColdProb(1, 5); // 20%
ColdEntryFreq = BlockFrequency(BFI->getEntryFreq()) * ColdProb;
// Don't attempt if
// 1. the target claims to have no vector registers, and
// 2. interleaving won't help ILP.
// The second condition is necessary because, even if the target has no
// vector registers, loop vectorization may still enable scalar
// interleaving.
if (!TTI->getNumberOfRegisters(true) && TTI->getMaxInterleaveFactor(1) < 2)
return false;
// Build up a worklist of inner-loops to vectorize. This is necessary as
// the act of vectorizing or partially unrolling a loop creates new loops
// and can invalidate iterators across the loops.
SmallVector<Loop *, 8> Worklist;
for (Loop *L : *LI)
addInnerLoop(*L, Worklist);
LoopsAnalyzed += Worklist.size();
// Now walk the identified inner loops.
bool Changed = false;
while (!Worklist.empty())
Changed |= processLoop(Worklist.pop_back_val());
// Process each loop nest in the function.
return Changed;
static void AddRuntimeUnrollDisableMetaData(Loop *L) {
SmallVector<Metadata *, 4> MDs;
// Reserve first location for self reference to the LoopID metadata node.
bool IsUnrollMetadata = false;
MDNode *LoopID = L->getLoopID();
if (LoopID) {
// First find existing loop unrolling disable metadata.
for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i));
if (MD) {
const MDString *S = dyn_cast<MDString>(MD->getOperand(0));
IsUnrollMetadata =
S && S->getString().startswith("llvm.loop.unroll.disable");
if (!IsUnrollMetadata) {
// Add runtime unroll disable metadata.
LLVMContext &Context = L->getHeader()->getContext();
SmallVector<Metadata *, 1> DisableOperands;
MDString::get(Context, "llvm.loop.unroll.runtime.disable"));
MDNode *DisableNode = MDNode::get(Context, DisableOperands);
MDNode *NewLoopID = MDNode::get(Context, MDs);
// Set operand 0 to refer to the loop id itself.
NewLoopID->replaceOperandWith(0, NewLoopID);
bool processLoop(Loop *L) {
assert(L->empty() && "Only process inner loops.");
#ifndef NDEBUG
const std::string DebugLocStr = getDebugLocString(L);
#endif /* NDEBUG */
DEBUG(dbgs() << "\nLV: Checking a loop in \""
<< L->getHeader()->getParent()->getName() << "\" from "
<< DebugLocStr << "\n");
LoopVectorizeHints Hints(L, DisableUnrolling);
DEBUG(dbgs() << "LV: Loop hints:"
<< " force="
<< (Hints.getForce() == LoopVectorizeHints::FK_Disabled
? "disabled"
: (Hints.getForce() == LoopVectorizeHints::FK_Enabled
? "enabled"
: "?"))
<< " width=" << Hints.getWidth()
<< " unroll=" << Hints.getInterleave() << "\n");
// Function containing loop
Function *F = L->getHeader()->getParent();
// Looking at the diagnostic output is the only way to determine if a loop
// was vectorized (other than looking at the IR or machine code), so it
// is important to generate an optimization remark for each loop. Most of
// these messages are generated by emitOptimizationRemarkAnalysis. Remarks
// generated by emitOptimizationRemark and emitOptimizationRemarkMissed are
// less verbose reporting vectorized loops and unvectorized loops that may
// benefit from vectorization, respectively.
if (!Hints.allowVectorization(F, L, AlwaysVectorize)) {
DEBUG(dbgs() << "LV: Loop hints prevent vectorization.\n");
return false;
// Check the loop for a trip count threshold:
// do not vectorize loops with a tiny trip count.
const unsigned TC = SE->getSmallConstantTripCount(L);
if (TC > 0u && TC < TinyTripCountVectorThreshold) {
DEBUG(dbgs() << "LV: Found a loop with a very small trip count. "
<< "This loop is not worth vectorizing.");
if (Hints.getForce() == LoopVectorizeHints::FK_Enabled)
DEBUG(dbgs() << " But vectorizing was explicitly forced.\n");
else {
DEBUG(dbgs() << "\n");
emitAnalysisDiag(F, L, Hints, VectorizationReport()
<< "vectorization is not beneficial "
"and is not explicitly forced");
return false;
PredicatedScalarEvolution PSE(*SE, *L);
// Check if it is legal to vectorize the loop.
LoopVectorizationRequirements Requirements;
LoopVectorizationLegality LVL(L, PSE, DT, TLI, AA, F, TTI, LAA,
&Requirements, &Hints);
if (!LVL.canVectorize()) {
DEBUG(dbgs() << "LV: Not vectorizing: Cannot prove legality.\n");
emitMissedWarning(F, L, Hints);
return false;
// Use the cost model.
LoopVectorizationCostModel CM(L, PSE, LI, &LVL, *TTI, TLI, DB, AC, F,
// Check the function attributes to find out if this function should be
// optimized for size.
bool OptForSize =
Hints.getForce() != LoopVectorizeHints::FK_Enabled && F->optForSize();
// Compute the weighted frequency of this loop being executed and see if it
// is less than 20% of the function entry baseline frequency. Note that we
// always have a canonical loop here because we think we *can* vectorize.
// FIXME: This is hidden behind a flag due to pervasive problems with
// exactly what block frequency models.
if (LoopVectorizeWithBlockFrequency) {
BlockFrequency LoopEntryFreq = BFI->getBlockFreq(L->getLoopPreheader());
if (Hints.getForce() != LoopVectorizeHints::FK_Enabled &&
LoopEntryFreq < ColdEntryFreq)
OptForSize = true;
// Check the function attributes to see if implicit floats are allowed.
// FIXME: This check doesn't seem possibly correct -- what if the loop is
// an integer loop and the vector instructions selected are purely integer
// vector instructions?
if (F->hasFnAttribute(Attribute::NoImplicitFloat)) {
DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat"
"attribute is used.\n");
F, L, Hints,
<< "loop not vectorized due to NoImplicitFloat attribute");
emitMissedWarning(F, L, Hints);
return false;
// Check if the target supports potentially unsafe FP vectorization.
// FIXME: Add a check for the type of safety issue (denormal, signaling)
// for the target we're vectorizing for, to make sure none of the
// additional fp-math flags can help.
if (Hints.isPotentiallyUnsafe() &&
TTI->isFPVectorizationPotentiallyUnsafe()) {
DEBUG(dbgs() << "LV: Potentially unsafe FP op prevents vectorization.\n");
emitAnalysisDiag(F, L, Hints,
<< "loop not vectorized due to unsafe FP support.");
emitMissedWarning(F, L, Hints);
return false;
// Select the optimal vectorization factor.
const LoopVectorizationCostModel::VectorizationFactor VF =
// Select the interleave count.
unsigned IC = CM.selectInterleaveCount(OptForSize, VF.Width, VF.Cost);
// Get user interleave count.
unsigned UserIC = Hints.getInterleave();
// Identify the diagnostic messages that should be produced.
std::string VecDiagMsg, IntDiagMsg;
bool VectorizeLoop = true, InterleaveLoop = true;
if (Requirements.doesNotMeet(F, L, Hints)) {
DEBUG(dbgs() << "LV: Not vectorizing: loop did not meet vectorization "
emitMissedWarning(F, L, Hints);
return false;
if (VF.Width == 1) {
DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n");
VecDiagMsg =
"the cost-model indicates that vectorization is not beneficial";
VectorizeLoop = false;
if (IC == 1 && UserIC <= 1) {
// Tell the user interleaving is not beneficial.
DEBUG(dbgs() << "LV: Interleaving is not beneficial.\n");
IntDiagMsg =
"the cost-model indicates that interleaving is not beneficial";
InterleaveLoop = false;
if (UserIC == 1)
IntDiagMsg +=
" and is explicitly disabled or interleave count is set to 1";
} else if (IC > 1 && UserIC == 1) {
// Tell the user interleaving is beneficial, but it explicitly disabled.
<< "LV: Interleaving is beneficial but is explicitly disabled.");
IntDiagMsg = "the cost-model indicates that interleaving is beneficial "
"but is explicitly disabled or interleave count is set to 1";
InterleaveLoop = false;
// Override IC if user provided an interleave count.
IC = UserIC > 0 ? UserIC : IC;
// Emit diagnostic messages, if any.
const char *VAPassName = Hints.vectorizeAnalysisPassName();
if (!VectorizeLoop && !InterleaveLoop) {
// Do not vectorize or interleaving the loop.
emitOptimizationRemarkAnalysis(F->getContext(), VAPassName, *F,
L->getStartLoc(), VecDiagMsg);
emitOptimizationRemarkAnalysis(F->getContext(), LV_NAME, *F,
L->getStartLoc(), IntDiagMsg);
return false;
} else if (!VectorizeLoop && InterleaveLoop) {
DEBUG(dbgs() << "LV: Interleave Count is " << IC << '\n');
emitOptimizationRemarkAnalysis(F->getContext(), VAPassName, *F,
L->getStartLoc(), VecDiagMsg);
} else if (VectorizeLoop && !InterleaveLoop) {
DEBUG(dbgs() << "LV: Found a vectorizable loop (" << VF.Width << ") in "
<< DebugLocStr << '\n');
emitOptimizationRemarkAnalysis(F->getContext(), LV_NAME, *F,
L->getStartLoc(), IntDiagMsg);
} else if (VectorizeLoop && InterleaveLoop) {
DEBUG(dbgs() << "LV: Found a vectorizable loop (" << VF.Width << ") in "
<< DebugLocStr << '\n');
DEBUG(dbgs() << "LV: Interleave Count is " << IC << '\n');
if (!VectorizeLoop) {
assert(IC > 1 && "interleave count should not be 1 or 0");
// If we decided that it is not legal to vectorize the loop, then
// interleave it.
InnerLoopUnroller Unroller(L, PSE, LI, DT, TLI, TTI, AC, IC);
Unroller.vectorize(&LVL, CM.MinBWs);
emitOptimizationRemark(F->getContext(), LV_NAME, *F, L->getStartLoc(),
Twine("interleaved loop (interleaved count: ") +
Twine(IC) + ")");
} else {
// If we decided that it is *legal* to vectorize the loop, then do it.
InnerLoopVectorizer LB(L, PSE, LI, DT, TLI, TTI, AC, VF.Width, IC);
LB.vectorize(&LVL, CM.MinBWs);
// Add metadata to disable runtime unrolling a scalar loop when there are
// no runtime checks about strides and memory. A scalar loop that is
// rarely used is not worth unrolling.
if (!LB.areSafetyChecksAdded())
// Report the vectorization decision.
emitOptimizationRemark(F->getContext(), LV_NAME, *F, L->getStartLoc(),
Twine("vectorized loop (vectorization width: ") +
Twine(VF.Width) + ", interleaved count: " +
Twine(IC) + ")");
// Mark the loop as already vectorized to avoid vectorizing again.
return true;
void getAnalysisUsage(AnalysisUsage &AU) const override {
} // end anonymous namespace
// Implementation of LoopVectorizationLegality, InnerLoopVectorizer and
// LoopVectorizationCostModel.
Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) {
// We need to place the broadcast of invariant variables outside the loop.
Instruction *Instr = dyn_cast<Instruction>(V);
bool NewInstr = (Instr && Instr->getParent() == LoopVectorBody);
bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr;
// Place the code for broadcasting invariant variables in the new preheader.
IRBuilder<>::InsertPointGuard Guard(Builder);
if (Invariant)
// Broadcast the scalar into all locations in the vector.
Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast");
return Shuf;
Value *InnerLoopVectorizer::getStepVector(Value *Val, int StartIdx,
const SCEV *StepSCEV) {
const DataLayout &DL = OrigLoop->getHeader()->getModule()->getDataLayout();
SCEVExpander Exp(*PSE.getSE(), DL, "induction");
Value *StepValue = Exp.expandCodeFor(StepSCEV, StepSCEV->getType(),
return getStepVector(Val, StartIdx, StepValue);
void InnerLoopVectorizer::widenInductionVariable(const InductionDescriptor &II,
VectorParts &Entry,
IntegerType *TruncType) {
Value *Start = II.getStartValue();
ConstantInt *Step = II.getConstIntStepValue();
assert(Step && "Can not widen an IV with a non-constant step");
// Construct the initial value of the vector IV in the vector loop preheader
auto CurrIP = Builder.saveIP();
if (TruncType) {
Step = ConstantInt::getSigned(TruncType, Step->getSExtValue());
Start = Builder.CreateCast(Instruction::Trunc, Start, TruncType);
Value *SplatStart = Builder.CreateVectorSplat(VF, Start);
Value *SteppedStart = getStepVector(SplatStart, 0, Step);
Value *SplatVF =
ConstantVector::getSplat(VF, ConstantInt::getSigned(Start->getType(),
VF * Step->getSExtValue()));
// We may need to add the step a number of times, depending on the unroll
// factor. The last of those goes into the PHI.
PHINode *VecInd = PHINode::Create(SteppedStart->getType(), 2, "vec.ind",
Value *LastInduction = VecInd;
for (unsigned Part = 0; Part < UF; ++Part) {
Entry[Part] = LastInduction;
LastInduction = Builder.CreateAdd(LastInduction, SplatVF, "step.add");
VecInd->addIncoming(SteppedStart, LoopVectorPreHeader);
VecInd->addIncoming(LastInduction, LoopVectorBody);
Value *InnerLoopVectorizer::getStepVector(Value *Val, int StartIdx,
Value *Step) {
assert(Val->getType()->isVectorTy() && "Must be a vector");
assert(Val->getType()->getScalarType()->isIntegerTy() &&
"Elem must be an integer");
assert(Step->getType() == Val->getType()->getScalarType() &&
"Step has wrong type");
// Create the types.
Type *ITy = Val->getType()->getScalarType();
VectorType *Ty = cast<VectorType>(Val->getType());
int VLen = Ty->getNumElements();
SmallVector<Constant *, 8> Indices;
// Create a vector of consecutive numbers from zero to VF.
for (int i = 0; i < VLen; ++i)
Indices.push_back(ConstantInt::get(ITy, StartIdx + i));
// Add the consecutive indices to the vector value.
Constant *Cv = ConstantVector::get(Indices);
assert(Cv->getType() == Val->getType() && "Invalid consecutive vec");
Step = Builder.CreateVectorSplat(VLen, Step);
assert(Step->getType() == Val->getType() && "Invalid step vec");
// FIXME: The newly created binary instructions should contain nsw/nuw flags,
// which can be found from the original scalar operations.
Step = Builder.CreateMul(Cv, Step);
return Builder.CreateAdd(Val, Step, "induction");
int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) {
assert(Ptr->getType()->isPointerTy() && "Unexpected non-ptr");
auto *SE = PSE.getSE();
// Make sure that the pointer does not point to structs.
if (Ptr->getType()->getPointerElementType()->isAggregateType())
return 0;
// If this value is a pointer induction variable, we know it is consecutive.
PHINode *Phi = dyn_cast_or_null<PHINode>(Ptr);
if (Phi && Inductions.count(Phi)) {
InductionDescriptor II = Inductions[Phi];
return II.getConsecutiveDirection();
GetElementPtrInst *Gep = getGEPInstruction(Ptr);
if (!Gep)
return 0;
unsigned NumOperands = Gep->getNumOperands();
Value *GpPtr = Gep->getPointerOperand();
// If this GEP value is a consecutive pointer induction variable and all of
// the indices are constant, then we know it is consecutive.
Phi = dyn_cast<PHINode>(GpPtr);
if (Phi && Inductions.count(Phi)) {
// Make sure that the pointer does not point to structs.
PointerType *GepPtrType = cast<PointerType>(GpPtr->getType());
if (GepPtrType->getElementType()->isAggregateType())
return 0;
// Make sure that all of the index operands are loop invariant.
for (unsigned i = 1; i < NumOperands; ++i)
if (!SE->isLoopInvariant(PSE.getSCEV(Gep->getOperand(i)), TheLoop))
return 0;
InductionDescriptor II = Inductions[Phi];
return II.getConsecutiveDirection();
unsigned InductionOperand = getGEPInductionOperand(Gep);
// Check that all of the gep indices are uniform except for our induction
// operand.
for (unsigned i = 0; i != NumOperands; ++i)
if (i != InductionOperand &&
!SE->isLoopInvariant(PSE.getSCEV(Gep->getOperand(i)), TheLoop))
return 0;
// We can emit wide load/stores only if the last non-zero index is the
// induction variable.
const SCEV *Last = nullptr;
if (!getSymbolicStrides() || !getSymbolicStrides()->count(Gep))
Last = PSE.getSCEV(Gep->getOperand(InductionOperand));
else {
// Because of the multiplication by a stride we can have a s/zext cast.
// We are going to replace this stride by 1 so the cast is safe to ignore.
// %indvars.iv = phi i64 [ 0, %entry ], [, %for.body ]
// %0 = trunc i64 %indvars.iv to i32
// %mul = mul i32 %0, %Stride1
// %idxprom = zext i32 %mul to i64 << Safe cast.
// %arrayidx = getelementptr inbounds i32* %B, i64 %idxprom
Last = replaceSymbolicStrideSCEV(PSE, *getSymbolicStrides(),
Gep->getOperand(InductionOperand), Gep);
if (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(Last))
Last =
(C->getSCEVType() == scSignExtend || C->getSCEVType() == scZeroExtend)
? C->getOperand()
: Last;
if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Last)) {
const SCEV *Step = AR->getStepRecurrence(*SE);
// The memory is consecutive because the last index is consecutive
// and all other indices are loop invariant.
if (Step->isOne())
return 1;
if (Step->isAllOnesValue())
return -1;
return 0;
bool LoopVectorizationLegality::isUniform(Value *V) {
return LAI->isUniform(V);
InnerLoopVectorizer::VectorParts &
InnerLoopVectorizer::getVectorValue(Value *V) {
assert(V != Induction && "The new induction variable should not be used.");
assert(!V->getType()->isVectorTy() && "Can't widen a vector");
// If we have a stride that is replaced by one, do it here.
if (Legal->hasStride(V))
V = ConstantInt::get(V->getType(), 1);
// If we have this scalar in the map, return it.
if (WidenMap.has(V))
return WidenMap.get(V);
// If this scalar is unknown, assume that it is a constant or that it is
// loop invariant. Broadcast V and save the value for future uses.
