[InstrProf] Minimal Block Coverage

[ellis]

Summary

This diff implements minimal block coverage instrumentation. When the -pgo-block-coverage option is used, basic blocks will be instrumented for block coverage using single byte booleans. The coverage of some basic blocks can be inferred from others, so not every basic block is instrumented. In fact, we found that only ~60% of basic blocks need to be instrumented. These differences lead to less size overhead when compared to instrumenting block counts. For example, block coverage on the clang binary has an overhead of 20 Mi (17%) compared to 56 Mi (47%) with block counts.

Even though block coverage profiles have less precision than block count profiles, they can still be used to guide optimizations. In PGOUseFunc we use block coverage to populate edge weights such that BFI gives nonzero counts to only covered blocks. We do this by 1) setting the entry count of covered functions to a large value, i.e., 10000 and 2) populating edge weights using block coverage. In the next diff https://reviews.llvm.org/D125743 we use BFI to guide the machine outliner to avoid outlining covered blocks. This -pgo-block-coverage option provides a trade off of generating less precise profiles for faster and smaller instrumented binaries.

The BlockCoverageInference class defines the algorithm to find the minimal set of basic blocks that need to be instrumented for coverage. This is different from the Kirchhoff circuit law optimization that is used for edge counts because that does not work for block coverage. The reason for this is that edge counts can be added together to find a missing count while block coverage cannot since they store boolean values. So we need a new algorithm to find which blocks must be instrumented.

The details on this algorithm can be found in this paper titled "Minimum Coverage Instrumentation": https://arxiv.org/abs/2208.13907

Special thanks to Julian Mestre for creating this block coverage inference algorithm.

Binary size of clang using -O2:

• Base
  • .text: 65.8 Mi
  • Total: 119 Mi
• IRPGO (-fprofile-generate -mllvm -disable-vp -mllvm -debug-info-correlate)
  • .text: 93.0 Mi
  • __llvm_prf_cnts: 14.5 Mi
  • Total: 175 Mi
• Minimal Block Coverage (-fprofile-generate -mllvm -disable-vp -mllvm -debug-info-correlate -mllvm -pgo-block-coverage)
  • .text: 82.1 Mi
  • __llvm_prf_cnts: 1.38 Mi
  • Total: 139 Mi

[MaskRay]

Special thanks to Julian Mestre for creating this block coverage inference algorithm.

I haven't read the code yet but can you briefly describe it in the summary?

How is this compared with Kirchhoff circuit law optimization which requires integral execution counts?
Note: -fprofile-instr-generate is quite a bit slower because it does not have the optimization.

[ellis]

In D124490#3516747, @MaskRay wrote:

Special thanks to Julian Mestre for creating this block coverage inference algorithm.

I haven't read the code yet but can you briefly describe it in the summary?

How is this compared with Kirchhoff circuit law optimization which requires integral execution counts?
Note: -fprofile-instr-generate is quite a bit slower because it does not have the optimization.

I've updated the summary to explain the algorithm.

[paquette]

Do the outliner changes need to be a part of this patch? Or can you split the outliner changes out into a separate patch, and then add that separate patch as a child of this one?

[ellis]

Rebase and separate out machine outliner code into https://reviews.llvm.org/D125743

[gulfem]

Hi @ellis,

This is exciting for us! We are interested in using single byte booleans for source-based code coverage, and I am currently working on the implementation.
We are trying to find a good solution to the problem that you described that missing counts cannot be inferred by doing arithmetic on other block counts when we use boolean counters.
For ex, in an if statement, else part is not instrumented, and its counter is inferred by subtracting parent and then counters.
When we use the boolean values for counters, this cannot be done anymore.
Simpler approach is to instrument more basic blocks, but we are exploring approaches that add counters to minimal blocks.
One of the biggest differences of coverage and PGO is that counters are emitted by traversing AST nodes in the front-end for coverage, whereas they are emitted by traversing CFG nodes for PGO.
The algorithm that you introduced is based on CFG traversal. I'm looking at that to see whether this can be repurposed for coverage.

A few questions:

1. You mentioned that "we found that only ~60% of basic blocks need to be instrumented". With boolean counters, do you how much that has changed?
2. Size reduction is great! Do you have any data on the impact of block coverage on compilation time and runtime performance? For coverage, we are also aiming runtime performance with boolean counters.
3. Did you do any verification to compare the correctness of block coverage like comparing it against block counts?

It seems like we are trying to solve similar problems in different contexts, so we would be very interested in collaboration.

[ellis]

In D124490#3520905, @gulfem wrote:

Hi @ellis,

This is exciting for us! We are interested in using single byte booleans for source-based code coverage, and I am currently working on the implementation.
We are trying to find a good solution to the problem that you described that missing counts cannot be inferred by doing arithmetic on other block counts when we use boolean counters.
For ex, in an if statement, else part is not instrumented, and its counter is inferred by subtracting parent and then counters.
When we use the boolean values for counters, this cannot be done anymore.
Simpler approach is to instrument more basic blocks, but we are exploring approaches that add counters to minimal blocks.
One of the biggest differences of coverage and PGO is that counters are emitted by traversing AST nodes in the front-end for coverage, whereas they are emitted by traversing CFG nodes for PGO.
The algorithm that you introduced is based on CFG traversal. I'm looking at that to see whether this can be repurposed for coverage.

A few questions:

1. You mentioned that "we found that only ~60% of basic blocks need to be instrumented". With boolean counters, do you how much that has changed?
2. Size reduction is great! Do you have any data on the impact of block coverage on compilation time and runtime performance? For coverage, we are also aiming runtime performance with boolean counters.
3. Did you do any verification to compare the correctness of block coverage like comparing it against block counts?