Value *B = getBroadcastInstrs(V);
return WidenMap.splat(V, B);
Value *InnerLoopVectorizer::reverseVector(Value *Vec) {
assert(Vec->getType()->isVectorTy() && "Invalid type");
SmallVector<Constant *, 8> ShuffleMask;
for (unsigned i = 0; i < VF; ++i)
ShuffleMask.push_back(Builder.getInt32(VF - i - 1));
return Builder.CreateShuffleVector(Vec, UndefValue::get(Vec->getType()),
// Get a mask to interleave \p NumVec vectors into a wide vector.
// I.e. <0, VF, VF*2, ..., VF*(NumVec-1), 1, VF+1, VF*2+1, ...>
// E.g. For 2 interleaved vectors, if VF is 4, the mask is:
// <0, 4, 1, 5, 2, 6, 3, 7>
static Constant *getInterleavedMask(IRBuilder<> &Builder, unsigned VF,
unsigned NumVec) {
SmallVector<Constant *, 16> Mask;
for (unsigned i = 0; i < VF; i++)
for (unsigned j = 0; j < NumVec; j++)
Mask.push_back(Builder.getInt32(j * VF + i));
return ConstantVector::get(Mask);
// Get the strided mask starting from index \p Start.
// I.e. <Start, Start + Stride, ..., Start + Stride*(VF-1)>
static Constant *getStridedMask(IRBuilder<> &Builder, unsigned Start,
unsigned Stride, unsigned VF) {
SmallVector<Constant *, 16> Mask;
for (unsigned i = 0; i < VF; i++)
Mask.push_back(Builder.getInt32(Start + i * Stride));
return ConstantVector::get(Mask);
// Get a mask of two parts: The first part consists of sequential integers
// starting from 0, The second part consists of UNDEFs.
// I.e. <0, 1, 2, ..., NumInt - 1, undef, ..., undef>
static Constant *getSequentialMask(IRBuilder<> &Builder, unsigned NumInt,
unsigned NumUndef) {
SmallVector<Constant *, 16> Mask;
for (unsigned i = 0; i < NumInt; i++)
Constant *Undef = UndefValue::get(Builder.getInt32Ty());
for (unsigned i = 0; i < NumUndef; i++)
return ConstantVector::get(Mask);
// Concatenate two vectors with the same element type. The 2nd vector should
// not have more elements than the 1st vector. If the 2nd vector has less
// elements, extend it with UNDEFs.
static Value *ConcatenateTwoVectors(IRBuilder<> &Builder, Value *V1,
Value *V2) {
VectorType *VecTy1 = dyn_cast<VectorType>(V1->getType());
VectorType *VecTy2 = dyn_cast<VectorType>(V2->getType());
assert(VecTy1 && VecTy2 &&
VecTy1->getScalarType() == VecTy2->getScalarType() &&
"Expect two vectors with the same element type");
unsigned NumElts1 = VecTy1->getNumElements();
unsigned NumElts2 = VecTy2->getNumElements();
assert(NumElts1 >= NumElts2 && "Unexpect the first vector has less elements");
if (NumElts1 > NumElts2) {
// Extend with UNDEFs.
Constant *ExtMask =
getSequentialMask(Builder, NumElts2, NumElts1 - NumElts2);
V2 = Builder.CreateShuffleVector(V2, UndefValue::get(VecTy2), ExtMask);
Constant *Mask = getSequentialMask(Builder, NumElts1 + NumElts2, 0);
return Builder.CreateShuffleVector(V1, V2, Mask);
// Concatenate vectors in the given list. All vectors have the same type.
static Value *ConcatenateVectors(IRBuilder<> &Builder,
ArrayRef<Value *> InputList) {
unsigned NumVec = InputList.size();
assert(NumVec > 1 && "Should be at least two vectors");
SmallVector<Value *, 8> ResList;
ResList.append(InputList.begin(), InputList.end());
do {
SmallVector<Value *, 8> TmpList;
for (unsigned i = 0; i < NumVec - 1; i += 2) {
Value *V0 = ResList[i], *V1 = ResList[i + 1];
assert((V0->getType() == V1->getType() || i == NumVec - 2) &&
"Only the last vector may have a different type");
TmpList.push_back(ConcatenateTwoVectors(Builder, V0, V1));
// Push the last vector if the total number of vectors is odd.
if (NumVec % 2 != 0)
TmpList.push_back(ResList[NumVec - 1]);
ResList = TmpList;
NumVec = ResList.size();
} while (NumVec > 1);
return ResList[0];
// Try to vectorize the interleave group that \p Instr belongs to.
// E.g. Translate following interleaved load group (factor = 3):
// for (i = 0; i < N; i+=3) {
// R = Pic[i]; // Member of index 0
// G = Pic[i+1]; // Member of index 1
// B = Pic[i+2]; // Member of index 2
// ... // do something to R, G, B
// }
// To:
// %wide.vec = load <12 x i32> ; Read 4 tuples of R,G,B
// %R.vec = shuffle %wide.vec, undef, <0, 3, 6, 9> ; R elements
// %G.vec = shuffle %wide.vec, undef, <1, 4, 7, 10> ; G elements
// %B.vec = shuffle %wide.vec, undef, <2, 5, 8, 11> ; B elements
// Or translate following interleaved store group (factor = 3):
// for (i = 0; i < N; i+=3) {
// ... do something to R, G, B
// Pic[i] = R; // Member of index 0
// Pic[i+1] = G; // Member of index 1
// Pic[i+2] = B; // Member of index 2
// }
// To:
// %R_G.vec = shuffle %R.vec, %G.vec, <0, 1, 2, ..., 7>
// %B_U.vec = shuffle %B.vec, undef, <0, 1, 2, 3, u, u, u, u>
// %interleaved.vec = shuffle %R_G.vec, %B_U.vec,
// <0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7, 11> ; Interleave R,G,B elements
// store <12 x i32> %interleaved.vec ; Write 4 tuples of R,G,B
void InnerLoopVectorizer::vectorizeInterleaveGroup(Instruction *Instr) {
const InterleaveGroup *Group = Legal->getInterleavedAccessGroup(Instr);
assert(Group && "Fail to get an interleaved access group.");
// Skip if current instruction is not the insert position.
if (Instr != Group->getInsertPos())
LoadInst *LI = dyn_cast<LoadInst>(Instr);
StoreInst *SI = dyn_cast<StoreInst>(Instr);
Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand();
// Prepare for the vector type of the interleaved load/store.
Type *ScalarTy = LI ? LI->getType() : SI->getValueOperand()->getType();
unsigned InterleaveFactor = Group->getFactor();
Type *VecTy = VectorType::get(ScalarTy, InterleaveFactor * VF);
Type *PtrTy = VecTy->getPointerTo(Ptr->getType()->getPointerAddressSpace());
// Prepare for the new pointers.
setDebugLocFromInst(Builder, Ptr);
VectorParts &PtrParts = getVectorValue(Ptr);
SmallVector<Value *, 2> NewPtrs;
unsigned Index = Group->getIndex(Instr);
for (unsigned Part = 0; Part < UF; Part++) {
// Extract the pointer for current instruction from the pointer vector. A
// reverse access uses the pointer in the last lane.
Value *NewPtr = Builder.CreateExtractElement(
Group->isReverse() ? Builder.getInt32(VF - 1) : Builder.getInt32(0));
// Notice current instruction could be any index. Need to adjust the address
// to the member of index 0.
// E.g. a = A[i+1]; // Member of index 1 (Current instruction)
// b = A[i]; // Member of index 0
// Current pointer is pointed to A[i+1], adjust it to A[i].
// E.g. A[i+1] = a; // Member of index 1
// A[i] = b; // Member of index 0
// A[i+2] = c; // Member of index 2 (Current instruction)
// Current pointer is pointed to A[i+2], adjust it to A[i].
NewPtr = Builder.CreateGEP(NewPtr, Builder.getInt32(-Index));
// Cast to the vector pointer type.
NewPtrs.push_back(Builder.CreateBitCast(NewPtr, PtrTy));
setDebugLocFromInst(Builder, Instr);
Value *UndefVec = UndefValue::get(VecTy);
// Vectorize the interleaved load group.
if (LI) {
for (unsigned Part = 0; Part < UF; Part++) {
Instruction *NewLoadInstr = Builder.CreateAlignedLoad(
NewPtrs[Part], Group->getAlignment(), "wide.vec");
for (unsigned i = 0; i < InterleaveFactor; i++) {
Instruction *Member = Group->getMember(i);
// Skip the gaps in the group.
if (!Member)
Constant *StrideMask = getStridedMask(Builder, i, InterleaveFactor, VF);
Value *StridedVec = Builder.CreateShuffleVector(
NewLoadInstr, UndefVec, StrideMask, "strided.vec");
// If this member has different type, cast the result type.
if (Member->getType() != ScalarTy) {
VectorType *OtherVTy = VectorType::get(Member->getType(), VF);
StridedVec = Builder.CreateBitOrPointerCast(StridedVec, OtherVTy);
VectorParts &Entry = WidenMap.get(Member);
Entry[Part] =
Group->isReverse() ? reverseVector(StridedVec) : StridedVec;
addMetadata(NewLoadInstr, Instr);
// The sub vector type for current instruction.
VectorType *SubVT = VectorType::get(ScalarTy, VF);
// Vectorize the interleaved store group.
for (unsigned Part = 0; Part < UF; Part++) {
// Collect the stored vector from each member.
SmallVector<Value *, 4> StoredVecs;
for (unsigned i = 0; i < InterleaveFactor; i++) {
// Interleaved store group doesn't allow a gap, so each index has a member
Instruction *Member = Group->getMember(i);
assert(Member && "Fail to get a member from an interleaved store group");
Value *StoredVec =
if (Group->isReverse())
StoredVec = reverseVector(StoredVec);
// If this member has different type, cast it to an unified type.
if (StoredVec->getType() != SubVT)
StoredVec = Builder.CreateBitOrPointerCast(StoredVec, SubVT);
// Concatenate all vectors into a wide vector.
Value *WideVec = ConcatenateVectors(Builder, StoredVecs);
// Interleave the elements in the wide vector.
Constant *IMask = getInterleavedMask(Builder, VF, InterleaveFactor);
Value *IVec = Builder.CreateShuffleVector(WideVec, UndefVec, IMask,
Instruction *NewStoreInstr =
Builder.CreateAlignedStore(IVec, NewPtrs[Part], Group->getAlignment());
addMetadata(NewStoreInstr, Instr);
void InnerLoopVectorizer::vectorizeMemoryInstruction(Instruction *Instr) {
// Attempt to issue a wide load.
LoadInst *LI = dyn_cast<LoadInst>(Instr);
StoreInst *SI = dyn_cast<StoreInst>(Instr);
assert((LI || SI) && "Invalid Load/Store instruction");
// Try to vectorize the interleave group if this access is interleaved.
if (Legal->isAccessInterleaved(Instr))
return vectorizeInterleaveGroup(Instr);
Type *ScalarDataTy = LI ? LI->getType() : SI->getValueOperand()->getType();
Type *DataTy = VectorType::get(ScalarDataTy, VF);
Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand();
unsigned Alignment = LI ? LI->getAlignment() : SI->getAlignment();
// An alignment of 0 means target abi alignment. We need to use the scalar's
// target abi alignment in such a case.
const DataLayout &DL = Instr->getModule()->getDataLayout();
if (!Alignment)
Alignment = DL.getABITypeAlignment(ScalarDataTy);
unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace();
unsigned ScalarAllocatedSize = DL.getTypeAllocSize(ScalarDataTy);
unsigned VectorElementSize = DL.getTypeStoreSize(DataTy) / VF;
if (SI && Legal->blockNeedsPredication(SI->getParent()) &&
return scalarizeInstruction(Instr, true);
if (ScalarAllocatedSize != VectorElementSize)
return scalarizeInstruction(Instr);
// If the pointer is loop invariant scalarize the load.
if (LI && Legal->isUniform(Ptr))
return scalarizeInstruction(Instr);
// If the pointer is non-consecutive and gather/scatter is not supported
// scalarize the instruction.
int ConsecutiveStride = Legal->isConsecutivePtr(Ptr);
bool Reverse = ConsecutiveStride < 0;
bool CreateGatherScatter =
!ConsecutiveStride && ((LI && Legal->isLegalMaskedGather(ScalarDataTy)) ||
(SI && Legal->isLegalMaskedScatter(ScalarDataTy)));
if (!ConsecutiveStride && !CreateGatherScatter)
return scalarizeInstruction(Instr);
Constant *Zero = Builder.getInt32(0);
VectorParts &Entry = WidenMap.get(Instr);
VectorParts VectorGep;
// Handle consecutive loads/stores.
GetElementPtrInst *Gep = getGEPInstruction(Ptr);
if (ConsecutiveStride) {
if (Gep && Legal->isInductionVariable(Gep->getPointerOperand())) {
setDebugLocFromInst(Builder, Gep);
Value *PtrOperand = Gep->getPointerOperand();
Value *FirstBasePtr = getVectorValue(PtrOperand)[0];
FirstBasePtr = Builder.CreateExtractElement(FirstBasePtr, Zero);
// Create the new GEP with the new induction variable.
GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
Gep2->setOperand(0, FirstBasePtr);
Ptr = Builder.Insert(Gep2);
} else if (Gep) {
setDebugLocFromInst(Builder, Gep);
OrigLoop) &&
"Base ptr must be invariant");
// The last index does not have to be the induction. It can be
// consecutive and be a function of the index. For example A[I+1];
unsigned NumOperands = Gep->getNumOperands();
unsigned InductionOperand = getGEPInductionOperand(Gep);
// Create the new GEP with the new induction variable.
GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
for (unsigned i = 0; i < NumOperands; ++i) {
Value *GepOperand = Gep->getOperand(i);
Instruction *GepOperandInst = dyn_cast<Instruction>(GepOperand);
// Update last index or loop invariant instruction anchored in loop.
if (i == InductionOperand ||
(GepOperandInst && OrigLoop->contains(GepOperandInst))) {
assert((i == InductionOperand ||
OrigLoop)) &&
"Must be last index or loop invariant");
VectorParts &GEPParts = getVectorValue(GepOperand);
Value *Index = GEPParts[0];
Index = Builder.CreateExtractElement(Index, Zero);
Gep2->setOperand(i, Index);
Ptr = Builder.Insert(Gep2);
} else { // No GEP
// Use the induction element ptr.
assert(isa<PHINode>(Ptr) && "Invalid induction ptr");
setDebugLocFromInst(Builder, Ptr);
VectorParts &PtrVal = getVectorValue(Ptr);
Ptr = Builder.CreateExtractElement(PtrVal[0], Zero);
} else {
// At this point we should vector version of GEP for Gather or Scatter
assert(CreateGatherScatter && "The instruction should be scalarized");
if (Gep) {
SmallVector<VectorParts, 4> OpsV;
// Vectorizing GEP, across UF parts, we want to keep each loop-invariant
// base or index of GEP scalar
for (Value *Op : Gep->operands()) {
if (PSE.getSE()->isLoopInvariant(PSE.getSCEV(Op), OrigLoop))
OpsV.push_back(VectorParts(UF, Op));
for (unsigned Part = 0; Part < UF; ++Part) {
SmallVector<Value *, 4> Ops;
Value *GEPBasePtr = OpsV[0][Part];
for (unsigned i = 1; i < Gep->getNumOperands(); i++)
Value *NewGep =
Builder.CreateGEP(nullptr, GEPBasePtr, Ops, "VectorGep");
assert(NewGep->getType()->isVectorTy() && "Expected vector GEP");
NewGep =
Builder.CreateBitCast(NewGep, VectorType::get(Ptr->getType(), VF));
} else
VectorGep = getVectorValue(Ptr);
VectorParts Mask = createBlockInMask(Instr->getParent());
// Handle Stores:
if (SI) {
assert(!Legal->isUniform(SI->getPointerOperand()) &&
"We do not allow storing to uniform addresses");
setDebugLocFromInst(Builder, SI);
// We don't want to update the value in the map as it might be used in
// another expression. So don't use a reference type for "StoredVal".
VectorParts StoredVal = getVectorValue(SI->getValueOperand());
for (unsigned Part = 0; Part < UF; ++Part) {
Instruction *NewSI = nullptr;
if (CreateGatherScatter) {
Value *MaskPart = Legal->isMaskRequired(SI) ? Mask[Part] : nullptr;
NewSI = Builder.CreateMaskedScatter(StoredVal[Part], VectorGep[Part],
Alignment, MaskPart);
} else {
// Calculate the pointer for the specific unroll-part.
Value *PartPtr =
Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(Part * VF));
if (Reverse) {
// If we store to reverse consecutive memory locations, then we need
// to reverse the order of elements in the stored value.
StoredVal[Part] = reverseVector(StoredVal[Part]);
// If the address is consecutive but reversed, then the
// wide store needs to start at the last vector element.
PartPtr =
Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(-Part * VF));
PartPtr =
Builder.CreateGEP(nullptr, PartPtr, Builder.getInt32(1 - VF));
Mask[Part] = reverseVector(Mask[Part]);
Value *VecPtr =
Builder.CreateBitCast(PartPtr, DataTy->getPointerTo(AddressSpace));
if (Legal->isMaskRequired(SI))
NewSI = Builder.CreateMaskedStore(StoredVal[Part], VecPtr, Alignment,
NewSI =
Builder.CreateAlignedStore(StoredVal[Part], VecPtr, Alignment);
addMetadata(NewSI, SI);
// Handle loads.
assert(LI && "Must have a load instruction");
setDebugLocFromInst(Builder, LI);
for (unsigned Part = 0; Part < UF; ++Part) {
Instruction *NewLI;
if (CreateGatherScatter) {
Value *MaskPart = Legal->isMaskRequired(LI) ? Mask[Part] : nullptr;
NewLI = Builder.CreateMaskedGather(VectorGep[Part], Alignment, MaskPart,
0, "wide.masked.gather");
Entry[Part] = NewLI;
} else {
// Calculate the pointer for the specific unroll-part.
Value *PartPtr =
Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(Part * VF));
if (Reverse) {
// If the address is consecutive but reversed, then the
// wide load needs to start at the last vector element.
PartPtr = Builder.CreateGEP(nullptr, Ptr, Builder.getInt32(-Part * VF));
PartPtr = Builder.CreateGEP(nullptr, PartPtr, Builder.getInt32(1 - VF));
Mask[Part] = reverseVector(Mask[Part]);
Value *VecPtr =
Builder.CreateBitCast(PartPtr, DataTy->getPointerTo(AddressSpace));
if (Legal->isMaskRequired(LI))
NewLI = Builder.CreateMaskedLoad(VecPtr, Alignment, Mask[Part],
NewLI = Builder.CreateAlignedLoad(VecPtr, Alignment, "wide.load");
Entry[Part] = Reverse ? reverseVector(NewLI) : NewLI;
addMetadata(NewLI, LI);
void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr,
bool IfPredicateStore) {
assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
// Holds vector parameters or scalars, in case of uniform vals.
SmallVector<VectorParts, 4> Params;
setDebugLocFromInst(Builder, Instr);
// Find all of the vectorized parameters.
for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
Value *SrcOp = Instr->getOperand(op);
// If we are accessing the old induction variable, use the new one.
if (SrcOp == OldInduction) {
// Try using previously calculated values.
Instruction *SrcInst = dyn_cast<Instruction>(SrcOp);
// If the src is an instruction that appeared earlier in the basic block,
// then it should already be vectorized.
if (SrcInst && OrigLoop->contains(SrcInst)) {
assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
// The parameter is a vector value from earlier.
} else {
// The parameter is a scalar from outside the loop. Maybe even a constant.
VectorParts Scalars;
Scalars.append(UF, SrcOp);
assert(Params.size() == Instr->getNumOperands() &&
"Invalid number of operands");
// Does this instruction return a value ?
bool IsVoidRetTy = Instr->getType()->isVoidTy();
Value *UndefVec =
IsVoidRetTy ? nullptr
: UndefValue::get(VectorType::get(Instr->getType(), VF));
// Create a new entry in the WidenMap and initialize it to Undef or Null.
VectorParts &VecResults = WidenMap.splat(Instr, UndefVec);
VectorParts Cond;
if (IfPredicateStore) {
assert(Instr->getParent()->getSinglePredecessor() &&
"Only support single predecessor blocks");
Cond = createEdgeMask(Instr->getParent()->getSinglePredecessor(),
// For each vector unroll 'part':
for (unsigned Part = 0; Part < UF; ++Part) {
// For each scalar that we create:
for (unsigned Width = 0; Width < VF; ++Width) {
// Start if-block.
Value *Cmp = nullptr;
if (IfPredicateStore) {
Cmp = Builder.CreateExtractElement(Cond[Part], Builder.getInt32(Width));
Cmp = Builder.CreateICmp(ICmpInst::ICMP_EQ, Cmp,
ConstantInt::get(Cmp->getType(), 1));
Instruction *Cloned = Instr->clone();
if (!IsVoidRetTy)
Cloned->setName(Instr->getName() + ".cloned");
// Replace the operands of the cloned instructions with extracted scalars.
for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
Value *Op = Params[op][Part];
// Param is a vector. Need to extract the right lane.
if (Op->getType()->isVectorTy())
Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width));
Cloned->setOperand(op, Op);
addNewMetadata(Cloned, Instr);
// Place the cloned scalar in the new loop.
// If we just cloned a new assumption, add it the assumption cache.
if (auto *II = dyn_cast<IntrinsicInst>(Cloned))
if (II->getIntrinsicID() == Intrinsic::assume)
// If the original scalar returns a value we need to place it in a vector
// so that future users will be able to use it.
if (!IsVoidRetTy)
VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned,
// End if-block.
if (IfPredicateStore)
std::make_pair(cast<StoreInst>(Cloned), Cmp));
PHINode *InnerLoopVectorizer::createInductionVariable(Loop *L, Value *Start,
Value *End, Value *Step,
Instruction *DL) {
BasicBlock *Header = L->getHeader();
BasicBlock *Latch = L->getLoopLatch();
// As we're just creating this loop, it's possible no latch exists
// yet. If so, use the header as this will be a single block loop.
if (!Latch)
Latch = Header;
IRBuilder<> Builder(&*Header->getFirstInsertionPt());
setDebugLocFromInst(Builder, getDebugLocFromInstOrOperands(OldInduction));
auto *Induction = Builder.CreatePHI(Start->getType(), 2, "index");
// Create i+1 and fill the PHINode.
Value *Next = Builder.CreateAdd(Induction, Step, "");
Induction->addIncoming(Start, L->getLoopPreheader());
Induction->addIncoming(Next, Latch);
// Create the compare.
Value *ICmp = Builder.CreateICmpEQ(Next, End);
Builder.CreateCondBr(ICmp, L->getExitBlock(), Header);
// Now we have two terminators. Remove the old one from the block.
return Induction;
Value *InnerLoopVectorizer::getOrCreateTripCount(Loop *L) {
if (TripCount)
return TripCount;
IRBuilder<> Builder(L->getLoopPreheader()->getTerminator());
// Find the loop boundaries.
ScalarEvolution *SE = PSE.getSE();
const SCEV *BackedgeTakenCount = PSE.getBackedgeTakenCount();
assert(BackedgeTakenCount != SE->getCouldNotCompute() &&
"Invalid loop count");
Type *IdxTy = Legal->getWidestInductionType();
// The exit count might have the type of i64 while the phi is i32. This can
// happen if we have an induction variable that is sign extended before the
// compare. The only way that we get a backedge taken count is that the
// induction variable was signed and as such will not overflow. In such a case
// truncation is legal.
if (BackedgeTakenCount->getType()->getPrimitiveSizeInBits() >
BackedgeTakenCount = SE->getTruncateOrNoop(BackedgeTakenCount, IdxTy);
BackedgeTakenCount = SE->getNoopOrZeroExtend(BackedgeTakenCount, IdxTy);
// Get the total trip count from the count by adding 1.
const SCEV *ExitCount = SE->getAddExpr(
BackedgeTakenCount, SE->getOne(BackedgeTakenCount->getType()));
const DataLayout &DL = L->getHeader()->getModule()->getDataLayout();
// Expand the trip count and place the new instructions in the preheader.
// Notice that the pre-header does not change, only the loop body.
SCEVExpander Exp(*SE, DL, "induction");
// Count holds the overall loop count (N).
TripCount = Exp.expandCodeFor(ExitCount, ExitCount->getType(),
if (TripCount->getType()->isPointerTy())
TripCount =
CastInst::CreatePointerCast(TripCount, IdxTy, "",
return TripCount;
Value *InnerLoopVectorizer::getOrCreateVectorTripCount(Loop *L) {
if (VectorTripCount)
return VectorTripCount;
Value *TC = getOrCreateTripCount(L);
IRBuilder<> Builder(L->getLoopPreheader()->getTerminator());
// Now we need to generate the expression for the part of the loop that the
// vectorized body will execute. This is equal to N - (N % Step) if scalar
// iterations are not required for correctness, or N - Step, otherwise. Step
// is equal to the vectorization factor (number of SIMD elements) times the
// unroll factor (number of SIMD instructions).
Constant *Step = ConstantInt::get(TC->getType(), VF * UF);
Value *R = Builder.CreateURem(TC, Step, "n.mod.vf");
// If there is a non-reversed interleaved group that may speculatively access
// memory out-of-bounds, we need to ensure that there will be at least one
// iteration of the scalar epilogue loop. Thus, if the step evenly divides
// the trip count, we set the remainder to be equal to the step. If the step
// does not evenly divide the trip count, no adjustment is necessary since
// there will already be scalar iterations. Note that the minimum iterations
// check ensures that N >= Step.
if (VF > 1 && Legal->requiresScalarEpilogue()) {
auto *IsZero = Builder.CreateICmpEQ(R, ConstantInt::get(R->getType(), 0));
R = Builder.CreateSelect(IsZero, Step, R);
VectorTripCount = Builder.CreateSub(TC, R, "n.vec");
return VectorTripCount;
void InnerLoopVectorizer::emitMinimumIterationCountCheck(Loop *L,
BasicBlock *Bypass) {
Value *Count = getOrCreateTripCount(L);
BasicBlock *BB = L->getLoopPreheader();
IRBuilder<> Builder(BB->getTerminator());
// Generate code to check that the loop's trip count that we computed by
// adding one to the backedge-taken count will not overflow.
Value *CheckMinIters = Builder.CreateICmpULT(
Count, ConstantInt::get(Count->getType(), VF * UF), "min.iters.check");
BasicBlock *NewBB =
BB->splitBasicBlock(BB->getTerminator(), "min.iters.checked");
// Update dominator tree immediately if the generated block is a
// LoopBypassBlock because SCEV expansions to generate loop bypass
// checks may query it before the current function is finished.
DT->addNewBlock(NewBB, BB);
if (L->getParentLoop())
L->getParentLoop()->addBasicBlockToLoop(NewBB, *LI);
BranchInst::Create(Bypass, NewBB, CheckMinIters));
void InnerLoopVectorizer::emitVectorLoopEnteredCheck(Loop *L,
BasicBlock *Bypass) {
Value *TC = getOrCreateVectorTripCount(L);
BasicBlock *BB = L->getLoopPreheader();
IRBuilder<> Builder(BB->getTerminator());
// Now, compare the new count to zero. If it is zero skip the vector loop and
// jump to the scalar loop.
Value *Cmp = Builder.CreateICmpEQ(TC, Constant::getNullValue(TC->getType()),
// Generate code to check that the loop's trip count that we computed by
// adding one to the backedge-taken count will not overflow.
BasicBlock *NewBB = BB->splitBasicBlock(BB->getTerminator(), "");
// Update dominator tree immediately if the generated block is a
// LoopBypassBlock because SCEV expansions to generate loop bypass
// checks may query it before the current function is finished.
DT->addNewBlock(NewBB, BB);
if (L->getParentLoop())
L->getParentLoop()->addBasicBlockToLoop(NewBB, *LI);
BranchInst::Create(Bypass, NewBB, Cmp));
void InnerLoopVectorizer::emitSCEVChecks(Loop *L, BasicBlock *Bypass) {
BasicBlock *BB = L->getLoopPreheader();
// Generate the code to check that the SCEV assumptions that we made.
// We want the new basic block to start at the first instruction in a
// sequence of instructions that form a check.
SCEVExpander Exp(*PSE.getSE(), Bypass->getModule()->getDataLayout(),
Value *SCEVCheck =
Exp.expandCodeForPredicate(&PSE.getUnionPredicate(), BB->getTerminator());
if (auto *C = dyn_cast<ConstantInt>(SCEVCheck))
if (C->isZero())
// Create a new block containing the stride check.
auto *NewBB = BB->splitBasicBlock(BB->getTerminator(), "");
// Update dominator tree immediately if the generated block is a
// LoopBypassBlock because SCEV expansions to generate loop bypass
// checks may query it before the current function is finished.
DT->addNewBlock(NewBB, BB);
if (L->getParentLoop())
L->getParentLoop()->addBasicBlockToLoop(NewBB, *LI);
BranchInst::Create(Bypass, NewBB, SCEVCheck));
AddedSafetyChecks = true;
void InnerLoopVectorizer::emitMemRuntimeChecks(Loop *L, BasicBlock *Bypass) {
BasicBlock *BB = L->getLoopPreheader();
// Generate the code that checks in runtime if arrays overlap. We put the
// checks into a separate block to make the more common case of few elements
// faster.
Instruction *FirstCheckInst;
Instruction *MemRuntimeCheck;
std::tie(FirstCheckInst, MemRuntimeCheck) =
if (!MemRuntimeCheck)
// Create a new block containing the memory check.
auto *NewBB = BB->splitBasicBlock(BB->getTerminator(), "");
// Update dominator tree immediately if the generated block is a
// LoopBypassBlock because SCEV expansions to generate loop bypass
// checks may query it before the current function is finished.
DT->addNewBlock(NewBB, BB);
if (L->getParentLoop())
L->getParentLoop()->addBasicBlockToLoop(NewBB, *LI);
BranchInst::Create(Bypass, NewBB, MemRuntimeCheck));
AddedSafetyChecks = true;
// We currently don't use LoopVersioning for the actual loop cloning but we
// still use it to add the noalias metadata.
LVer = llvm::make_unique<LoopVersioning>(*Legal->getLAI(), OrigLoop, LI, DT,
void InnerLoopVectorizer::createEmptyLoop() {
In this function we generate a new loop. The new loop will contain
the vectorized instructions while the old loop will continue to run the
scalar remainder.
[ ] <-- loop iteration number check.
/ |
/ v
| [ ] <-- vector loop bypass (may consist of multiple blocks).
| / |
| / v
|| [ ] <-- vector pre header.
|/ |
| v
| [ ] \
| [ ]_| <-- vector loop.
| |
| v
| -[ ] <--- middle-block.
| / |
| / v
-|- >[ ] <--- new preheader.
| |
| v
| [ ] \
| [ ]_| <-- old scalar loop to handle remainder.
\ |
\ v
>[ ] <-- exit block.
BasicBlock *OldBasicBlock = OrigLoop->getHeader();
BasicBlock *VectorPH = OrigLoop->getLoopPreheader();
BasicBlock *ExitBlock = OrigLoop->getExitBlock();
assert(VectorPH && "Invalid loop structure");
assert(ExitBlock && "Must have an exit block");
// Some loops have a single integer induction variable, while other loops
// don't. One example is c++ iterators that often have multiple pointer
// induction variables. In the code below we also support a case where we
// don't have a single induction variable.
// We try to obtain an induction variable from the original loop as hard
// as possible. However if we don't find one that:
// - is an integer
// - counts from zero, stepping by one
// - is the size of the widest induction variable type
// then we create a new one.
OldInduction = Legal->getInduction();
Type *IdxTy = Legal->getWidestInductionType();
// Split the single block loop into the two loop structure described above.
BasicBlock *VecBody =
VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.body");
BasicBlock *MiddleBlock =
VecBody->splitBasicBlock(VecBody->getTerminator(), "middle.block");
BasicBlock *ScalarPH =
MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "");
// Create and register the new vector loop.
Loop *Lp = new Loop();
Loop *ParentLoop = OrigLoop->getParentLoop();
// Insert the new loop into the loop nest and register the new basic blocks
// before calling any utilities such as SCEV that require valid LoopInfo.
if (ParentLoop) {
ParentLoop->addBasicBlockToLoop(ScalarPH, *LI);
ParentLoop->addBasicBlockToLoop(MiddleBlock, *LI);
} else {
Lp->addBasicBlockToLoop(VecBody, *LI);
// Find the loop boundaries.
Value *Count = getOrCreateTripCount(Lp);
Value *StartIdx = ConstantInt::get(IdxTy, 0);
// We need to test whether the backedge-taken count is uint##_max. Adding one
// to it will cause overflow and an incorrect loop trip count in the vector
// body. In case of overflow we want to directly jump to the scalar remainder
// loop.
emitMinimumIterationCountCheck(Lp, ScalarPH);
// Now, compare the new count to zero. If it is zero skip the vector loop and
// jump to the scalar loop.
emitVectorLoopEnteredCheck(Lp, ScalarPH);
// Generate the code to check any assumptions that we've made for SCEV
// expressions.
emitSCEVChecks(Lp, ScalarPH);
// Generate the code that checks in runtime if arrays overlap. We put the
// checks into a separate block to make the more common case of few elements
// faster.
emitMemRuntimeChecks(Lp, ScalarPH);
// Generate the induction variable.
// The loop step is equal to the vectorization factor (num of SIMD elements)
// times the unroll factor (num of SIMD instructions).
Value *CountRoundDown = getOrCreateVectorTripCount(Lp);
Constant *Step = ConstantInt::get(IdxTy, VF * UF);
Induction =
createInductionVariable(Lp, StartIdx, CountRoundDown, Step,
// We are going to resume the execution of the scalar loop.
// Go over all of the induction variables that we found and fix the
// PHIs that are left in the scalar version of the loop.
// The starting values of PHI nodes depend on the counter of the last
// iteration in the vectorized loop.
// If we come from a bypass edge then we need to start from the original
// start value.
// This variable saves the new starting index for the scalar loop. It is used
// to test if there are any tail iterations left once the vector loop has
// completed.
LoopVectorizationLegality::InductionList::iterator I, E;
LoopVectorizationLegality::InductionList *List = Legal->getInductionVars();
for (I = List->begin(), E = List->end(); I != E; ++I) {
PHINode *OrigPhi = I->first;
InductionDescriptor II = I->second;
// Create phi nodes to merge from the backedge-taken check block.
PHINode *BCResumeVal = PHINode::Create(
OrigPhi->getType(), 3, "bc.resume.val", ScalarPH->getTerminator());
Value *EndValue;
if (OrigPhi == OldInduction) {
// We know what the end value is.
EndValue = CountRoundDown;
} else {
IRBuilder<> B(LoopBypassBlocks.back()->getTerminator());
Value *CRD = B.CreateSExtOrTrunc(CountRoundDown,
II.getStep()->getType(), "cast.crd");
const DataLayout &DL = OrigLoop->getHeader()->getModule()->getDataLayout();
EndValue = II.transform(B, CRD, PSE.getSE(), DL);
// The new PHI merges the original incoming value, in case of a bypass,
// or the value at the end of the vectorized loop.