It seems like we are trying to solve similar problems in different contexts, so we would be very interested in collaboration.

I'm happy to see interest in coverage instrumentation!

1. Let me clarify. The existing "Kirchhoff circuit law" optimization used for 64 bit counters allows us to instrument a subset of basic blocks. IIRC we need to instrument slightly more than 60% of basic blocks to do this. For the minimal block coverage algorithm I've implemented here, we also only need to instrument ~60% of basic blocks. Of course, the blocks we instrument are not the same in both algorithms, but the number of blocks is roughly the same.
2. I haven't analyzed compilation time, but the theoretical runtime is O(|E| * |V|). For runtime performance, I also haven't measured this but my intuition is that this is very close to optimal since we are adding a single store in as few blocks as possible. In some cases there is some choice in which blocks to instrument and so we could try to make better decisions there, e.g., choose to instrument a rarely executed block rather than one in a tight loop.
3. My colleague Julian Mestre actually proved that the algorithm produces a correct instrumentation and also that it produces a minimal instrumentation. So we cannot find a coverage that instruments fewer blocks. We are planning on publishing these results in a paper, but that might not be for some time.

I've implemented BlockCoverageInference to assume we are instrumenting Blocks in a CFG, but there is nothing special about blocks. This algorithm will work on any directed graph with entry and exit nodes. I think we can extend this class to support a more general graph and use it for AST coverage. Let me know if you think this could work.

I'm also wondering if we could use this PGO coverage to infer source-based code coverage by looking at debug info.

[ellis]

Remove isBlockRarelyExecuted() API.
For covered functions, set the entry count to 10000 so that BFI correctly gives non-zero profile counts to only covered blocks.

[gulfem]

In D124490#3522697, @ellis wrote:

In D124490#3520905, @gulfem wrote:

Hi @ellis,

This is exciting for us! We are interested in using single byte booleans for source-based code coverage, and I am currently working on the implementation.
We are trying to find a good solution to the problem that you described that missing counts cannot be inferred by doing arithmetic on other block counts when we use boolean counters.
For ex, in an if statement, else part is not instrumented, and its counter is inferred by subtracting parent and then counters.
When we use the boolean values for counters, this cannot be done anymore.
Simpler approach is to instrument more basic blocks, but we are exploring approaches that add counters to minimal blocks.
One of the biggest differences of coverage and PGO is that counters are emitted by traversing AST nodes in the front-end for coverage, whereas they are emitted by traversing CFG nodes for PGO.
The algorithm that you introduced is based on CFG traversal. I'm looking at that to see whether this can be repurposed for coverage.

A few questions:

1. You mentioned that "we found that only ~60% of basic blocks need to be instrumented". With boolean counters, do you how much that has changed?
2. Size reduction is great! Do you have any data on the impact of block coverage on compilation time and runtime performance? For coverage, we are also aiming runtime performance with boolean counters.
3. Did you do any verification to compare the correctness of block coverage like comparing it against block counts?

It seems like we are trying to solve similar problems in different contexts, so we would be very interested in collaboration.

I'm happy to see interest in coverage instrumentation!

1. Let me clarify. The existing "Kirchhoff circuit law" optimization used for 64 bit counters allows us to instrument a subset of basic blocks. IIRC we need to instrument slightly more than 60% of basic blocks to do this. For the minimal block coverage algorithm I've implemented here, we also only need to instrument ~60% of basic blocks. Of course, the blocks we instrument are not the same in both algorithms, but the number of blocks is roughly the same.
2. I haven't analyzed compilation time, but the theoretical runtime is O(|E| * |V|). For runtime performance, I also haven't measured this but my intuition is that this is very close to optimal since we are adding a single store in as few blocks as possible. In some cases there is some choice in which blocks to instrument and so we could try to make better decisions there, e.g., choose to instrument a rarely executed block rather than one in a tight loop.
3. My colleague Julian Mestre actually proved that the algorithm produces a correct instrumentation and also that it produces a minimal instrumentation. So we cannot find a coverage that instruments fewer blocks. We are planning on publishing these results in a paper, but that might not be for some time.

That's great!

I've implemented BlockCoverageInference to assume we are instrumenting Blocks in a CFG, but there is nothing special about blocks. This algorithm will work on any directed graph with entry and exit nodes. I think we can extend this class to support a more general graph and use it for AST coverage. Let me know if you think this could work.

CoverageMappingGen.cpp adds counters while traversing AST. For ex, this is how counters are added for an if statement.
https://github.com/llvm/llvm-project/blob/main/clang/lib/CodeGen/CoverageMappingGen.cpp#L1383
I'm currently building the prototype for using boolean counters in coverage, and I'm planning to upload a WIP review soon.
After that, we can discuss further whether BlockCoverageInference can be generalized.

I'm also wondering if we could use this PGO coverage to infer source-based code coverage by looking at debug info.

How are you planning to use block coverage for PGO?
In some of the tools that we show source-based coverage, we show whether a line is covered by the executed tests and do not show how many times each line is executed. For this specific purpose, we want to use single byte counters.
Although I'm not that familiar with PGO implementation, it seems like number counters might be more beneficial for making optimization decisions for PGO. Are there specific optimizations that you are planning to use block coverage?

[ellis]

In D124490#3526752, @gulfem wrote:

CoverageMappingGen.cpp adds counters while traversing AST. For ex, this is how counters are added for an if statement.
https://github.com/llvm/llvm-project/blob/main/clang/lib/CodeGen/CoverageMappingGen.cpp#L1383
I'm currently building the prototype for using boolean counters in coverage, and I'm planning to upload a WIP review soon.
After that, we can discuss further whether BlockCoverageInference can be generalized.

In D124490#3522697, @ellis wrote:

I'm also wondering if we could use this PGO coverage to infer source-based code coverage by looking at debug info.

How are you planning to use block coverage for PGO?
In some of the tools that we show source-based coverage, we show whether a line is covered by the executed tests and do not show how many times each line is executed. For this specific purpose, we want to use single byte counters.
Although I'm not that familiar with PGO implementation, it seems like number counters might be more beneficial for making optimization decisions for PGO. Are there specific optimizations that you are planning to use block coverage?

The default PGO instruments counters and is useful for optimization. That problem is that this instrumentation is expensive with respect to binary size and runtime. This diff adds a block coverage mode which is much smaller and faster, although the data is not as precise. In the parent diff D125743 I've added support to use block coverage to outline blocks that are not covered and we may use this data to guide more optimizations in the future.

About the source-based coverage, my intuition is that adding coverage instrumentation to clang AST is less efficient than adding coverage instrumentation to blocks in the LLVM-IR like this diff does. In theory, I think it's possible to map covered LLVM-IR blocks to source code using debug info. Then you would only need to run this block instrumentation and get source coverage out of the profiles. Unfortunately, we don't maintain the binary address or source locations of instrumented blocks in our profiles, so this idea would require some format changes. I'm just throwing out ideas and I'm now realizing https://discourse.llvm.org/ would be a good place for this discussion. Feel free to reach out there if you'd like to talk about it more.

[ellis]

Refactor BCI a bit and add a more interesting test case in compiler-rt.

[spupyrev]

We reviewed the code internally prior sending upstream, and it is still looks good to me.

llvm/lib/Transforms/Instrumentation/BlockCoverageInference.cpp

180

I have seen in some places assertions of type

assert(condition && "readable text message");

Is this optional or the accepted style?

222

why predecessor? is this for determinism?

[ellis]

llvm/lib/Transforms/Instrumentation/BlockCoverageInference.cpp

180

I don't know if this is optional or not, so I'm open to either way.

I don't expect to ever hit this assert unless there is a bug, so a user should not encounter this assert. If the assert is hit, then we will need to look at and understand the source anyway and I'm not sure how much added value we get from a readable message here.

[ellis]

Improve comments, add more statistics, and remove the get() helper function.

[MaskRay]

(I plan to read this soon, and adding myself as a blocking reviewer.)

[ellis]

In D124490#3557619, @MaskRay wrote:

(I plan to read this soon, and adding myself as a blocking reviewer.)

Ah that makes sense, thanks!

[ellis]

llvm/lib/Transforms/Instrumentation/BlockCoverageInference.cpp

222

The predecessor was just an arbitrary choice.

On second thought, this logic is not really needed. The original idea was to have every non-instrumented node depend on either some of its predecessors or some of its successors. This aligns well with the theory, but in practice we don't think this is needed. This may result in a node's coverage depending on more nodes than necessary, but this should be fine. I will remove this logic.

[ellis]

Remove logic that enforced a non-instrumented node to either depend on its predecessors or successors, but not both. This logic was valid, but not necessary to produce a valid coverage instrumentation, so it was removed for simplicity.

Also, copy the interesting test case from compiler-rt to llvm. This allows us to more easily debug the complex test case in LLVM rather than compiler-rt.

[MaskRay]

llvm/include/llvm/Transforms/Instrumentation/BlockCoverageInference.h

16

LLVM_TRANSFORMS_INSTRUMENTATION_BLOCKCOVERAGEINFERENCE_H

llvm/lib/Transforms/Instrumentation/BlockCoverageInference.cpp

49

remove. see https://llvm.org/docs/CodingStandards.html#use-namespace-qualifiers-to-implement-previously-declared-functions

51

Use a reference for non-null.

delete assert(F)

58

https://llvm.org/docs/CodingStandards.html#prefer-preincrement

llvm/lib/Transforms/Instrumentation/PGOInstrumentation.cpp

273

Delete , cl::init(false)

[MaskRay]

If this new instrumentation mode is for coverage (non-optimization), why modify PGOUseFunc? If just to use PGOVerifyBFI, it doesn't justify modifying PGOInstrumentation. It would be cleaner to create a new file based on my current understanding.

llvm/include/llvm/Transforms/Instrumentation/BlockCoverageInference.h

80

llvm/lib/Transforms/Instrumentation/BlockCoverageInference.cpp

67

104

114

return F.size() == Visited.size()

121

130

BlockList is used only once. Remove using

132

This loop can be augmented with more info to include canFindMinimalCoverage, then just delete canFindMinimalCoverage

138

The time complexity is O(|BB|^2) and can be problematic.

146

llvm::any_of

200

return Path.count(Neighbors[0]) ? Neighbors[1] : Neighbors[0];

245

Use llvm::append_range

llvm/lib/Transforms/Instrumentation/PGOInstrumentation.cpp

1651

This can use a flood-fill instead of a fixed-point iteration.

[MaskRay]

llvm/lib/Transforms/Instrumentation/BlockCoverageInference.cpp

150

I have other things to do and haven't read very carefully, but the impl here appears to differ from the algorithm description in the summary.

Having a SuperReachable Pred does not mean that PredecessorDependencies[&BB] should remain empty.

[MaskRay]

llvm/lib/Transforms/Instrumentation/PGOInstrumentation.cpp

273

Also delete cl::ZeroOrMore. I have changed cl::opt that the option can be specified multiple times without an error.