BCResumeVal->addIncoming(EndValue, MiddleBlock);
// Fix up external users of the induction variable.
fixupIVUsers(OrigPhi, II, CountRoundDown, EndValue, MiddleBlock);
// Fix the scalar body counter (PHI node).
unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH);
// The old induction's phi node in the scalar body needs the truncated
// value.
for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I)
BCResumeVal->addIncoming(II.getStartValue(), LoopBypassBlocks[I]);
OrigPhi->setIncomingValue(BlockIdx, BCResumeVal);
// Add a check in the middle block to see if we have completed
// all of the iterations in the first vector loop.
// If (N - N%VF) == N, then we *don't* need to run the remainder.
Value *CmpN =
CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, Count,
CountRoundDown, "cmp.n", MiddleBlock->getTerminator());
BranchInst::Create(ExitBlock, ScalarPH, CmpN));
// Get ready to start creating new instructions into the vectorized body.
// Save the state.
LoopVectorPreHeader = Lp->getLoopPreheader();
LoopScalarPreHeader = ScalarPH;
LoopMiddleBlock = MiddleBlock;
LoopExitBlock = ExitBlock;
LoopVectorBody = VecBody;
LoopScalarBody = OldBasicBlock;
// Keep all loop hints from the original loop on the vector loop (we'll
// replace the vectorizer-specific hints below).
if (MDNode *LID = OrigLoop->getLoopID())
LoopVectorizeHints Hints(Lp, true);
// Fix up external users of the induction variable. At this point, we are
// in LCSSA form, with all external PHIs that use the IV having one input value,
// coming from the remainder loop. We need those PHIs to also have a correct
// value for the IV when arriving directly from the middle block.
void InnerLoopVectorizer::fixupIVUsers(PHINode *OrigPhi,
const InductionDescriptor &II,
Value *CountRoundDown, Value *EndValue,
BasicBlock *MiddleBlock) {
// There are two kinds of external IV usages - those that use the value
// computed in the last iteration (the PHI) and those that use the penultimate
// value (the value that feeds into the phi from the loop latch).
// We allow both, but they, obviously, have different values.
// We only expect at most one of each kind of user. This is because LCSSA will
// canonicalize the users to a single PHI node per exit block, and we
// currently only vectorize loops with a single exit.
assert(OrigLoop->getExitBlock() && "Expected a single exit block");
// An external user of the last iteration's value should see the value that
// the remainder loop uses to initialize its own IV.
Value *PostInc = OrigPhi->getIncomingValueForBlock(OrigLoop->getLoopLatch());
for (User *U : PostInc->users()) {
Instruction *UI = cast<Instruction>(U);
if (!OrigLoop->contains(UI)) {
assert(isa<PHINode>(UI) && "Expected LCSSA form");
// One corner case we have to handle is two IVs "chasing" each-other,
// that is %IV2 = phi [...], [ %IV1, %latch ]
// In this case, if IV1 has an external use, we need to avoid adding both
// "last value of IV1" and "penultimate value of IV2". Since we don't know
// which IV will be handled first, check we haven't handled this user yet.
PHINode *User = cast<PHINode>(UI);
if (User->getBasicBlockIndex(MiddleBlock) == -1)
User->addIncoming(EndValue, MiddleBlock);
// An external user of the penultimate value need to see EndValue - Step.
// The simplest way to get this is to recompute it from the constituent SCEVs,
// that is Start + (Step * (CRD - 1)).
for (User *U : OrigPhi->users()) {
Instruction *UI = cast<Instruction>(U);
if (!OrigLoop->contains(UI)) {
const DataLayout &DL =
assert(isa<PHINode>(UI) && "Expected LCSSA form");
PHINode *User = cast<PHINode>(UI);
// As above, check we haven't already handled this user.
if (User->getBasicBlockIndex(MiddleBlock) != -1)
IRBuilder<> B(MiddleBlock->getTerminator());
Value *CountMinusOne = B.CreateSub(
CountRoundDown, ConstantInt::get(CountRoundDown->getType(), 1));
Value *CMO = B.CreateSExtOrTrunc(CountMinusOne, II.getStep()->getType(),
Value *Escape = II.transform(B, CMO, PSE.getSE(), DL);
User->addIncoming(Escape, MiddleBlock);
namespace {
struct CSEDenseMapInfo {
static bool canHandle(Instruction *I) {
return isa<InsertElementInst>(I) || isa<ExtractElementInst>(I) ||
isa<ShuffleVectorInst>(I) || isa<GetElementPtrInst>(I);
static inline Instruction *getEmptyKey() {
return DenseMapInfo<Instruction *>::getEmptyKey();
static inline Instruction *getTombstoneKey() {
return DenseMapInfo<Instruction *>::getTombstoneKey();
static unsigned getHashValue(Instruction *I) {
assert(canHandle(I) && "Unknown instruction!");
return hash_combine(I->getOpcode(), hash_combine_range(I->value_op_begin(),
static bool isEqual(Instruction *LHS, Instruction *RHS) {
if (LHS == getEmptyKey() || RHS == getEmptyKey() ||
LHS == getTombstoneKey() || RHS == getTombstoneKey())
return LHS == RHS;
return LHS->isIdenticalTo(RHS);
///\brief Perform cse of induction variable instructions.
static void cse(BasicBlock *BB) {
// Perform simple cse.
SmallDenseMap<Instruction *, Instruction *, 4, CSEDenseMapInfo> CSEMap;
for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E;) {
Instruction *In = &*I++;
if (!CSEDenseMapInfo::canHandle(In))
// Check if we can replace this instruction with any of the
// visited instructions.
if (Instruction *V = CSEMap.lookup(In)) {
CSEMap[In] = In;
/// \brief Adds a 'fast' flag to floating point operations.
static Value *addFastMathFlag(Value *V) {
if (isa<FPMathOperator>(V)) {
FastMathFlags Flags;
return V;
/// Estimate the overhead of scalarizing a value. Insert and Extract are set if
/// the result needs to be inserted and/or extracted from vectors.
static unsigned getScalarizationOverhead(Type *Ty, bool Insert, bool Extract,
const TargetTransformInfo &TTI) {
if (Ty->isVoidTy())
return 0;
assert(Ty->isVectorTy() && "Can only scalarize vectors");
unsigned Cost = 0;
for (int i = 0, e = Ty->getVectorNumElements(); i < e; ++i) {
if (Insert)
Cost += TTI.getVectorInstrCost(Instruction::InsertElement, Ty, i);
if (Extract)
Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, Ty, i);
return Cost;
// Estimate cost of a call instruction CI if it were vectorized with factor VF.
// Return the cost of the instruction, including scalarization overhead if it's
// needed. The flag NeedToScalarize shows if the call needs to be scalarized -
// i.e. either vector version isn't available, or is too expensive.
static unsigned getVectorCallCost(CallInst *CI, unsigned VF,
const TargetTransformInfo &TTI,
const TargetLibraryInfo *TLI,
bool &NeedToScalarize) {
Function *F = CI->getCalledFunction();
StringRef FnName = CI->getCalledFunction()->getName();
Type *ScalarRetTy = CI->getType();
SmallVector<Type *, 4> Tys, ScalarTys;
for (auto &ArgOp : CI->arg_operands())
// Estimate cost of scalarized vector call. The source operands are assumed
// to be vectors, so we need to extract individual elements from there,
// execute VF scalar calls, and then gather the result into the vector return
// value.
unsigned ScalarCallCost = TTI.getCallInstrCost(F, ScalarRetTy, ScalarTys);
if (VF == 1)
return ScalarCallCost;
// Compute corresponding vector type for return value and arguments.
Type *RetTy = ToVectorTy(ScalarRetTy, VF);
for (unsigned i = 0, ie = ScalarTys.size(); i != ie; ++i)
Tys.push_back(ToVectorTy(ScalarTys[i], VF));
// Compute costs of unpacking argument values for the scalar calls and
// packing the return values to a vector.
unsigned ScalarizationCost =
getScalarizationOverhead(RetTy, true, false, TTI);
for (unsigned i = 0, ie = Tys.size(); i != ie; ++i)
ScalarizationCost += getScalarizationOverhead(Tys[i], false, true, TTI);
unsigned Cost = ScalarCallCost * VF + ScalarizationCost;
// If we can't emit a vector call for this function, then the currently found
// cost is the cost we need to return.
NeedToScalarize = true;
if (!TLI || !TLI->isFunctionVectorizable(FnName, VF) || CI->isNoBuiltin())
return Cost;
// If the corresponding vector cost is cheaper, return its cost.
unsigned VectorCallCost = TTI.getCallInstrCost(nullptr, RetTy, Tys);
if (VectorCallCost < Cost) {
NeedToScalarize = false;
return VectorCallCost;
return Cost;
// Estimate cost of an intrinsic call instruction CI if it were vectorized with
// factor VF. Return the cost of the instruction, including scalarization
// overhead if it's needed.
static unsigned getVectorIntrinsicCost(CallInst *CI, unsigned VF,
const TargetTransformInfo &TTI,
const TargetLibraryInfo *TLI) {
Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
assert(ID && "Expected intrinsic call!");
Type *RetTy = ToVectorTy(CI->getType(), VF);
SmallVector<Type *, 4> Tys;
for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i)
Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF));
FastMathFlags FMF;
if (auto *FPMO = dyn_cast<FPMathOperator>(CI))
FMF = FPMO->getFastMathFlags();
return TTI.getIntrinsicInstrCost(ID, RetTy, Tys, FMF);
static Type *smallestIntegerVectorType(Type *T1, Type *T2) {
IntegerType *I1 = cast<IntegerType>(T1->getVectorElementType());
IntegerType *I2 = cast<IntegerType>(T2->getVectorElementType());
return I1->getBitWidth() < I2->getBitWidth() ? T1 : T2;
static Type *largestIntegerVectorType(Type *T1, Type *T2) {
IntegerType *I1 = cast<IntegerType>(T1->getVectorElementType());
IntegerType *I2 = cast<IntegerType>(T2->getVectorElementType());
return I1->getBitWidth() > I2->getBitWidth() ? T1 : T2;
void InnerLoopVectorizer::truncateToMinimalBitwidths() {
// For every instruction `I` in MinBWs, truncate the operands, create a
// truncated version of `I` and reextend its result. InstCombine runs
// later and will remove any ext/trunc pairs.
SmallPtrSet<Value *, 4> Erased;
- for (auto &KV : MinBWs) {
+ for (const auto &KV : *MinBWs) {
VectorParts &Parts = WidenMap.get(KV.first);
for (Value *&I : Parts) {
if (Erased.count(I) || I->use_empty())
Type *OriginalTy = I->getType();
Type *ScalarTruncatedTy =
IntegerType::get(OriginalTy->getContext(), KV.second);
Type *TruncatedTy = VectorType::get(ScalarTruncatedTy,
if (TruncatedTy == OriginalTy)
if (!isa<Instruction>(I))
IRBuilder<> B(cast<Instruction>(I));
auto ShrinkOperand = [&](Value *V) -> Value * {
if (auto *ZI = dyn_cast<ZExtInst>(V))
if (ZI->getSrcTy() == TruncatedTy)
return ZI->getOperand(0);
return B.CreateZExtOrTrunc(V, TruncatedTy);
// The actual instruction modification depends on the instruction type,
// unfortunately.
Value *NewI = nullptr;
if (BinaryOperator *BO = dyn_cast<BinaryOperator>(I)) {
NewI = B.CreateBinOp(BO->getOpcode(), ShrinkOperand(BO->getOperand(0)),
} else if (ICmpInst *CI = dyn_cast<ICmpInst>(I)) {
NewI =
B.CreateICmp(CI->getPredicate(), ShrinkOperand(CI->getOperand(0)),
} else if (SelectInst *SI = dyn_cast<SelectInst>(I)) {
NewI = B.CreateSelect(SI->getCondition(),
} else if (CastInst *CI = dyn_cast<CastInst>(I)) {
switch (CI->getOpcode()) {
llvm_unreachable("Unhandled cast!");
case Instruction::Trunc:
NewI = ShrinkOperand(CI->getOperand(0));
case Instruction::SExt:
NewI = B.CreateSExtOrTrunc(
smallestIntegerVectorType(OriginalTy, TruncatedTy));
case Instruction::ZExt:
NewI = B.CreateZExtOrTrunc(
smallestIntegerVectorType(OriginalTy, TruncatedTy));
} else if (ShuffleVectorInst *SI = dyn_cast<ShuffleVectorInst>(I)) {
auto Elements0 = SI->getOperand(0)->getType()->getVectorNumElements();
auto *O0 = B.CreateZExtOrTrunc(
SI->getOperand(0), VectorType::get(ScalarTruncatedTy, Elements0));
auto Elements1 = SI->getOperand(1)->getType()->getVectorNumElements();
auto *O1 = B.CreateZExtOrTrunc(
SI->getOperand(1), VectorType::get(ScalarTruncatedTy, Elements1));
NewI = B.CreateShuffleVector(O0, O1, SI->getMask());
} else if (isa<LoadInst>(I)) {
// Don't do anything with the operands, just extend the result.
} else if (auto *IE = dyn_cast<InsertElementInst>(I)) {
auto Elements = IE->getOperand(0)->getType()->getVectorNumElements();
auto *O0 = B.CreateZExtOrTrunc(
IE->getOperand(0), VectorType::get(ScalarTruncatedTy, Elements));
auto *O1 = B.CreateZExtOrTrunc(IE->getOperand(1), ScalarTruncatedTy);
NewI = B.CreateInsertElement(O0, O1, IE->getOperand(2));
} else if (auto *EE = dyn_cast<ExtractElementInst>(I)) {
auto Elements = EE->getOperand(0)->getType()->getVectorNumElements();
auto *O0 = B.CreateZExtOrTrunc(
EE->getOperand(0), VectorType::get(ScalarTruncatedTy, Elements));
NewI = B.CreateExtractElement(O0, EE->getOperand(2));
} else {
llvm_unreachable("Unhandled instruction type!");
// Lastly, extend the result.
Value *Res = B.CreateZExtOrTrunc(NewI, OriginalTy);
I = Res;
// We'll have created a bunch of ZExts that are now parentless. Clean up.
- for (auto &KV : MinBWs) {
+ for (const auto &KV : *MinBWs) {
VectorParts &Parts = WidenMap.get(KV.first);
for (Value *&I : Parts) {
ZExtInst *Inst = dyn_cast<ZExtInst>(I);
if (Inst && Inst->use_empty()) {
Value *NewI = Inst->getOperand(0);
I = NewI;
void InnerLoopVectorizer::vectorizeLoop() {
// Notice: any optimization or new instruction that go
// into the code below should be also be implemented in
// the cost-model.
Constant *Zero = Builder.getInt32(0);
// In order to support recurrences we need to be able to vectorize Phi nodes.
// Phi nodes have cycles, so we need to vectorize them in two stages. First,
// we create a new vector PHI node with no incoming edges. We use this value
// when we vectorize all of the instructions that use the PHI. Next, after
// all of the instructions in the block are complete we add the new incoming
// edges to the PHI. At this point all of the instructions in the basic block
// are vectorized, so we can use them to construct the PHI.
PhiVector PHIsToFix;
// Scan the loop in a topological order to ensure that defs are vectorized
// before users.
LoopBlocksDFS DFS(OrigLoop);
// Vectorize all of the blocks in the original loop.
for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(), be = DFS.endRPO();
bb != be; ++bb)
vectorizeBlockInLoop(*bb, &PHIsToFix);
// Insert truncates and extends for any truncated instructions as hints to
// InstCombine.
if (VF > 1)
// At this point every instruction in the original loop is widened to a
// vector form. Now we need to fix the recurrences in PHIsToFix. These PHI
// nodes are currently empty because we did not want to introduce cycles.
// This is the second stage of vectorizing recurrences.
for (PHINode *Phi : PHIsToFix) {
assert(Phi && "Unable to recover vectorized PHI");
// Handle first-order recurrences that need to be fixed.
if (Legal->isFirstOrderRecurrence(Phi)) {
// If the phi node is not a first-order recurrence, it must be a reduction.
// Get it's reduction variable descriptor.
assert(Legal->isReductionVariable(Phi) &&
"Unable to find the reduction variable");
RecurrenceDescriptor RdxDesc = (*Legal->getReductionVars())[Phi];
RecurrenceDescriptor::RecurrenceKind RK = RdxDesc.getRecurrenceKind();
TrackingVH<Value> ReductionStartValue = RdxDesc.getRecurrenceStartValue();
Instruction *LoopExitInst = RdxDesc.getLoopExitInstr();
RecurrenceDescriptor::MinMaxRecurrenceKind MinMaxKind =
setDebugLocFromInst(Builder, ReductionStartValue);
// We need to generate a reduction vector from the incoming scalar.
// To do so, we need to generate the 'identity' vector and override
// one of the elements with the incoming scalar reduction. We need
// to do it in the vector-loop preheader.
// This is the vector-clone of the value that leaves the loop.
VectorParts &VectorExit = getVectorValue(LoopExitInst);
Type *VecTy = VectorExit[0]->getType();
// Find the reduction identity variable. Zero for addition, or, xor,
// one for multiplication, -1 for And.
Value *Identity;
Value *VectorStart;
if (RK == RecurrenceDescriptor::RK_IntegerMinMax ||
RK == RecurrenceDescriptor::RK_FloatMinMax) {
// MinMax reduction have the start value as their identify.
if (VF == 1) {
VectorStart = Identity = ReductionStartValue;
} else {
VectorStart = Identity =
Builder.CreateVectorSplat(VF, ReductionStartValue, "minmax.ident");
} else {
// Handle other reduction kinds:
Constant *Iden = RecurrenceDescriptor::getRecurrenceIdentity(
RK, VecTy->getScalarType());
if (VF == 1) {
Identity = Iden;
// This vector is the Identity vector where the first element is the
// incoming scalar reduction.
VectorStart = ReductionStartValue;
} else {
Identity = ConstantVector::getSplat(VF, Iden);
// This vector is the Identity vector where the first element is the
// incoming scalar reduction.
VectorStart =
Builder.CreateInsertElement(Identity, ReductionStartValue, Zero);
// Fix the vector-loop phi.
// Reductions do not have to start at zero. They can start with
// any loop invariant values.
VectorParts &VecRdxPhi = WidenMap.get(Phi);
BasicBlock *Latch = OrigLoop->getLoopLatch();
Value *LoopVal = Phi->getIncomingValueForBlock(Latch);
VectorParts &Val = getVectorValue(LoopVal);
for (unsigned part = 0; part < UF; ++part) {
// Make sure to add the reduction stat value only to the
// first unroll part.
Value *StartVal = (part == 0) ? VectorStart : Identity;
->addIncoming(StartVal, LoopVectorPreHeader);
->addIncoming(Val[part], LoopVectorBody);
// Before each round, move the insertion point right between
// the PHIs and the values we are going to write.
// This allows us to write both PHINodes and the extractelement
// instructions.
VectorParts RdxParts = getVectorValue(LoopExitInst);
setDebugLocFromInst(Builder, LoopExitInst);
// If the vector reduction can be performed in a smaller type, we truncate
// then extend the loop exit value to enable InstCombine to evaluate the
// entire expression in the smaller type.
if (VF > 1 && Phi->getType() != RdxDesc.getRecurrenceType()) {
Type *RdxVecTy = VectorType::get(RdxDesc.getRecurrenceType(), VF);
for (unsigned part = 0; part < UF; ++part) {
Value *Trunc = Builder.CreateTrunc(RdxParts[part], RdxVecTy);
Value *Extnd = RdxDesc.isSigned() ? Builder.CreateSExt(Trunc, VecTy)
: Builder.CreateZExt(Trunc, VecTy);
for (Value::user_iterator UI = RdxParts[part]->user_begin();
UI != RdxParts[part]->user_end();)
if (*UI != Trunc) {
(*UI++)->replaceUsesOfWith(RdxParts[part], Extnd);
RdxParts[part] = Extnd;
} else {
for (unsigned part = 0; part < UF; ++part)
RdxParts[part] = Builder.CreateTrunc(RdxParts[part], RdxVecTy);
// Reduce all of the unrolled parts into a single vector.
Value *ReducedPartRdx = RdxParts[0];
unsigned Op = RecurrenceDescriptor::getRecurrenceBinOp(RK);
setDebugLocFromInst(Builder, ReducedPartRdx);
for (unsigned part = 1; part < UF; ++part) {
if (Op != Instruction::ICmp && Op != Instruction::FCmp)
// Floating point operations had to be 'fast' to enable the reduction.
ReducedPartRdx = addFastMathFlag(
Builder.CreateBinOp((Instruction::BinaryOps)Op, RdxParts[part],
ReducedPartRdx, "bin.rdx"));
ReducedPartRdx = RecurrenceDescriptor::createMinMaxOp(
Builder, MinMaxKind, ReducedPartRdx, RdxParts[part]);
if (VF > 1) {
// VF is a power of 2 so we can emit the reduction using log2(VF) shuffles
// and vector ops, reducing the set of values being computed by half each
// round.
assert(isPowerOf2_32(VF) &&
"Reduction emission only supported for pow2 vectors!");
Value *TmpVec = ReducedPartRdx;
SmallVector<Constant *, 32> ShuffleMask(VF, nullptr);
for (unsigned i = VF; i != 1; i >>= 1) {
// Move the upper half of the vector to the lower half.
for (unsigned j = 0; j != i / 2; ++j)
ShuffleMask[j] = Builder.getInt32(i / 2 + j);
// Fill the rest of the mask with undef.
std::fill(&ShuffleMask[i / 2], ShuffleMask.end(),
Value *Shuf = Builder.CreateShuffleVector(
TmpVec, UndefValue::get(TmpVec->getType()),
ConstantVector::get(ShuffleMask), "rdx.shuf");
if (Op != Instruction::ICmp && Op != Instruction::FCmp)
// Floating point operations had to be 'fast' to enable the reduction.
TmpVec = addFastMathFlag(Builder.CreateBinOp(
(Instruction::BinaryOps)Op, TmpVec, Shuf, "bin.rdx"));
TmpVec = RecurrenceDescriptor::createMinMaxOp(Builder, MinMaxKind,
TmpVec, Shuf);
// The result is in the first element of the vector.
ReducedPartRdx =
Builder.CreateExtractElement(TmpVec, Builder.getInt32(0));
// If the reduction can be performed in a smaller type, we need to extend
// the reduction to the wider type before we branch to the original loop.
if (Phi->getType() != RdxDesc.getRecurrenceType())
ReducedPartRdx =
? Builder.CreateSExt(ReducedPartRdx, Phi->getType())
: Builder.CreateZExt(ReducedPartRdx, Phi->getType());
// Create a phi node that merges control-flow from the backedge-taken check
// block and the middle block.
PHINode *BCBlockPhi = PHINode::Create(Phi->getType(), 2, "bc.merge.rdx",
for (unsigned I = 0, E = LoopBypassBlocks.size(); I != E; ++I)
BCBlockPhi->addIncoming(ReductionStartValue, LoopBypassBlocks[I]);
BCBlockPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock);
// Now, we need to fix the users of the reduction variable
// inside and outside of the scalar remainder loop.
// We know that the loop is in LCSSA form. We need to update the
// PHI nodes in the exit blocks.
for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
LEE = LoopExitBlock->end();
LEI != LEE; ++LEI) {
PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
if (!LCSSAPhi)
// All PHINodes need to have a single entry edge, or two if
// we already fixed them.
assert(LCSSAPhi->getNumIncomingValues() < 3 && "Invalid LCSSA PHI");
// We found our reduction value exit-PHI. Update it with the
// incoming bypass edge.
if (LCSSAPhi->getIncomingValue(0) == LoopExitInst) {
// Add an edge coming from the bypass.
LCSSAPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock);
} // end of the LCSSA phi scan.
// Fix the scalar loop reduction variable with the incoming reduction sum
// from the vector body and from the backedge value.
int IncomingEdgeBlockIdx =
assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index");
// Pick the other block.
int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1);
Phi->setIncomingValue(SelfEdgeBlockIdx, BCBlockPhi);
Phi->setIncomingValue(IncomingEdgeBlockIdx, LoopExitInst);
} // end of for each Phi in PHIsToFix.
// Make sure DomTree is updated.
// Predicate any stores.
for (auto KV : PredicatedStores) {
BasicBlock::iterator I(KV.first);
auto *BB = SplitBlock(I->getParent(), &*std::next(I), DT, LI);
auto *T = SplitBlockAndInsertIfThen(KV.second, &*I, /*Unreachable=*/false,
/*BranchWeights=*/nullptr, DT, LI);
// Remove redundant induction instructions.
void InnerLoopVectorizer::fixFirstOrderRecurrence(PHINode *Phi) {
// This is the second phase of vectorizing first-order recurrences. An
// overview of the transformation is described below. Suppose we have the
// following loop.
// for (int i = 0; i < n; ++i)
// b[i] = a[i] - a[i - 1];
// There is a first-order recurrence on "a". For this loop, the shorthand
// scalar IR looks like:
// s_init = a[-1]
// br scalar.body
// scalar.body:
// i = phi [0,], [i+1, scalar.body]
// s1 = phi [s_init,], [s2, scalar.body]
// s2 = a[i]
// b[i] = s2 - s1
// br cond, scalar.body, ...
// In this example, s1 is a recurrence because it's value depends on the
// previous iteration. In the first phase of vectorization, we created a
// temporary value for s1. We now complete the vectorization and produce the
// shorthand vector IR shown below (for VF = 4, UF = 1).
// v_init = vector(..., ..., ..., a[-1])
// br vector.body
// vector.body
// i = phi [0,], [i+4, vector.body]
// v1 = phi [v_init,], [v2, vector.body]
// v2 = a[i, i+1, i+2, i+3];
// v3 = vector(v1(3), v2(0, 1, 2))
// b[i, i+1, i+2, i+3] = v2 - v3
// br cond, vector.body, middle.block
// middle.block:
// x = v2(3)
// br
// s_init = phi [x, middle.block], [a[-1], otherwise]
// br scalar.body
// After execution completes the vector loop, we extract the next value of
// the recurrence (x) to use as the initial value in the scalar loop.
// Get the original loop preheader and single loop latch.
auto *Preheader = OrigLoop->getLoopPreheader();
auto *Latch = OrigLoop->getLoopLatch();
// Get the initial and previous values of the scalar recurrence.
auto *ScalarInit = Phi->getIncomingValueForBlock(Preheader);
auto *Previous = Phi->getIncomingValueForBlock(Latch);
// Create a vector from the initial value.
auto *VectorInit = ScalarInit;
if (VF > 1) {
VectorInit = Builder.CreateInsertElement(
UndefValue::get(VectorType::get(VectorInit->getType(), VF)), VectorInit,
Builder.getInt32(VF - 1), "vector.recur.init");
// We constructed a temporary phi node in the first phase of vectorization.
// This phi node will eventually be deleted.
auto &PhiParts = getVectorValue(Phi);
// Create a phi node for the new recurrence. The current value will either be
// the initial value inserted into a vector or loop-varying vector value.
auto *VecPhi = Builder.CreatePHI(VectorInit->getType(), 2, "vector.recur");
VecPhi->addIncoming(VectorInit, LoopVectorPreHeader);
// Get the vectorized previous value. We ensured the previous values was an
// instruction when detecting the recurrence.
auto &PreviousParts = getVectorValue(Previous);
// Set the insertion point to be after this instruction. We ensured the
// previous value dominated all uses of the phi when detecting the
// recurrence.
&*++BasicBlock::iterator(cast<Instruction>(PreviousParts[UF - 1])));
// We will construct a vector for the recurrence by combining the values for
// the current and previous iterations. This is the required shuffle mask.
SmallVector<Constant *, 8> ShuffleMask(VF);
ShuffleMask[0] = Builder.getInt32(VF - 1);
for (unsigned I = 1; I < VF; ++I)
ShuffleMask[I] = Builder.getInt32(I + VF - 1);
// The vector from which to take the initial value for the current iteration
// (actual or unrolled). Initially, this is the vector phi node.
Value *Incoming = VecPhi;
// Shuffle the current and previous vector and update the vector parts.
for (unsigned Part = 0; Part < UF; ++Part) {
auto *Shuffle =
VF > 1
? Builder.CreateShuffleVector(Incoming, PreviousParts[Part],
: Incoming;
PhiParts[Part] = Shuffle;
Incoming = PreviousParts[Part];
// Fix the latch value of the new recurrence in the vector loop.
// Extract the last vector element in the middle block. This will be the
// initial value for the recurrence when jumping to the scalar loop.
auto *Extract = Incoming;
if (VF > 1) {
Extract = Builder.CreateExtractElement(Extract, Builder.getInt32(VF - 1),
// Fix the initial value of the original recurrence in the scalar loop.
auto *Start = Builder.CreatePHI(Phi->getType(), 2, "scalar.recur.init");
for (auto *BB : predecessors(LoopScalarPreHeader)) {
auto *Incoming = BB == LoopMiddleBlock ? Extract : ScalarInit;
Start->addIncoming(Incoming, BB);
Phi->setIncomingValue(Phi->getBasicBlockIndex(LoopScalarPreHeader), Start);
// Finally, fix users of the recurrence outside the loop. The users will need
// either the last value of the scalar recurrence or the last value of the
// vector recurrence we extracted in the middle block. Since the loop is in
// LCSSA form, we just need to find the phi node for the original scalar
// recurrence in the exit block, and then add an edge for the middle block.
for (auto &I : *LoopExitBlock) {
auto *LCSSAPhi = dyn_cast<PHINode>(&I);
if (!LCSSAPhi)
if (LCSSAPhi->getIncomingValue(0) == Phi) {
LCSSAPhi->addIncoming(Extract, LoopMiddleBlock);
void InnerLoopVectorizer::fixLCSSAPHIs() {
for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
LEE = LoopExitBlock->end();
LEI != LEE; ++LEI) {
PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
if (!LCSSAPhi)
if (LCSSAPhi->getNumIncomingValues() == 1)
InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) {
assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) &&
"Invalid edge");
// Look for cached value.
std::pair<BasicBlock *, BasicBlock *> Edge(Src, Dst);
EdgeMaskCache::iterator ECEntryIt = MaskCache.find(Edge);
if (ECEntryIt != MaskCache.end())
return ECEntryIt->second;
VectorParts SrcMask = createBlockInMask(Src);
// The terminator has to be a branch inst!
BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator());
assert(BI && "Unexpected terminator found");
if (BI->isConditional()) {
VectorParts EdgeMask = getVectorValue(BI->getCondition());
if (BI->getSuccessor(0) != Dst)
for (unsigned part = 0; part < UF; ++part)
EdgeMask[part] = Builder.CreateNot(EdgeMask[part]);
for (unsigned part = 0; part < UF; ++part)
EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]);
MaskCache[Edge] = EdgeMask;
return EdgeMask;
MaskCache[Edge] = SrcMask;
return SrcMask;
InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) {
assert(OrigLoop->contains(BB) && "Block is not a part of a loop");
// Loop incoming mask is all-one.
if (OrigLoop->getHeader() == BB) {
Value *C = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 1);
return getVectorValue(C);
// This is the block mask. We OR all incoming edges, and with zero.
Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0);
VectorParts BlockMask = getVectorValue(Zero);
// For each pred:
for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) {
VectorParts EM = createEdgeMask(*it, BB);
for (unsigned part = 0; part < UF; ++part)
BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]);
return BlockMask;
void InnerLoopVectorizer::widenPHIInstruction(
Instruction *PN, InnerLoopVectorizer::VectorParts &Entry, unsigned UF,
unsigned VF, PhiVector *PV) {
PHINode *P = cast<PHINode>(PN);
// Handle recurrences.
if (Legal->isReductionVariable(P) || Legal->isFirstOrderRecurrence(P)) {
for (unsigned part = 0; part < UF; ++part) {
// This is phase one of vectorizing PHIs.
Type *VecTy =
(VF == 1) ? PN->getType() : VectorType::get(PN->getType(), VF);
Entry[part] = PHINode::Create(
VecTy, 2, "vec.phi", &*LoopVectorBody->getFirstInsertionPt());
setDebugLocFromInst(Builder, P);
// Check for PHI nodes that are lowered to vector selects.
if (P->getParent() != OrigLoop->getHeader()) {
// We know that all PHIs in non-header blocks are converted into
// selects, so we don't have to worry about the insertion order and we
// can just use the builder.
// At this point we generate the predication tree. There may be
// duplications since this is a simple recursive scan, but future
// optimizations will clean it up.
unsigned NumIncoming = P->getNumIncomingValues();
// Generate a sequence of selects of the form:
// SELECT(Mask3, In3,
// SELECT(Mask2, In2,
// ( ...)))
for (unsigned In = 0; In < NumIncoming; In++) {
VectorParts Cond =
createEdgeMask(P->getIncomingBlock(In), P->getParent());
VectorParts &In0 = getVectorValue(P->getIncomingValue(In));
for (unsigned part = 0; part < UF; ++part) {
// We might have single edge PHIs (blocks) - use an identity
// 'select' for the first PHI operand.
if (In == 0)
Entry[part] = Builder.CreateSelect(Cond[part], In0[part], In0[part]);
// Select between the current value and the previous incoming edge
// based on the incoming mask.
Entry[part] = Builder.CreateSelect(Cond[part], In0[part], Entry[part],
// This PHINode must be an induction variable.
// Make sure that we know about it.
assert(Legal->getInductionVars()->count(P) && "Not an induction variable");
InductionDescriptor II = Legal->getInductionVars()->lookup(P);
const DataLayout &DL = OrigLoop->getHeader()->getModule()->getDataLayout();
// FIXME: The newly created binary instructions should contain nsw/nuw flags,
// which can be found from the original scalar operations.
switch (II.getKind()) {
case InductionDescriptor::IK_NoInduction:
llvm_unreachable("Unknown induction");
case InductionDescriptor::IK_IntInduction: {
assert(P->getType() == II.getStartValue()->getType() && "Types must match");
if (VF == 1 || P->getType() != Induction->getType() ||
!II.getConstIntStepValue()) {
Value *V = Induction;
// Handle other induction variables that are now based on the
// canonical one.
if (P != OldInduction) {
V = Builder.CreateSExtOrTrunc(Induction, P->getType());
V = II.transform(Builder, V, PSE.getSE(), DL);
Value *Broadcasted = getBroadcastInstrs(V);
// After broadcasting the induction variable we need to make the vector
// consecutive by adding 0, 1, 2, etc.
for (unsigned part = 0; part < UF; ++part)
Entry[part] = getStepVector(Broadcasted, VF * part, II.getStep());
} else {
// Instead of re-creating the vector IV by splatting the scalar IV
// in each iteration, we can make a new independent vector IV.
widenInductionVariable(II, Entry);
case InductionDescriptor::IK_PtrInduction:
// Handle the pointer induction variable case.
assert(P->getType()->isPointerTy() && "Unexpected type.");
// This is the normalized GEP that starts counting at zero.
Value *PtrInd = Induction;
PtrInd = Builder.CreateSExtOrTrunc(PtrInd, II.getStep()->getType());
// This is the vector of results. Notice that we don't generate
// vector geps because scalar geps result in better code.
for (unsigned part = 0; part < UF; ++part) {
if (VF == 1) {
int EltIndex = part;
Constant *Idx = ConstantInt::get(PtrInd->getType(), EltIndex);
Value *GlobalIdx = Builder.CreateAdd(PtrInd, Idx);
Value *SclrGep = II.transform(Builder, GlobalIdx, PSE.getSE(), DL);
Entry[part] = SclrGep;
Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF));
for (unsigned int i = 0; i < VF; ++i) {
int EltIndex = i + part * VF;
Constant *Idx = ConstantInt::get(PtrInd->getType(), EltIndex);
Value *GlobalIdx = Builder.CreateAdd(PtrInd, Idx);
Value *SclrGep = II.transform(Builder, GlobalIdx, PSE.getSE(), DL);
VecVal = Builder.CreateInsertElement(VecVal, SclrGep,
Builder.getInt32(i), "insert.gep");
Entry[part] = VecVal;
void InnerLoopVectorizer::vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV) {
// For each instruction in the old loop.