[ellis]

In D124490#3558438, @MaskRay wrote:

If this new instrumentation mode is for coverage (non-optimization), why modify PGOUseFunc? If just to use PGOVerifyBFI, it doesn't justify modifying PGOInstrumentation. It would be cleaner to create a new file based on my current understanding.

Perhaps I should update the description to better explain how this diff is used for optimization. I will update it shortly.

In PGOUseFunc we populate edge weights such that BlockFrequencyInfo reports uncovered blocks as cold and covered blocks as hot. Obviously this will not be as precise as populating real edge weights from block counts, but this is a trade off from using extremely lightweight instrumented binaries. In the next diff D125743 we can take advantage of these imprecise profiles by using block coverage to guide the machine outliner. We have found this to work quite well at reducing binary size without harming runtime performance.

[ellis]

Make changes based on comments.

[ellis]

I am planning changes for now. We might have a simpler algorithm that uses dominator trees. It also runs in linear time, so it's more efficient than the current one.

llvm/lib/Transforms/Instrumentation/PGOInstrumentation.cpp

273

Nice 🙂

[ellis]

Rebase

[ellis]

Fix warning with Optional<BlockCoverageInference>

[ellis]

Add link to paper

[jmestre]

llvm/lib/Transforms/Instrumentation/BlockCoverageInference.cpp

150

As long as BB itself is reachable from EntryBlock, PredecessorDependencies should be non-empty whenever HasSuperReachablePred is true. Consider a simple path (i.e., there are no repeated nodes in the path) from EntryBlock to BB. Let Pred be the second to last node in this path. (Pred is well defined because HasSuperReachablePred is true implies BB != EntryBlock and so the path has at least one edge.) Then Pred belongs in RecheableFromEntry and so it will be added to PredecessorDependencies.
If it is desirable that the implementation handles functions with blocks that are not reachable from EntryBlock, then we can filter them out at the start and set their coverage status of these block to false right way.

[ellis]

Rebase and add comment discussing the runtime.

[ellis]

Can we get another review of this? CC @MaskRay

llvm/lib/Transforms/Instrumentation/BlockCoverageInference.cpp

138

I've added a comment discussing the runtime. We do know of a linear time algorithm that would compute the Dependencies maps, but it is significantly more complicated. We thought it would be best to first add this simpler implementation and in the future we can use the linear algorithm if we find that it gives a significant speedup in practice.

[ellis]

Friendly ping :)

[ellis]

Rebase.

llvm/lib/Transforms/Instrumentation/PGOInstrumentation.cpp

1651

I opted to use this algorithm for simplicity. Since most CFGs are relatively small, this function doesn't contribute too much to buildtime. If we discover that this causes a slowdown in some real world scenario then we can improve it. In fact, we can use info from the block coverage inference algorithm to infer all blocks in one pass. But again, this would add complexity and I would rather not do this unless we needed to.

[smeenai]

@MaskRay, were you still planning to review this/do you have any unaddressed concerns?

[ellis]

Rebase, use the std::optional() API, and initialize region counters for cover instructions as well as increment instructions.

[smeenai]

Ping @MaskRay. Have your blocking concerns been addressed?

[smeenai]

This comment was removed by smeenai.

[MaskRay]

In D124490#4146219, @smeenai wrote:

Ping @MaskRay. Have your blocking concerns been addressed?

Very sorry for missing these notifications! I'll read this patch soon...

[smeenai]

In D124490#4151517, @MaskRay wrote:

In D124490#4146219, @smeenai wrote:

Ping @MaskRay. Have your blocking concerns been addressed?

Very sorry for missing these notifications! I'll read this patch soon...

Thank you!

[MaskRay]

In BlockCoverageInference.cpp , for (auto &BB : F) { ... getReachableAvoiding is strictly quadratic and I think that may be problematic.
There are quite a few programs (e.g. Chisel genrerated C++) which contain functions with many basic blocks (say, >1000).
Also see D137184: a workaround for some programs with too many critical edges.

Applying a strict quadratic algorithm is a compile time pitfall. I understand that it may be fine for some mobile applications.
There are certainly other quadratic algorithms such as an O((V+E)*c) algorithm in GCC gcov (V: number of vertices; E: number of edges; c: number of elementary circuits),
an O(V^2) implementation of Semi-NCA algorithm.
For them, the quadratic time complexity is a theoretic upper bound which is really really difficult to achieve in practice (if ever achievable considering that in practice most CFGs are reducible).

Note that the optimality in the number of instrumented basic blocks is not required.
It does not necessarily lead to optimal performance since we have discarded execution count information.
Is it possible to use a faster algorithm which may instrument a few more basic blocks (let's arbitrarily say 1.2-approximation is good enough in practice)?

llvm/lib/Transforms/Instrumentation/BlockCoverageInference.cpp

112

Rename ExitBlocks: BB may end with an unreachable/resume/cleanupret/etc. I think we don't name them exit blocks.

138

We have quadratic time algorithms like O((V+E)(c+1)) used in gcov.

llvm/lib/Transforms/Instrumentation/PGOInstrumentation.cpp

1651

I think it's worth fixing it. A flood-fill algorithm is nearly of the same length and avoids the performance pitfall. That style is used much more than the iterative algorithm here.

1713

[ellis]

Use flood-fill algorithm to infer block coverage and rename some compiler-rt tests.

llvm/lib/Transforms/Instrumentation/BlockCoverageInference.cpp

112

Is TerminalBlocks a better name?

llvm/lib/Transforms/Instrumentation/PGOInstrumentation.cpp

1651

I've changes this to a flood-fill algorithm, but I needed to first compute InverseDependencies which is done in one pass.