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
VectorParts &Entry = WidenMap.get(&*it);
switch (it->getOpcode()) {
case Instruction::Br:
// Nothing to do for PHIs and BR, since we already took care of the
// loop control flow instructions.
case Instruction::PHI: {
// Vectorize PHINodes.
widenPHIInstruction(&*it, Entry, UF, VF, PV);
} // End of PHI.
case Instruction::Add:
case Instruction::FAdd:
case Instruction::Sub:
case Instruction::FSub:
case Instruction::Mul:
case Instruction::FMul:
case Instruction::UDiv:
case Instruction::SDiv:
case Instruction::FDiv:
case Instruction::URem:
case Instruction::SRem:
case Instruction::FRem:
case Instruction::Shl:
case Instruction::LShr:
case Instruction::AShr:
case Instruction::And:
case Instruction::Or:
case Instruction::Xor: {
// Just widen binops.
BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it);
setDebugLocFromInst(Builder, BinOp);
VectorParts &A = getVectorValue(it->getOperand(0));
VectorParts &B = getVectorValue(it->getOperand(1));
// Use this vector value for all users of the original instruction.
for (unsigned Part = 0; Part < UF; ++Part) {
Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A[Part], B[Part]);
if (BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V))
Entry[Part] = V;
addMetadata(Entry, &*it);
case Instruction::Select: {
// Widen selects.
// If the selector is loop invariant we can create a select
// instruction with a scalar condition. Otherwise, use vector-select.
auto *SE = PSE.getSE();
bool InvariantCond =
SE->isLoopInvariant(PSE.getSCEV(it->getOperand(0)), OrigLoop);
setDebugLocFromInst(Builder, &*it);
// The condition can be loop invariant but still defined inside the
// loop. This means that we can't just use the original 'cond' value.
// We have to take the 'vectorized' value and pick the first lane.
// Instcombine will make this a no-op.
VectorParts &Cond = getVectorValue(it->getOperand(0));
VectorParts &Op0 = getVectorValue(it->getOperand(1));
VectorParts &Op1 = getVectorValue(it->getOperand(2));
Value *ScalarCond =
(VF == 1)
? Cond[0]
: Builder.CreateExtractElement(Cond[0], Builder.getInt32(0));
for (unsigned Part = 0; Part < UF; ++Part) {
Entry[Part] = Builder.CreateSelect(
InvariantCond ? ScalarCond : Cond[Part], Op0[Part], Op1[Part]);
addMetadata(Entry, &*it);
case Instruction::ICmp:
case Instruction::FCmp: {
// Widen compares. Generate vector compares.
bool FCmp = (it->getOpcode() == Instruction::FCmp);
CmpInst *Cmp = dyn_cast<CmpInst>(it);
setDebugLocFromInst(Builder, &*it);
VectorParts &A = getVectorValue(it->getOperand(0));
VectorParts &B = getVectorValue(it->getOperand(1));
for (unsigned Part = 0; Part < UF; ++Part) {
Value *C = nullptr;
if (FCmp) {
C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]);
} else {
C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]);
Entry[Part] = C;
addMetadata(Entry, &*it);
case Instruction::Store:
case Instruction::Load:
case Instruction::ZExt:
case Instruction::SExt:
case Instruction::FPToUI:
case Instruction::FPToSI:
case Instruction::FPExt:
case Instruction::PtrToInt:
case Instruction::IntToPtr:
case Instruction::SIToFP:
case Instruction::UIToFP:
case Instruction::Trunc:
case Instruction::FPTrunc:
case Instruction::BitCast: {
CastInst *CI = dyn_cast<CastInst>(it);
setDebugLocFromInst(Builder, &*it);
/// Optimize the special case where the source is a constant integer
/// induction variable. Notice that we can only optimize the 'trunc' case
/// because: a. FP conversions lose precision, b. sext/zext may wrap,
/// c. other casts depend on pointer size.
if (CI->getOperand(0) == OldInduction &&
it->getOpcode() == Instruction::Trunc) {
InductionDescriptor II =
if (auto StepValue = II.getConstIntStepValue()) {
IntegerType *TruncType = cast<IntegerType>(CI->getType());
if (VF == 1) {
StepValue =
ConstantInt::getSigned(TruncType, StepValue->getSExtValue());
Value *ScalarCast =
Builder.CreateCast(CI->getOpcode(), Induction, CI->getType());
Value *Broadcasted = getBroadcastInstrs(ScalarCast);
for (unsigned Part = 0; Part < UF; ++Part)
Entry[Part] = getStepVector(Broadcasted, VF * Part, StepValue);
} else {
// Truncating a vector induction variable on each iteration
// may be expensive. Instead, truncate the initial value, and create
// a new, truncated, vector IV based on that.
widenInductionVariable(II, Entry, TruncType);
addMetadata(Entry, &*it);
/// Vectorize casts.
Type *DestTy =
(VF == 1) ? CI->getType() : VectorType::get(CI->getType(), VF);
VectorParts &A = getVectorValue(it->getOperand(0));
for (unsigned Part = 0; Part < UF; ++Part)
Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy);
addMetadata(Entry, &*it);
case Instruction::Call: {
// Ignore dbg intrinsics.
if (isa<DbgInfoIntrinsic>(it))
setDebugLocFromInst(Builder, &*it);
Module *M = BB->getParent()->getParent();
CallInst *CI = cast<CallInst>(it);
StringRef FnName = CI->getCalledFunction()->getName();
Function *F = CI->getCalledFunction();
Type *RetTy = ToVectorTy(CI->getType(), VF);
SmallVector<Type *, 4> Tys;
for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i)
Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF));
Intrinsic::ID ID = getVectorIntrinsicIDForCall(CI, TLI);
if (ID && (ID == Intrinsic::assume || ID == Intrinsic::lifetime_end ||
ID == Intrinsic::lifetime_start)) {
// The flag shows whether we use Intrinsic or a usual Call for vectorized
// version of the instruction.
// Is it beneficial to perform intrinsic call compared to lib call?
bool NeedToScalarize;
unsigned CallCost = getVectorCallCost(CI, VF, *TTI, TLI, NeedToScalarize);
bool UseVectorIntrinsic =
ID && getVectorIntrinsicCost(CI, VF, *TTI, TLI) <= CallCost;
if (!UseVectorIntrinsic && NeedToScalarize) {
for (unsigned Part = 0; Part < UF; ++Part) {
SmallVector<Value *, 4> Args;
for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) {
Value *Arg = CI->getArgOperand(i);
// Some intrinsics have a scalar argument - don't replace it with a
// vector.
if (!UseVectorIntrinsic || !hasVectorInstrinsicScalarOpd(ID, i)) {
VectorParts &VectorArg = getVectorValue(CI->getArgOperand(i));
Arg = VectorArg[Part];
Function *VectorF;
if (UseVectorIntrinsic) {
// Use vector version of the intrinsic.
Type *TysForDecl[] = {CI->getType()};
if (VF > 1)
TysForDecl[0] = VectorType::get(CI->getType()->getScalarType(), VF);
VectorF = Intrinsic::getDeclaration(M, ID, TysForDecl);
} else {
// Use vector version of the library call.
StringRef VFnName = TLI->getVectorizedFunction(FnName, VF);
assert(!VFnName.empty() && "Vector function name is empty.");
VectorF = M->getFunction(VFnName);
if (!VectorF) {
// Generate a declaration
FunctionType *FTy = FunctionType::get(RetTy, Tys, false);
VectorF =
Function::Create(FTy, Function::ExternalLinkage, VFnName, M);
assert(VectorF && "Can't create vector function.");
SmallVector<OperandBundleDef, 1> OpBundles;
CallInst *V = Builder.CreateCall(VectorF, Args, OpBundles);
if (isa<FPMathOperator>(V))
Entry[Part] = V;
addMetadata(Entry, &*it);
// All other instructions are unsupported. Scalarize them.
} // end of switch.
} // end of for_each instr.
void InnerLoopVectorizer::updateAnalysis() {
// Forget the original basic block.
// Update the dominator tree information.
assert(DT->properlyDominates(LoopBypassBlocks.front(), LoopExitBlock) &&
"Entry does not dominate exit.");
// We don't predicate stores by this point, so the vector body should be a
// single loop.
DT->addNewBlock(LoopVectorBody, LoopVectorPreHeader);
DT->addNewBlock(LoopMiddleBlock, LoopVectorBody);
DT->addNewBlock(LoopScalarPreHeader, LoopBypassBlocks[0]);
DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader);
DT->changeImmediateDominator(LoopExitBlock, LoopBypassBlocks[0]);
/// \brief Check whether it is safe to if-convert this phi node.
/// Phi nodes with constant expressions that can trap are not safe to if
/// convert.
static bool canIfConvertPHINodes(BasicBlock *BB) {
for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
PHINode *Phi = dyn_cast<PHINode>(I);
if (!Phi)
return true;
for (unsigned p = 0, e = Phi->getNumIncomingValues(); p != e; ++p)
if (Constant *C = dyn_cast<Constant>(Phi->getIncomingValue(p)))
if (C->canTrap())
return false;
return true;
bool LoopVectorizationLegality::canVectorizeWithIfConvert() {
if (!EnableIfConversion) {
emitAnalysis(VectorizationReport() << "if-conversion is disabled");
return false;
assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable");
// A list of pointers that we can safely read and write to.
SmallPtrSet<Value *, 8> SafePointes;
// Collect safe addresses.
for (Loop::block_iterator BI = TheLoop->block_begin(),
BE = TheLoop->block_end();
BI != BE; ++BI) {
BasicBlock *BB = *BI;
if (blockNeedsPredication(BB))
for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
if (LoadInst *LI = dyn_cast<LoadInst>(I))
else if (StoreInst *SI = dyn_cast<StoreInst>(I))
// Collect the blocks that need predication.
BasicBlock *Header = TheLoop->getHeader();
for (Loop::block_iterator BI = TheLoop->block_begin(),
BE = TheLoop->block_end();
BI != BE; ++BI) {
BasicBlock *BB = *BI;
// We don't support switch statements inside loops.
if (!isa<BranchInst>(BB->getTerminator())) {
<< "loop contains a switch statement");
return false;
// We must be able to predicate all blocks that need to be predicated.
if (blockNeedsPredication(BB)) {
if (!blockCanBePredicated(BB, SafePointes)) {
<< "control flow cannot be substituted for a select");
return false;
} else if (BB != Header && !canIfConvertPHINodes(BB)) {
<< "control flow cannot be substituted for a select");
return false;
// We can if-convert this loop.
return true;
bool LoopVectorizationLegality::canVectorize() {
// We must have a loop in canonical form. Loops with indirectbr in them cannot
// be canonicalized.
if (!TheLoop->getLoopPreheader()) {
<< "loop control flow is not understood by vectorizer");
return false;
// We can only vectorize innermost loops.
if (!TheLoop->empty()) {
emitAnalysis(VectorizationReport() << "loop is not the innermost loop");
return false;
// We must have a single backedge.
if (TheLoop->getNumBackEdges() != 1) {
<< "loop control flow is not understood by vectorizer");
return false;
// We must have a single exiting block.
if (!TheLoop->getExitingBlock()) {
<< "loop control flow is not understood by vectorizer");
return false;
// We only handle bottom-tested loops, i.e. loop in which the condition is
// checked at the end of each iteration. With that we can assume that all
// instructions in the loop are executed the same number of times.
if (TheLoop->getExitingBlock() != TheLoop->getLoopLatch()) {
<< "loop control flow is not understood by vectorizer");
return false;
// We need to have a loop header.
DEBUG(dbgs() << "LV: Found a loop: " << TheLoop->getHeader()->getName()
<< '\n');
// Check if we can if-convert non-single-bb loops.
unsigned NumBlocks = TheLoop->getNumBlocks();
if (NumBlocks != 1 && !canVectorizeWithIfConvert()) {
DEBUG(dbgs() << "LV: Can't if-convert the loop.\n");
return false;
// ScalarEvolution needs to be able to find the exit count.
const SCEV *ExitCount = PSE.getBackedgeTakenCount();
if (ExitCount == PSE.getSE()->getCouldNotCompute()) {
<< "could not determine number of loop iterations");
DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n");
return false;
// Check if we can vectorize the instructions and CFG in this loop.
if (!canVectorizeInstrs()) {
DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n");
return false;
// Go over each instruction and look at memory deps.
if (!canVectorizeMemory()) {
DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n");
return false;
// Collect all of the variables that remain uniform after vectorization.
DEBUG(dbgs() << "LV: We can vectorize this loop"
<< (LAI->getRuntimePointerChecking()->Need
? " (with a runtime bound check)"
: "")
<< "!\n");
bool UseInterleaved = TTI->enableInterleavedAccessVectorization();
// If an override option has been passed in for interleaved accesses, use it.
if (EnableInterleavedMemAccesses.getNumOccurrences() > 0)
UseInterleaved = EnableInterleavedMemAccesses;
// Analyze interleaved memory accesses.
if (UseInterleaved)
unsigned SCEVThreshold = VectorizeSCEVCheckThreshold;
if (Hints->getForce() == LoopVectorizeHints::FK_Enabled)
SCEVThreshold = PragmaVectorizeSCEVCheckThreshold;
if (PSE.getUnionPredicate().getComplexity() > SCEVThreshold) {
<< "Too many SCEV assumptions need to be made and checked "
<< "at runtime");
DEBUG(dbgs() << "LV: Too many SCEV checks needed.\n");
return false;
// Okay! We can vectorize. At this point we don't have any other mem analysis
// which may limit our maximum vectorization factor, so just return true with
// no restrictions.
return true;
static Type *convertPointerToIntegerType(const DataLayout &DL, Type *Ty) {
if (Ty->isPointerTy())
return DL.getIntPtrType(Ty);
// It is possible that char's or short's overflow when we ask for the loop's
// trip count, work around this by changing the type size.
if (Ty->getScalarSizeInBits() < 32)
return Type::getInt32Ty(Ty->getContext());
return Ty;
static Type *getWiderType(const DataLayout &DL, Type *Ty0, Type *Ty1) {
Ty0 = convertPointerToIntegerType(DL, Ty0);
Ty1 = convertPointerToIntegerType(DL, Ty1);
if (Ty0->getScalarSizeInBits() > Ty1->getScalarSizeInBits())
return Ty0;
return Ty1;
/// \brief Check that the instruction has outside loop users and is not an
/// identified reduction variable.
static bool hasOutsideLoopUser(const Loop *TheLoop, Instruction *Inst,
SmallPtrSetImpl<Value *> &AllowedExit) {
// Reduction and Induction instructions are allowed to have exit users. All
// other instructions must not have external users.
if (!AllowedExit.count(Inst))
// Check that all of the users of the loop are inside the BB.
for (User *U : Inst->users()) {
Instruction *UI = cast<Instruction>(U);
// This user may be a reduction exit value.
if (!TheLoop->contains(UI)) {
DEBUG(dbgs() << "LV: Found an outside user for : " << *UI << '\n');
return true;
return false;
void LoopVectorizationLegality::addInductionPhi(
- PHINode *Phi, InductionDescriptor ID,
+ PHINode *Phi, const InductionDescriptor &ID,
SmallPtrSetImpl<Value *> &AllowedExit) {
Inductions[Phi] = ID;
Type *PhiTy = Phi->getType();
const DataLayout &DL = Phi->getModule()->getDataLayout();
// Get the widest type.
if (!WidestIndTy)
WidestIndTy = convertPointerToIntegerType(DL, PhiTy);
WidestIndTy = getWiderType(DL, PhiTy, WidestIndTy);
// Int inductions are special because we only allow one IV.
if (ID.getKind() == InductionDescriptor::IK_IntInduction &&
ID.getConstIntStepValue() &&
ID.getConstIntStepValue()->isOne() &&
isa<Constant>(ID.getStartValue()) &&
cast<Constant>(ID.getStartValue())->isNullValue()) {
// Use the phi node with the widest type as induction. Use the last
// one if there are multiple (no good reason for doing this other
// than it is expedient). We've checked that it begins at zero and
// steps by one, so this is a canonical induction variable.
if (!Induction || PhiTy == WidestIndTy)
Induction = Phi;
// Both the PHI node itself, and the "post-increment" value feeding
// back into the PHI node may have external users.
DEBUG(dbgs() << "LV: Found an induction variable.\n");
bool LoopVectorizationLegality::canVectorizeInstrs() {
BasicBlock *Header = TheLoop->getHeader();
// Look for the attribute signaling the absence of NaNs.
Function &F = *Header->getParent();
HasFunNoNaNAttr =
F.getFnAttribute("no-nans-fp-math").getValueAsString() == "true";
// For each block in the loop.
for (Loop::block_iterator bb = TheLoop->block_begin(),
be = TheLoop->block_end();
bb != be; ++bb) {
// Scan the instructions in the block and look for hazards.
for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
++it) {
if (PHINode *Phi = dyn_cast<PHINode>(it)) {
Type *PhiTy = Phi->getType();
// Check that this PHI type is allowed.
if (!PhiTy->isIntegerTy() && !PhiTy->isFloatingPointTy() &&
!PhiTy->isPointerTy()) {
<< "loop control flow is not understood by vectorizer");
DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n");
return false;
// If this PHINode is not in the header block, then we know that we
// can convert it to select during if-conversion. No need to check if
// the PHIs in this block are induction or reduction variables.
if (*bb != Header) {
// Check that this instruction has no outside users or is an
// identified reduction value with an outside user.
if (!hasOutsideLoopUser(TheLoop, &*it, AllowedExit))
<< "value could not be identified as "
"an induction or reduction variable");
return false;
// We only allow if-converted PHIs with exactly two incoming values.
if (Phi->getNumIncomingValues() != 2) {
<< "control flow not understood by vectorizer");
DEBUG(dbgs() << "LV: Found an invalid PHI.\n");
return false;
RecurrenceDescriptor RedDes;
if (RecurrenceDescriptor::isReductionPHI(Phi, TheLoop, RedDes)) {
if (RedDes.hasUnsafeAlgebra())
Reductions[Phi] = RedDes;
InductionDescriptor ID;
if (InductionDescriptor::isInductionPHI(Phi, PSE, ID)) {
addInductionPhi(Phi, ID, AllowedExit);
if (RecurrenceDescriptor::isFirstOrderRecurrence(Phi, TheLoop, DT)) {
// As a last resort, coerce the PHI to a AddRec expression
// and re-try classifying it a an induction PHI.
if (InductionDescriptor::isInductionPHI(Phi, PSE, ID, true)) {
addInductionPhi(Phi, ID, AllowedExit);
<< "value that could not be identified as "
"reduction is used outside the loop");
DEBUG(dbgs() << "LV: Found an unidentified PHI." << *Phi << "\n");
return false;
} // end of PHI handling
// We handle calls that:
// * Are debug info intrinsics.