[ellis]

llvm/lib/Transforms/Instrumentation/BlockCoverageInference.cpp

138

I haven't forgotten about this, I just wanted to resolve the other comments first.

[ellis]

In D124490#4153293, @MaskRay wrote:

In BlockCoverageInference.cpp , for (auto &BB : F) { ... getReachableAvoiding is strictly quadratic and I think that may be problematic.
There are quite a few programs (e.g. Chisel genrerated C++) which contain functions with many basic blocks (say, >1000).
Also see D137184: a workaround for some programs with too many critical edges.

Applying a strict quadratic algorithm is a compile time pitfall. I understand that it may be fine for some mobile applications.
There are certainly other quadratic algorithms such as an O((V+E)*c) algorithm in GCC gcov (V: number of vertices; E: number of edges; c: number of elementary circuits),
an O(V^2) implementation of Semi-NCA algorithm.
For them, the quadratic time complexity is a theoretic upper bound which is really really difficult to achieve in practice (if ever achievable considering that in practice most CFGs are reducible).

Note that the optimality in the number of instrumented basic blocks is not required.
It does not necessarily lead to optimal performance since we have discarded execution count information.
Is it possible to use a faster algorithm which may instrument a few more basic blocks (let's arbitrarily say 1.2-approximation is good enough in practice)?

We have analyzed the runtime on several real-world programs that have large functions with many basic blocks. We found that the total runtime of the pgo-instr-gen pass for functions with less than 1.5K blocks is less than 5 seconds. For functions with between 4K and 10K basic blocks, the runtime was 150 seconds to 850 seconds.

Note that the intended use case is to instrument minimal block coverage on binaries interested in minimizing binary size so that we can better control the machine outliner. Those binaries likely won't have functions this large because inlining is likely restricted to reduce code size. For those special cases where functions are large (say, >1.5K blocks), I'd like to bail on this algorithm and instead instrument every block. This will keep the code complexity down while preventing build time regressions for the pathological cases.

[ellis]

Bail if the function has >1.5K blocks.

[ellis]

Hi @MaskRay do you have any more concerns?

[kyulee]

This looks good to me as this change is effective even for large programs.
This good change has been sitting for a while. I think it would be beneficial for the community to have it, so I approve it.
I also suggest following up any concerns and feedbacks after it lands.

[smeenai]

In D124490#4230857, @kyulee wrote:

This looks good to me as this change is effective even for large programs.
This good change has been sitting for a while. I think it would be beneficial for the community to have it, so I approve it.
I also suggest following up any concerns and feedbacks after it lands.

Just to clarify, as far as I can tell, all other comments have been addressed, and the one remaining concern is around using a faster algorithm. I believe that concern is mitigated by applying the size cutoff. You could argue that having the linear algorithm is cleaner than having a quadratic one with a cutoff, but it sounds like the linear algorithm would be significantly more complex, which is also a trade-off. For the intended application, where being optimal for size is really important and you're unlikely to have a function large enough to hit the cutoff in practice, going with the simpler algorithm seems like a reasonable trade-off.

[ellis]

Rebase

compiler-rt/test/profile/instrprof-entry-coverage.c

+// RUN: %clang_pgogen -mllvm -pgo-block-coverage %s -o %t.out
+// RUN: env LLVM_PROFILE_FILE=%t1.profraw %run %t.out 1
+// RUN: env LLVM_PROFILE_FILE=%t2.profraw %run %t.out 2
+// RUN: llvm-profdata merge -o %t.profdata %t1.profraw %t2.profraw
+// RUN: %clang_profuse=%t.profdata -mllvm -pgo-verify-bfi -o - -S -emit-llvm %s 2>%t.errs | FileCheck %s --implicit-check-not="!prof"
+// RUN: FileCheck %s < %t.errs --allow-empty --check-prefix=CHECK-ERROR
+
+#include <stdlib.h>
+
+// CHECK: @foo({{.*}})
+// CHECK-SAME: !prof ![[PROF0:[0-9]+]]
+void foo(int a) {
+  // CHECK: br i1 %{{.*}}, label %{{.*}}, label %{{.*}}, !prof ![[PROF1:[0-9]+]]
+  if (a % 2 == 0) {
+    //
+  } else {
+    //
+  }
+
+  // CHECK: br i1 %{{.*}}, label %{{.*}}, label %{{.*}}, !prof ![[PROF1]]
+  for (int i = 1; i < a; i++) {
+    // CHECK: br i1 %{{.*}}, label %{{.*}}, label %{{.*}}, !prof ![[PROF2:[0-9]+]]
+    if (a % 3 == 0) {
+      //
+    } else {
+      // CHECK: br i1 %{{.*}}, label %{{.*}}, label %{{.*}}, !prof ![[PROF2]]
+      if (a % 1001 == 0) {
+        return;
+      }
+    }
+  }
+
+  return;
+}
+
+// CHECK: @main({{.*}})
+// CHECK-SAME: !prof ![[PROF0]]
+int main(int argc, char *argv[]) {
+  foo(atoi(argv[1]));
+  return 0;
+}
+
+// CHECK-DAG: ![[PROF0]] = !{!"function_entry_count", i64 10000}
+// CHECK-DAG: ![[PROF1]] = !{!"branch_weights", i32 1, i32 1}
+// CHECK-DAG: ![[PROF2]] = !{!"branch_weights", i32 0, i32 1}
+
+// CHECK-ERROR-NOT: warning: {{.*}}: Found inconsistent block coverage

llvm/include/llvm/Transforms/Instrumentation/BlockCoverageInference.h

+//===-- BlockCoverageInference.h - Minimal Execution Coverage ---*- C++ -*-===//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+///
+/// \file
+/// This file finds the minimum set of blocks on a CFG that must be instrumented
+/// to infer execution coverage for the whole graph.
+///
+//===----------------------------------------------------------------------===//
+
+#ifndef LLVM_TRANSFORMS_INSTRUMENTATION_BLOCKCOVERAGEINFERENCE_H
+#define LLVM_TRANSFORMS_INSTRUMENTATION_BLOCKCOVERAGEINFERENCE_H
+
+#include "llvm/ADT/ArrayRef.h"
+#include "llvm/ADT/DenseMap.h"
+#include "llvm/ADT/SetVector.h"
+
+namespace llvm {
+
+class Function;
+class BasicBlock;
+class DotFuncBCIInfo;
+
+class BlockCoverageInference {
+  friend class DotFuncBCIInfo;
+
+public:
+  using BlockSet = SmallSetVector<const BasicBlock *, 4>;
+
+  BlockCoverageInference(const Function &F, bool ForceInstrumentEntry);
+
+  /// \return true if \p BB should be instrumented for coverage.
+  bool shouldInstrumentBlock(const BasicBlock &BB) const;
+
+  /// \return the set of blocks such that \p BB is covered iff any of them are
+  /// covered.
+  BlockSet getDependencies(const BasicBlock &BB) const;
+
+  /// \return a hash that depends on the set of instrumented blocks.
+  uint64_t getInstrumentedBlocksHash() const;
+
+  /// Dump the inference graph.
+  void dump(raw_ostream &OS) const;
+
+  /// View the inferred block coverage as a dot file.
+  /// Filled gray blocks are instrumented, red outlined blocks are found to be
+  /// covered, red edges show that a block's coverage can be inferred from its
+  /// successors, and blue edges show that a block's coverage can be inferred
+  /// from its predecessors.
+  void viewBlockCoverageGraph(
+      const DenseMap<const BasicBlock *, bool> *Coverage = nullptr) const;
+
+private:
+  const Function &F;
+  bool ForceInstrumentEntry;
+
+  /// Maps blocks to a minimal list of predecessors that can be used to infer
+  /// this block's coverage.
+  DenseMap<const BasicBlock *, BlockSet> PredecessorDependencies;
+
+  /// Maps blocks to a minimal list of successors that can be used to infer
+  /// this block's coverage.
+  DenseMap<const BasicBlock *, BlockSet> SuccessorDependencies;
+
+  /// Compute \p PredecessorDependencies and \p SuccessorDependencies.
+  void findDependencies();
+
+  /// Find the set of basic blocks that are reachable from \p Start without the
+  /// basic block \p Avoid.
+  void getReachableAvoiding(const BasicBlock &Start, const BasicBlock &Avoid,
+                            bool IsForward, BlockSet &Reachable) const;
+
+  static std::string getBlockNames(ArrayRef<const BasicBlock *> BBs);
+  static std::string getBlockNames(BlockSet BBs) {
+    return getBlockNames(ArrayRef<const BasicBlock *>(BBs.begin(), BBs.end()));
+  }
+};
+
+} // end namespace llvm
+
+#endif // LLVM_TRANSFORMS_INSTRUMENTATION_BLOCKCOVERAGEINFERENCE_H