// * Have a mapping to an IR intrinsic.
// * Have a vector version available.
CallInst *CI = dyn_cast<CallInst>(it);
if (CI && !getVectorIntrinsicIDForCall(CI, TLI) &&
!isa<DbgInfoIntrinsic>(CI) &&
!(CI->getCalledFunction() && TLI &&
TLI->isFunctionVectorizable(CI->getCalledFunction()->getName()))) {
<< "call instruction cannot be vectorized");
DEBUG(dbgs() << "LV: Found a non-intrinsic, non-libfunc callsite.\n");
return false;
// Intrinsics such as powi,cttz and ctlz are legal to vectorize if the
// second argument is the same (i.e. loop invariant)
if (CI && hasVectorInstrinsicScalarOpd(
getVectorIntrinsicIDForCall(CI, TLI), 1)) {
auto *SE = PSE.getSE();
if (!SE->isLoopInvariant(PSE.getSCEV(CI->getOperand(1)), TheLoop)) {
<< "intrinsic instruction cannot be vectorized");
DEBUG(dbgs() << "LV: Found unvectorizable intrinsic " << *CI << "\n");
return false;
// Check that the instruction return type is vectorizable.
// Also, we can't vectorize extractelement instructions.
if ((!VectorType::isValidElementType(it->getType()) &&
!it->getType()->isVoidTy()) ||
isa<ExtractElementInst>(it)) {
<< "instruction return type cannot be vectorized");
DEBUG(dbgs() << "LV: Found unvectorizable type.\n");
return false;
// Check that the stored type is vectorizable.
if (StoreInst *ST = dyn_cast<StoreInst>(it)) {
Type *T = ST->getValueOperand()->getType();
if (!VectorType::isValidElementType(T)) {
<< "store instruction cannot be vectorized");
return false;
// FP instructions can allow unsafe algebra, thus vectorizable by
// non-IEEE-754 compliant SIMD units.
// This applies to floating-point math operations and calls, not memory
// operations, shuffles, or casts, as they don't change precision or
// semantics.
} else if (it->getType()->isFloatingPointTy() &&
(CI || it->isBinaryOp()) && !it->hasUnsafeAlgebra()) {
DEBUG(dbgs() << "LV: Found FP op with unsafe algebra.\n");
// Reduction instructions are allowed to have exit users.
// All other instructions must not have external users.
if (hasOutsideLoopUser(TheLoop, &*it, AllowedExit)) {
<< "value cannot be used outside the loop");
return false;
} // next instr.
if (!Induction) {
DEBUG(dbgs() << "LV: Did not find one integer induction var.\n");
if (Inductions.empty()) {
<< "loop induction variable could not be identified");
return false;
// Now we know the widest induction type, check if our found induction
// is the same size. If it's not, unset it here and InnerLoopVectorizer
// will create another.
if (Induction && WidestIndTy != Induction->getType())
Induction = nullptr;
return true;
void LoopVectorizationLegality::collectLoopUniforms() {
// We now know that the loop is vectorizable!
// Collect variables that will remain uniform after vectorization.
std::vector<Value *> Worklist;
BasicBlock *Latch = TheLoop->getLoopLatch();
// Start with the conditional branch and walk up the block.
// Also add all consecutive pointer values; these values will be uniform
// after vectorization (and subsequent cleanup) and, until revectorization is
// supported, all dependencies must also be uniform.
for (Loop::block_iterator B = TheLoop->block_begin(),
BE = TheLoop->block_end();
B != BE; ++B)
for (BasicBlock::iterator I = (*B)->begin(), IE = (*B)->end(); I != IE; ++I)
if (I->getType()->isPointerTy() && isConsecutivePtr(&*I))
Worklist.insert(Worklist.end(), I->op_begin(), I->op_end());
while (!Worklist.empty()) {
Instruction *I = dyn_cast<Instruction>(Worklist.back());
// Look at instructions inside this loop.
// Stop when reaching PHI nodes.
// TODO: we need to follow values all over the loop, not only in this block.
if (!I || !TheLoop->contains(I) || isa<PHINode>(I))
// This is a known uniform.
// Insert all operands.
Worklist.insert(Worklist.end(), I->op_begin(), I->op_end());
bool LoopVectorizationLegality::canVectorizeMemory() {
LAI = &LAA->getInfo(TheLoop, EnableMemAccessVersioning);
auto &OptionalReport = LAI->getReport();
if (OptionalReport)
if (!LAI->canVectorizeMemory())
return false;
if (LAI->hasStoreToLoopInvariantAddress()) {
<< "write to a loop invariant address could not be vectorized");
DEBUG(dbgs() << "LV: We don't allow storing to uniform addresses\n");
return false;
return true;
bool LoopVectorizationLegality::isInductionVariable(const Value *V) {
Value *In0 = const_cast<Value *>(V);
PHINode *PN = dyn_cast_or_null<PHINode>(In0);
if (!PN)
return false;
return Inductions.count(PN);
bool LoopVectorizationLegality::isFirstOrderRecurrence(const PHINode *Phi) {
return FirstOrderRecurrences.count(Phi);
bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB) {
return LoopAccessInfo::blockNeedsPredication(BB, TheLoop, DT);
bool LoopVectorizationLegality::blockCanBePredicated(
BasicBlock *BB, SmallPtrSetImpl<Value *> &SafePtrs) {
const bool IsAnnotatedParallel = TheLoop->isAnnotatedParallel();
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
// Check that we don't have a constant expression that can trap as operand.
for (Instruction::op_iterator OI = it->op_begin(), OE = it->op_end();
OI != OE; ++OI) {
if (Constant *C = dyn_cast<Constant>(*OI))
if (C->canTrap())
return false;
// We might be able to hoist the load.
if (it->mayReadFromMemory()) {
LoadInst *LI = dyn_cast<LoadInst>(it);
if (!LI)
return false;
if (!SafePtrs.count(LI->getPointerOperand())) {
if (isLegalMaskedLoad(LI->getType(), LI->getPointerOperand()) ||
isLegalMaskedGather(LI->getType())) {
// !llvm.mem.parallel_loop_access implies if-conversion safety.
if (IsAnnotatedParallel)
return false;
// We don't predicate stores at the moment.
if (it->mayWriteToMemory()) {
StoreInst *SI = dyn_cast<StoreInst>(it);
// We only support predication of stores in basic blocks with one
// predecessor.
if (!SI)
return false;
// Build a masked store if it is legal for the target.
if (isLegalMaskedStore(SI->getValueOperand()->getType(),
SI->getPointerOperand()) ||
isLegalMaskedScatter(SI->getValueOperand()->getType())) {
bool isSafePtr = (SafePtrs.count(SI->getPointerOperand()) != 0);
bool isSinglePredecessor = SI->getParent()->getSinglePredecessor();
if (++NumPredStores > NumberOfStoresToPredicate || !isSafePtr ||
return false;
if (it->mayThrow())
return false;
// The instructions below can trap.
switch (it->getOpcode()) {
case Instruction::UDiv:
case Instruction::SDiv:
case Instruction::URem:
case Instruction::SRem:
return false;
return true;
void InterleavedAccessInfo::collectConstStridedAccesses(
MapVector<Instruction *, StrideDescriptor> &StrideAccesses,
const ValueToValueMap &Strides) {
// Holds load/store instructions in program order.
SmallVector<Instruction *, 16> AccessList;
for (auto *BB : TheLoop->getBlocks()) {
bool IsPred = LoopAccessInfo::blockNeedsPredication(BB, TheLoop, DT);
for (auto &I : *BB) {
if (!isa<LoadInst>(&I) && !isa<StoreInst>(&I))
// FIXME: Currently we can't handle mixed accesses and predicated accesses
if (IsPred)
if (AccessList.empty())
auto &DL = TheLoop->getHeader()->getModule()->getDataLayout();
for (auto I : AccessList) {
LoadInst *LI = dyn_cast<LoadInst>(I);
StoreInst *SI = dyn_cast<StoreInst>(I);
Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand();
int Stride = getPtrStride(PSE, Ptr, TheLoop, Strides);
// The factor of the corresponding interleave group.
unsigned Factor = std::abs(Stride);
// Ignore the access if the factor is too small or too large.
if (Factor < 2 || Factor > MaxInterleaveGroupFactor)
const SCEV *Scev = replaceSymbolicStrideSCEV(PSE, Strides, Ptr);
PointerType *PtrTy = dyn_cast<PointerType>(Ptr->getType());
unsigned Size = DL.getTypeAllocSize(PtrTy->getElementType());
// An alignment of 0 means target ABI alignment.
unsigned Align = LI ? LI->getAlignment() : SI->getAlignment();
if (!Align)
Align = DL.getABITypeAlignment(PtrTy->getElementType());
StrideAccesses[I] = StrideDescriptor(Stride, Scev, Size, Align);
// Analyze interleaved accesses and collect them into interleave groups.
// Notice that the vectorization on interleaved groups will change instruction
// orders and may break dependences. But the memory dependence check guarantees
// that there is no overlap between two pointers of different strides, element
// sizes or underlying bases.
// For pointers sharing the same stride, element size and underlying base, no
// need to worry about Read-After-Write dependences and Write-After-Read
// dependences.
// E.g. The RAW dependence: A[i] = a;
// b = A[i];
// This won't exist as it is a store-load forwarding conflict, which has
// already been checked and forbidden in the dependence check.
// E.g. The WAR dependence: a = A[i]; // (1)
// A[i] = b; // (2)
// The store group of (2) is always inserted at or below (2), and the load group
// of (1) is always inserted at or above (1). The dependence is safe.
void InterleavedAccessInfo::analyzeInterleaving(
const ValueToValueMap &Strides) {
DEBUG(dbgs() << "LV: Analyzing interleaved accesses...\n");
// Holds all the stride accesses.
MapVector<Instruction *, StrideDescriptor> StrideAccesses;
collectConstStridedAccesses(StrideAccesses, Strides);
if (StrideAccesses.empty())
// Holds all interleaved store groups temporarily.
SmallSetVector<InterleaveGroup *, 4> StoreGroups;
// Holds all interleaved load groups temporarily.
SmallSetVector<InterleaveGroup *, 4> LoadGroups;
// Search the load-load/write-write pair B-A in bottom-up order and try to
// insert B into the interleave group of A according to 3 rules:
// 1. A and B have the same stride.
// 2. A and B have the same memory object size.
// 3. B belongs to the group according to the distance.
// The bottom-up order can avoid breaking the Write-After-Write dependences
// between two pointers of the same base.
// E.g. A[i] = a; (1)
// A[i] = b; (2)
// A[i+1] = c (3)
// We form the group (2)+(3) in front, so (1) has to form groups with accesses
// above (1), which guarantees that (1) is always above (2).
for (auto I = StrideAccesses.rbegin(), E = StrideAccesses.rend(); I != E;
++I) {
Instruction *A = I->first;
StrideDescriptor DesA = I->second;
InterleaveGroup *Group = getInterleaveGroup(A);
if (!Group) {
DEBUG(dbgs() << "LV: Creating an interleave group with:" << *A << '\n');
Group = createInterleaveGroup(A, DesA.Stride, DesA.Align);
if (A->mayWriteToMemory())
for (auto II = std::next(I); II != E; ++II) {
Instruction *B = II->first;
StrideDescriptor DesB = II->second;
// Ignore if B is already in a group or B is a different memory operation.
if (isInterleaved(B) || A->mayReadFromMemory() != B->mayReadFromMemory())
// Check the rule 1 and 2.
if (DesB.Stride != DesA.Stride || DesB.Size != DesA.Size)
// Calculate the distance and prepare for the rule 3.
const SCEVConstant *DistToA = dyn_cast<SCEVConstant>(
PSE.getSE()->getMinusSCEV(DesB.Scev, DesA.Scev));
if (!DistToA)
int DistanceToA = DistToA->getAPInt().getSExtValue();
// Skip if the distance is not multiple of size as they are not in the
// same group.
if (DistanceToA % static_cast<int>(DesA.Size))
// The index of B is the index of A plus the related index to A.
int IndexB =
Group->getIndex(A) + DistanceToA / static_cast<int>(DesA.Size);
// Try to insert B into the group.
if (Group->insertMember(B, IndexB, DesB.Align)) {
DEBUG(dbgs() << "LV: Inserted:" << *B << '\n'
<< " into the interleave group with" << *A << '\n');
InterleaveGroupMap[B] = Group;
// Set the first load in program order as the insert position.
if (B->mayReadFromMemory())
} // Iteration on instruction B
} // Iteration on instruction A
// Remove interleaved store groups with gaps.
for (InterleaveGroup *Group : StoreGroups)
if (Group->getNumMembers() != Group->getFactor())
// If there is a non-reversed interleaved load group with gaps, we will need
// to execute at least one scalar epilogue iteration. This will ensure that
// we don't speculatively access memory out-of-bounds. Note that we only need
// to look for a member at index factor - 1, since every group must have a
// member at index zero.
for (InterleaveGroup *Group : LoadGroups)
if (!Group->getMember(Group->getFactor() - 1)) {
if (Group->isReverse()) {
} else {
DEBUG(dbgs() << "LV: Interleaved group requires epilogue iteration.\n");
RequiresScalarEpilogue = true;
LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize) {
// Width 1 means no vectorize
VectorizationFactor Factor = {1U, 0U};
if (OptForSize && Legal->getRuntimePointerChecking()->Need) {
<< "runtime pointer checks needed. Enable vectorization of this "
"loop with '#pragma clang loop vectorize(enable)' when "
"compiling with -Os/-Oz");
<< "LV: Aborting. Runtime ptr check is required with -Os/-Oz.\n");
return Factor;
if (!EnableCondStoresVectorization && Legal->getNumPredStores()) {
<< "store that is conditionally executed prevents vectorization");
DEBUG(dbgs() << "LV: No vectorization. There are conditional stores.\n");
return Factor;
// Find the trip count.
unsigned TC = PSE.getSE()->getSmallConstantTripCount(TheLoop);
DEBUG(dbgs() << "LV: Found trip count: " << TC << '\n');
MinBWs = computeMinimumValueSizes(TheLoop->getBlocks(), *DB, &TTI);
unsigned SmallestType, WidestType;
std::tie(SmallestType, WidestType) = getSmallestAndWidestTypes();
unsigned WidestRegister = TTI.getRegisterBitWidth(true);
unsigned MaxSafeDepDist = -1U;
// Get the maximum safe dependence distance in bits computed by LAA. If the
// loop contains any interleaved accesses, we divide the dependence distance
// by the maximum interleave factor of all interleaved groups. Note that
// although the division ensures correctness, this is a fairly conservative
// computation because the maximum distance computed by LAA may not involve
// any of the interleaved accesses.
if (Legal->getMaxSafeDepDistBytes() != -1U)
MaxSafeDepDist =
Legal->getMaxSafeDepDistBytes() * 8 / Legal->getMaxInterleaveFactor();
WidestRegister =
((WidestRegister < MaxSafeDepDist) ? WidestRegister : MaxSafeDepDist);
unsigned MaxVectorSize = WidestRegister / WidestType;
DEBUG(dbgs() << "LV: The Smallest and Widest types: " << SmallestType << " / "
<< WidestType << " bits.\n");
DEBUG(dbgs() << "LV: The Widest register is: " << WidestRegister
<< " bits.\n");
if (MaxVectorSize == 0) {
DEBUG(dbgs() << "LV: The target has no vector registers.\n");
MaxVectorSize = 1;
assert(MaxVectorSize <= 64 && "Did not expect to pack so many elements"
" into one vector!");
unsigned VF = MaxVectorSize;
if (MaximizeBandwidth && !OptForSize) {
// Collect all viable vectorization factors.
SmallVector<unsigned, 8> VFs;
unsigned NewMaxVectorSize = WidestRegister / SmallestType;
for (unsigned VS = MaxVectorSize; VS <= NewMaxVectorSize; VS *= 2)
// For each VF calculate its register usage.
auto RUs = calculateRegisterUsage(VFs);
// Select the largest VF which doesn't require more registers than existing
// ones.
unsigned TargetNumRegisters = TTI.getNumberOfRegisters(true);
for (int i = RUs.size() - 1; i >= 0; --i) {
if (RUs[i].MaxLocalUsers <= TargetNumRegisters) {
VF = VFs[i];
// If we optimize the program for size, avoid creating the tail loop.
if (OptForSize) {
// If we are unable to calculate the trip count then don't try to vectorize.
if (TC < 2) {
<< "unable to calculate the loop count due to complex control flow");
DEBUG(dbgs() << "LV: Aborting. A tail loop is required with -Os/-Oz.\n");
return Factor;
// Find the maximum SIMD width that can fit within the trip count.
VF = TC % MaxVectorSize;
if (VF == 0)
VF = MaxVectorSize;
else {
// If the trip count that we found modulo the vectorization factor is not
// zero then we require a tail.