llvm/lib/Transforms/Instrumentation/BlockCoverageInference.cpp

+//===-- BlockCoverageInference.cpp - Minimal Execution Coverage -*- C++ -*-===//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+//
+// Our algorithm works by first identifying a subset of nodes that must always
+// be instrumented. We call these nodes ambiguous because knowing the coverage
+// of all remaining nodes is not enough to infer their coverage status.
+//
+// In general a node v is ambiguous if there exists two entry-to-terminal paths
+// P_1 and P_2 such that:
+//   1. v not in P_1 but P_1 visits a predecessor of v, and
+//   2. v not in P_2 but P_2 visits a successor of v.
+//
+// If a node v is not ambiguous, then if condition 1 fails, we can infer v’s
+// coverage from the coverage of its predecessors, or if condition 2 fails, we
+// can infer v’s coverage from the coverage of its successors.
+//
+// Sadly, there are example CFGs where it is not possible to infer all nodes
+// from the ambiguous nodes alone. Our algorithm selects a minimum number of
+// extra nodes to add to the ambiguous nodes to form a valid instrumentation S.
+//
+// Details on this algorithm can be found in https://arxiv.org/abs/2208.13907
+//
+//===----------------------------------------------------------------------===//
+
+#include "llvm/Transforms/Instrumentation/BlockCoverageInference.h"
+#include "llvm/ADT/DepthFirstIterator.h"
+#include "llvm/ADT/Statistic.h"
+#include "llvm/Support/CRC.h"
+#include "llvm/Support/Debug.h"
+#include "llvm/Support/GraphWriter.h"
+#include "llvm/Support/raw_ostream.h"
+#include "llvm/Transforms/Utils/BasicBlockUtils.h"
+
+using namespace llvm;
+
+#define DEBUG_TYPE "pgo-block-coverage"
+
+STATISTIC(NumFunctions, "Number of total functions that BCI has processed");
+STATISTIC(NumIneligibleFunctions,
+          "Number of functions for which BCI cannot run on");
+STATISTIC(NumBlocks, "Number of total basic blocks that BCI has processed");
+STATISTIC(NumInstrumentedBlocks,
+          "Number of basic blocks instrumented for coverage");
+
+BlockCoverageInference::BlockCoverageInference(const Function &F,
+                                               bool ForceInstrumentEntry)
+    : F(F), ForceInstrumentEntry(ForceInstrumentEntry) {
+  findDependencies();
+  assert(!ForceInstrumentEntry || shouldInstrumentBlock(F.getEntryBlock()));
+
+  ++NumFunctions;
+  for (auto &BB : F) {
+    ++NumBlocks;
+    if (shouldInstrumentBlock(BB))
+      ++NumInstrumentedBlocks;
+  }
+}
+
+BlockCoverageInference::BlockSet
+BlockCoverageInference::getDependencies(const BasicBlock &BB) const {
+  assert(BB.getParent() == &F);
+  BlockSet Dependencies;
+  auto It = PredecessorDependencies.find(&BB);
+  if (It != PredecessorDependencies.end())
+    Dependencies.set_union(It->second);
+  It = SuccessorDependencies.find(&BB);
+  if (It != SuccessorDependencies.end())
+    Dependencies.set_union(It->second);
+  return Dependencies;
+}
+
+uint64_t BlockCoverageInference::getInstrumentedBlocksHash() const {
+  JamCRC JC;
+  uint64_t Index = 0;
+  for (auto &BB : F) {
+    if (shouldInstrumentBlock(BB)) {
+      uint8_t Data[8];
+      support::endian::write64le(Data, Index);
+      JC.update(Data);
+    }
+    Index++;
+  }
+  return JC.getCRC();
+}
+
+bool BlockCoverageInference::shouldInstrumentBlock(const BasicBlock &BB) const {
+  assert(BB.getParent() == &F);
+  auto It = PredecessorDependencies.find(&BB);
+  if (It != PredecessorDependencies.end() && It->second.size())
+    return false;
+  It = SuccessorDependencies.find(&BB);
+  if (It != SuccessorDependencies.end() && It->second.size())
+    return false;
+  return true;
+}
+
+void BlockCoverageInference::findDependencies() {
+  assert(PredecessorDependencies.empty() && SuccessorDependencies.empty());
+  if (F.hasFnAttribute(Attribute::NoReturn)) {
+    ++NumIneligibleFunctions;
+    return;
+  }
+
+  SmallVector<const BasicBlock *, 4> ExitBlocks;
+  for (auto &BB : F)
+    if (succ_empty(&BB))
+      ExitBlocks.push_back(&BB);
+
+  // Traverse the CFG backwards from the exit blocks to make sure every block
+  // can reach some exit block. Otherwise this algorithm will not work and we
+  // must fall back to instrumenting every block.
+  df_iterator_default_set<const BasicBlock *> Visited;
+  for (auto *BB : ExitBlocks)
+    for (auto *N : inverse_depth_first_ext(BB, Visited))
+      (void)N;
+  if (F.size() != Visited.size()) {
+    ++NumIneligibleFunctions;
+    return;
+  }
+
+  // The current implementation for computing `PredecessorDependencies` and
+  // `SuccessorDependencies` runs in quadratic time with respect to the number
+  // of basic blocks. While we do have a more complicated linear time algorithm
+  // in https://arxiv.org/abs/2208.13907 we do not know if it will give a
+  // significant speedup in practice given that most functions tend to be
+  // relatively small in size.
+  auto &EntryBlock = F.getEntryBlock();
+  for (auto &BB : F) {
+    // The set of blocks that are reachable while avoiding BB.
+    BlockSet ReachableFromEntry, ReachableFromExit;
+    getReachableAvoiding(EntryBlock, BB, /*IsForward=*/true,
+                         ReachableFromEntry);
+    for (auto *ExitBlock : ExitBlocks)
+      getReachableAvoiding(*ExitBlock, BB, /*IsForward=*/false,
+                           ReachableFromExit);
+
+    auto Preds = predecessors(&BB);
+    bool HasSuperReachablePred = llvm::any_of(Preds, [&](auto *Pred) {
+      return ReachableFromEntry.count(Pred) && ReachableFromExit.count(Pred);
+    });
+    if (!HasSuperReachablePred)
+      for (auto *Pred : Preds)
+        if (ReachableFromEntry.count(Pred))
+          PredecessorDependencies[&BB].insert(Pred);
+
+    auto Succs = successors(&BB);
+    bool HasSuperReachableSucc = llvm::any_of(Succs, [&](auto *Succ) {
+      return ReachableFromEntry.count(Succ) && ReachableFromExit.count(Succ);
+    });