<< "cannot optimize for size and vectorize at the "
"same time. Enable vectorization of this loop "
"with '#pragma clang loop vectorize(enable)' "
"when compiling with -Os/-Oz");
DEBUG(dbgs() << "LV: Aborting. A tail loop is required with -Os/-Oz.\n");
return Factor;
int UserVF = Hints->getWidth();
if (UserVF != 0) {
assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two");
DEBUG(dbgs() << "LV: Using user VF " << UserVF << ".\n");
Factor.Width = UserVF;
return Factor;
float Cost = expectedCost(1).first;
#ifndef NDEBUG
const float ScalarCost = Cost;
#endif /* NDEBUG */
unsigned Width = 1;
DEBUG(dbgs() << "LV: Scalar loop costs: " << (int)ScalarCost << ".\n");
bool ForceVectorization = Hints->getForce() == LoopVectorizeHints::FK_Enabled;
// Ignore scalar width, because the user explicitly wants vectorization.
if (ForceVectorization && VF > 1) {
Width = 2;
Cost = expectedCost(Width).first / (float)Width;
for (unsigned i = 2; i <= VF; i *= 2) {
// Notice that the vector loop needs to be executed less times, so
// we need to divide the cost of the vector loops by the width of
// the vector elements.
VectorizationCostTy C = expectedCost(i);
float VectorCost = C.first / (float)i;
DEBUG(dbgs() << "LV: Vector loop of width " << i
<< " costs: " << (int)VectorCost << ".\n");
if (!C.second && !ForceVectorization) {
dbgs() << "LV: Not considering vector loop of width " << i
<< " because it will not generate any vector instructions.\n");
if (VectorCost < Cost) {
Cost = VectorCost;
Width = i;
DEBUG(if (ForceVectorization && Width > 1 && Cost >= ScalarCost) dbgs()
<< "LV: Vectorization seems to be not beneficial, "
<< "but was forced by a user.\n");
DEBUG(dbgs() << "LV: Selecting VF: " << Width << ".\n");
Factor.Width = Width;
Factor.Cost = Width * Cost;
return Factor;
std::pair<unsigned, unsigned>
LoopVectorizationCostModel::getSmallestAndWidestTypes() {
unsigned MinWidth = -1U;
unsigned MaxWidth = 8;
const DataLayout &DL = TheFunction->getParent()->getDataLayout();
// For each block.
for (Loop::block_iterator bb = TheLoop->block_begin(),
be = TheLoop->block_end();
bb != be; ++bb) {
BasicBlock *BB = *bb;
// For each instruction in the loop.
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
Type *T = it->getType();
// Skip ignored values.
if (ValuesToIgnore.count(&*it))
// Only examine Loads, Stores and PHINodes.
if (!isa<LoadInst>(it) && !isa<StoreInst>(it) && !isa<PHINode>(it))
// Examine PHI nodes that are reduction variables. Update the type to
// account for the recurrence type.
if (PHINode *PN = dyn_cast<PHINode>(it)) {
if (!Legal->isReductionVariable(PN))
RecurrenceDescriptor RdxDesc = (*Legal->getReductionVars())[PN];
T = RdxDesc.getRecurrenceType();
// Examine the stored values.
if (StoreInst *ST = dyn_cast<StoreInst>(it))
T = ST->getValueOperand()->getType();
// Ignore loaded pointer types and stored pointer types that are not
// consecutive. However, we do want to take consecutive stores/loads of
// pointer vectors into account.
if (T->isPointerTy() && !isConsecutiveLoadOrStore(&*it))
MinWidth = std::min(MinWidth,
MaxWidth = std::max(MaxWidth,
return {MinWidth, MaxWidth};
unsigned LoopVectorizationCostModel::selectInterleaveCount(bool OptForSize,
unsigned VF,
unsigned LoopCost) {
// -- The interleave heuristics --
// We interleave the loop in order to expose ILP and reduce the loop overhead.
// There are many micro-architectural considerations that we can't predict
// at this level. For example, frontend pressure (on decode or fetch) due to
// code size, or the number and capabilities of the execution ports.
// We use the following heuristics to select the interleave count:
// 1. If the code has reductions, then we interleave to break the cross
// iteration dependency.
// 2. If the loop is really small, then we interleave to reduce the loop
// overhead.
// 3. We don't interleave if we think that we will spill registers to memory
// due to the increased register pressure.
// When we optimize for size, we don't interleave.
if (OptForSize)
return 1;
// We used the distance for the interleave count.
if (Legal->getMaxSafeDepDistBytes() != -1U)
return 1;
// Do not interleave loops with a relatively small trip count.
unsigned TC = PSE.getSE()->getSmallConstantTripCount(TheLoop);
if (TC > 1 && TC < TinyTripCountInterleaveThreshold)
return 1;
unsigned TargetNumRegisters = TTI.getNumberOfRegisters(VF > 1);
DEBUG(dbgs() << "LV: The target has " << TargetNumRegisters
<< " registers\n");
if (VF == 1) {
if (ForceTargetNumScalarRegs.getNumOccurrences() > 0)
TargetNumRegisters = ForceTargetNumScalarRegs;
} else {
if (ForceTargetNumVectorRegs.getNumOccurrences() > 0)
TargetNumRegisters = ForceTargetNumVectorRegs;
RegisterUsage R = calculateRegisterUsage({VF})[0];
// We divide by these constants so assume that we have at least one
// instruction that uses at least one register.
R.MaxLocalUsers = std::max(R.MaxLocalUsers, 1U);
R.NumInstructions = std::max(R.NumInstructions, 1U);
// We calculate the interleave count using the following formula.
// Subtract the number of loop invariants from the number of available
// registers. These registers are used by all of the interleaved instances.
// Next, divide the remaining registers by the number of registers that is
// required by the loop, in order to estimate how many parallel instances
// fit without causing spills. All of this is rounded down if necessary to be
// a power of two. We want power of two interleave count to simplify any
// addressing operations or alignment considerations.
unsigned IC = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs) /
// Don't count the induction variable as interleaved.
if (EnableIndVarRegisterHeur)
IC = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs - 1) /
std::max(1U, (R.MaxLocalUsers - 1)));
// Clamp the interleave ranges to reasonable counts.
unsigned MaxInterleaveCount = TTI.getMaxInterleaveFactor(VF);
// Check if the user has overridden the max.
if (VF == 1) {
if (ForceTargetMaxScalarInterleaveFactor.getNumOccurrences() > 0)
MaxInterleaveCount = ForceTargetMaxScalarInterleaveFactor;
} else {
if (ForceTargetMaxVectorInterleaveFactor.getNumOccurrences() > 0)
MaxInterleaveCount = ForceTargetMaxVectorInterleaveFactor;
// If we did not calculate the cost for VF (because the user selected the VF)
// then we calculate the cost of VF here.
if (LoopCost == 0)
LoopCost = expectedCost(VF).first;
// Clamp the calculated IC to be between the 1 and the max interleave count
// that the target allows.
if (IC > MaxInterleaveCount)
IC = MaxInterleaveCount;
else if (IC < 1)
IC = 1;
// Interleave if we vectorized this loop and there is a reduction that could
// benefit from interleaving.
if (VF > 1 && Legal->getReductionVars()->size()) {
DEBUG(dbgs() << "LV: Interleaving because of reductions.\n");
return IC;
// Note that if we've already vectorized the loop we will have done the
// runtime check and so interleaving won't require further checks.
bool InterleavingRequiresRuntimePointerCheck =
(VF == 1 && Legal->getRuntimePointerChecking()->Need);
// We want to interleave small loops in order to reduce the loop overhead and
// potentially expose ILP opportunities.
DEBUG(dbgs() << "LV: Loop cost is " << LoopCost << '\n');
if (!InterleavingRequiresRuntimePointerCheck && LoopCost < SmallLoopCost) {
// We assume that the cost overhead is 1 and we use the cost model
// to estimate the cost of the loop and interleave until the cost of the
// loop overhead is about 5% of the cost of the loop.
unsigned SmallIC =
std::min(IC, (unsigned)PowerOf2Floor(SmallLoopCost / LoopCost));
// Interleave until store/load ports (estimated by max interleave count) are
// saturated.
unsigned NumStores = Legal->getNumStores();
unsigned NumLoads = Legal->getNumLoads();
unsigned StoresIC = IC / (NumStores ? NumStores : 1);
unsigned LoadsIC = IC / (NumLoads ? NumLoads : 1);
// If we have a scalar reduction (vector reductions are already dealt with
// by this point), we can increase the critical path length if the loop
// we're interleaving is inside another loop. Limit, by default to 2, so the
// critical path only gets increased by one reduction operation.
if (Legal->getReductionVars()->size() && TheLoop->getLoopDepth() > 1) {
unsigned F = static_cast<unsigned>(MaxNestedScalarReductionIC);
SmallIC = std::min(SmallIC, F);
StoresIC = std::min(StoresIC, F);
LoadsIC = std::min(LoadsIC, F);
if (EnableLoadStoreRuntimeInterleave &&
std::max(StoresIC, LoadsIC) > SmallIC) {
DEBUG(dbgs() << "LV: Interleaving to saturate store or load ports.\n");
return std::max(StoresIC, LoadsIC);
DEBUG(dbgs() << "LV: Interleaving to reduce branch cost.\n");
return SmallIC;
// Interleave if this is a large loop (small loops are already dealt with by
// this point) that could benefit from interleaving.
bool HasReductions = (Legal->getReductionVars()->size() > 0);
if (TTI.enableAggressiveInterleaving(HasReductions)) {
DEBUG(dbgs() << "LV: Interleaving to expose ILP.\n");
return IC;
DEBUG(dbgs() << "LV: Not Interleaving.\n");
return 1;
SmallVector<LoopVectorizationCostModel::RegisterUsage, 8>
LoopVectorizationCostModel::calculateRegisterUsage(ArrayRef<unsigned> VFs) {
// This function calculates the register usage by measuring the highest number
// of values that are alive at a single location. Obviously, this is a very
// rough estimation. We scan the loop in a topological order in order and
// assign a number to each instruction. We use RPO to ensure that defs are
// met before their users. We assume that each instruction that has in-loop
// users starts an interval. We record every time that an in-loop value is
// used, so we have a list of the first and last occurrences of each
// instruction. Next, we transpose this data structure into a multi map that
// holds the list of intervals that *end* at a specific location. This multi
// map allows us to perform a linear search. We scan the instructions linearly
// and record each time that a new interval starts, by placing it in a set.
// If we find this value in the multi-map then we remove it from the set.
// The max register usage is the maximum size of the set.
// We also search for instructions that are defined outside the loop, but are
// used inside the loop. We need this number separately from the max-interval
// usage number because when we unroll, loop-invariant values do not take
// more register.
LoopBlocksDFS DFS(TheLoop);
RegisterUsage RU;
RU.NumInstructions = 0;
// Each 'key' in the map opens a new interval. The values
// of the map are the index of the 'last seen' usage of the
// instruction that is the key.
typedef DenseMap<Instruction *, unsigned> IntervalMap;
// Maps instruction to its index.
DenseMap<unsigned, Instruction *> IdxToInstr;
// Marks the end of each interval.
IntervalMap EndPoint;
// Saves the list of instruction indices that are used in the loop.
SmallSet<Instruction *, 8> Ends;
// Saves the list of values that are used in the loop but are
// defined outside the loop, such as arguments and constants.
SmallPtrSet<Value *, 8> LoopInvariants;
unsigned Index = 0;
for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(), be = DFS.endRPO();
bb != be; ++bb) {
RU.NumInstructions += (*bb)->size();
for (Instruction &I : **bb) {
IdxToInstr[Index++] = &I;
// Save the end location of each USE.
for (unsigned i = 0; i < I.getNumOperands(); ++i) {
Value *U = I.getOperand(i);
Instruction *Instr = dyn_cast<Instruction>(U);
// Ignore non-instruction values such as arguments, constants, etc.
if (!Instr)
// If this instruction is outside the loop then record it and continue.
if (!TheLoop->contains(Instr)) {
// Overwrite previous end points.
EndPoint[Instr] = Index;
// Saves the list of intervals that end with the index in 'key'.
typedef SmallVector<Instruction *, 2> InstrList;
DenseMap<unsigned, InstrList> TransposeEnds;
// Transpose the EndPoints to a list of values that end at each index.
for (IntervalMap::iterator it = EndPoint.begin(), e = EndPoint.end(); it != e;
SmallSet<Instruction *, 8> OpenIntervals;
// Get the size of the widest register.
unsigned MaxSafeDepDist = -1U;
if (Legal->getMaxSafeDepDistBytes() != -1U)
MaxSafeDepDist = Legal->getMaxSafeDepDistBytes() * 8;
unsigned WidestRegister =
std::min(TTI.getRegisterBitWidth(true), MaxSafeDepDist);
const DataLayout &DL = TheFunction->getParent()->getDataLayout();
SmallVector<RegisterUsage, 8> RUs(VFs.size());
SmallVector<unsigned, 8> MaxUsages(VFs.size(), 0);
DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n");
// A lambda that gets the register usage for the given type and VF.
auto GetRegUsage = [&DL, WidestRegister](Type *Ty, unsigned VF) {
if (Ty->isTokenTy())
return 0U;
unsigned TypeSize = DL.getTypeSizeInBits(Ty->getScalarType());
return std::max<unsigned>(1, VF * TypeSize / WidestRegister);
for (unsigned int i = 0; i < Index; ++i) {
Instruction *I = IdxToInstr[i];
// Ignore instructions that are never used within the loop.
if (!Ends.count(I))
// Remove all of the instructions that end at this location.
InstrList &List = TransposeEnds[i];
for (unsigned int j = 0, e = List.size(); j < e; ++j)
// Skip ignored values.
if (ValuesToIgnore.count(I))
// For each VF find the maximum usage of registers.
for (unsigned j = 0, e = VFs.size(); j < e; ++j) {
if (VFs[j] == 1) {
MaxUsages[j] = std::max(MaxUsages[j], OpenIntervals.size());
// Count the number of live intervals.
unsigned RegUsage = 0;
for (auto Inst : OpenIntervals) {
// Skip ignored values for VF > 1.
if (VecValuesToIgnore.count(Inst))
RegUsage += GetRegUsage(Inst->getType(), VFs[j]);
MaxUsages[j] = std::max(MaxUsages[j], RegUsage);
DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # "
<< OpenIntervals.size() << '\n');
// Add the current instruction to the list of open intervals.
for (unsigned i = 0, e = VFs.size(); i < e; ++i) {
unsigned Invariant = 0;
if (VFs[i] == 1)
Invariant = LoopInvariants.size();
else {
for (auto Inst : LoopInvariants)
Invariant += GetRegUsage(Inst->getType(), VFs[i]);
DEBUG(dbgs() << "LV(REG): VF = " << VFs[i] << '\n');
DEBUG(dbgs() << "LV(REG): Found max usage: " << MaxUsages[i] << '\n');
DEBUG(dbgs() << "LV(REG): Found invariant usage: " << Invariant << '\n');
DEBUG(dbgs() << "LV(REG): LoopSize: " << RU.NumInstructions << '\n');
RU.LoopInvariantRegs = Invariant;
RU.MaxLocalUsers = MaxUsages[i];
RUs[i] = RU;
return RUs;
LoopVectorizationCostModel::expectedCost(unsigned VF) {
VectorizationCostTy Cost;
// For each block.
for (Loop::block_iterator bb = TheLoop->block_begin(),
be = TheLoop->block_end();
bb != be; ++bb) {
VectorizationCostTy BlockCost;
BasicBlock *BB = *bb;
// For each instruction in the old loop.
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
// Skip dbg intrinsics.
if (isa<DbgInfoIntrinsic>(it))
// Skip ignored values.
if (ValuesToIgnore.count(&*it))
VectorizationCostTy C = getInstructionCost(&*it, VF);
// Check if we should override the cost.
if (ForceTargetInstructionCost.getNumOccurrences() > 0)
C.first = ForceTargetInstructionCost;
BlockCost.first += C.first;
BlockCost.second |= C.second;
DEBUG(dbgs() << "LV: Found an estimated cost of " << C.first << " for VF "
<< VF << " For instruction: " << *it << '\n');
// We assume that if-converted blocks have a 50% chance of being executed.
// When the code is scalar then some of the blocks are avoided due to CF.
// When the code is vectorized we execute all code paths.
if (VF == 1 && Legal->blockNeedsPredication(*bb))
BlockCost.first /= 2;
Cost.first += BlockCost.first;
Cost.second |= BlockCost.second;
return Cost;
/// \brief Check if the load/store instruction \p I may be translated into
/// gather/scatter during vectorization.
/// Pointer \p Ptr specifies address in memory for the given scalar memory
/// instruction. We need it to retrieve data type.
/// Using gather/scatter is possible when it is supported by target.
static bool isGatherOrScatterLegal(Instruction *I, Value *Ptr,
LoopVectorizationLegality *Legal) {
Type *DataTy = cast<PointerType>(Ptr->getType())->getElementType();
return (isa<LoadInst>(I) && Legal->isLegalMaskedGather(DataTy)) ||
(isa<StoreInst>(I) && Legal->isLegalMaskedScatter(DataTy));
/// \brief Check whether the address computation for a non-consecutive memory
/// access looks like an unlikely candidate for being merged into the indexing
/// mode.
/// We look for a GEP which has one index that is an induction variable and all
/// other indices are loop invariant. If the stride of this access is also
/// within a small bound we decide that this address computation can likely be
/// merged into the addressing mode.
/// In all other cases, we identify the address computation as complex.
static bool isLikelyComplexAddressComputation(Value *Ptr,
LoopVectorizationLegality *Legal,
ScalarEvolution *SE,
const Loop *TheLoop) {
GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
if (!Gep)
return true;
// We are looking for a gep with all loop invariant indices except for one
// which should be an induction variable.
unsigned NumOperands = Gep->getNumOperands();
for (unsigned i = 1; i < NumOperands; ++i) {
Value *Opd = Gep->getOperand(i);