+    if (!HasSuperReachableSucc)
+      for (auto *Succ : Succs)
+        if (ReachableFromExit.count(Succ))
+          SuccessorDependencies[&BB].insert(Succ);
+  }
+
+  if (ForceInstrumentEntry) {
+    // Force the entry block to be instrumented by clearing the blocks it can
+    // infer coverage from.
+    PredecessorDependencies[&EntryBlock].clear();
+    SuccessorDependencies[&EntryBlock].clear();
+  }
+
+  // Construct a graph where blocks are connected if there is a mutual
+  // dependency between them. This graph has a special property that it contains
+  // only paths.
+  DenseMap<const BasicBlock *, BlockSet> AdjacencyList;
+  for (auto &BB : F) {
+    for (auto *Succ : successors(&BB)) {
+      if (SuccessorDependencies[&BB].count(Succ) &&
+          PredecessorDependencies[Succ].count(&BB)) {
+        AdjacencyList[&BB].insert(Succ);
+        AdjacencyList[Succ].insert(&BB);
+      }
+    }
+  }
+
+  // Given a path with at least one node, return the next node on the path.
+  auto getNextOnPath = [&](BlockSet &Path) -> const BasicBlock * {
+    assert(Path.size());
+    auto &Neighbors = AdjacencyList[Path.back()];
+    if (Path.size() == 1) {
+      // This is the first node on the path, return its neighbor.
+      assert(Neighbors.size() == 1);
+      return Neighbors.front();
+    } else if (Neighbors.size() == 2) {
+      // This is the middle of the path, find the neighbor that is not on the
+      // path already.
+      assert(Path.size() >= 2);
+      return Path.count(Neighbors[0]) ? Neighbors[1] : Neighbors[0];
+    }
+    // This is the end of the path.
+    assert(Neighbors.size() == 1);
+    return nullptr;
+  };
+
+  // Remove all cycles in the inferencing graph.
+  for (auto &BB : F) {
+    if (AdjacencyList[&BB].size() == 1) {
+      // We found the head of some path.
+      BlockSet Path;
+      Path.insert(&BB);
+      while (const BasicBlock *Next = getNextOnPath(Path))
+        Path.insert(Next);
+      LLVM_DEBUG(dbgs() << "Found path: " << getBlockNames(Path) << "\n");
+
+      // Remove these nodes from the graph so we don't discover this path again.
+      for (auto *BB : Path)
+        AdjacencyList[BB].clear();
+
+      // Finally, remove the cycles.
+      if (PredecessorDependencies[Path.front()].size()) {
+        for (auto *BB : Path)
+          if (BB != Path.back())
+            SuccessorDependencies[BB].clear();
+      } else {
+        for (auto *BB : Path)
+          if (BB != Path.front())
+            PredecessorDependencies[BB].clear();
+      }
+    }
+  }
+  LLVM_DEBUG(dump(dbgs()));
+}
+
+void BlockCoverageInference::getReachableAvoiding(const BasicBlock &Start,
+                                                  const BasicBlock &Avoid,
+                                                  bool IsForward,
+                                                  BlockSet &Reachable) const {
+  df_iterator_default_set<const BasicBlock *> Visited;
+  Visited.insert(&Avoid);
+  if (IsForward) {
+    auto Range = depth_first_ext(&Start, Visited);
+    Reachable.insert(Range.begin(), Range.end());
+  } else {
+    auto Range = inverse_depth_first_ext(&Start, Visited);
+    Reachable.insert(Range.begin(), Range.end());
+  }
+}
+
+namespace llvm {
+class DotFuncBCIInfo {
+private:
+  const BlockCoverageInference *BCI;
+  const DenseMap<const BasicBlock *, bool> *Coverage;
+
+public:
+  DotFuncBCIInfo(const BlockCoverageInference *BCI,
+                 const DenseMap<const BasicBlock *, bool> *Coverage)
+      : BCI(BCI), Coverage(Coverage) {}
+
+  const Function &getFunction() { return BCI->F; }
+
+  bool isInstrumented(const BasicBlock *BB) const {
+    return BCI->shouldInstrumentBlock(*BB);
+  }
+
+  bool isCovered(const BasicBlock *BB) const {
+    return Coverage && Coverage->lookup(BB);
+  }
+
+  bool isDependent(const BasicBlock *Src, const BasicBlock *Dest) const {
+    return BCI->getDependencies(*Src).count(Dest);
+  }
+};
+
+template <>
+struct GraphTraits<DotFuncBCIInfo *> : public GraphTraits<const BasicBlock *> {
+  static NodeRef getEntryNode(DotFuncBCIInfo *Info) {
+    return &(Info->getFunction().getEntryBlock());
+  }
+
+  // nodes_iterator/begin/end - Allow iteration over all nodes in the graph
+  using nodes_iterator = pointer_iterator<Function::const_iterator>;
+
+  static nodes_iterator nodes_begin(DotFuncBCIInfo *Info) {
+    return nodes_iterator(Info->getFunction().begin());
+  }
+
+  static nodes_iterator nodes_end(DotFuncBCIInfo *Info) {
+    return nodes_iterator(Info->getFunction().end());
+  }
+
+  static size_t size(DotFuncBCIInfo *Info) {
+    return Info->getFunction().size();
+  }
+};
+
+template <>
+struct DOTGraphTraits<DotFuncBCIInfo *> : public DefaultDOTGraphTraits {
+
+  DOTGraphTraits(bool IsSimple = false) : DefaultDOTGraphTraits(IsSimple) {}
+
+  static std::string getGraphName(DotFuncBCIInfo *Info) {
+    return "BCI CFG for " + Info->getFunction().getName().str();
+  }
+
+  std::string getNodeLabel(const BasicBlock *Node, DotFuncBCIInfo *Info) {
+    return Node->getName().str();
+  }
+
+  std::string getEdgeAttributes(const BasicBlock *Src, const_succ_iterator I,
+                                DotFuncBCIInfo *Info) {
+    const BasicBlock *Dest = *I;
+    if (Info->isDependent(Src, Dest))
+      return "color=red";
+    if (Info->isDependent(Dest, Src))
+      return "color=blue";
+    return "";
+  }
+
+  std::string getNodeAttributes(const BasicBlock *Node, DotFuncBCIInfo *Info) {
+    std::string Result;
+    if (Info->isInstrumented(Node))
+      Result += "style=filled,fillcolor=gray";
+    if (Info->isCovered(Node))
+      Result += std::string(Result.empty() ? "" : ",") + "color=red";
+    return Result;
+  }
+};
+
+} // namespace llvm
+
+void BlockCoverageInference::viewBlockCoverageGraph(
+    const DenseMap<const BasicBlock *, bool> *Coverage) const {
+  DotFuncBCIInfo Info(this, Coverage);
+  WriteGraph(&Info, "BCI", false,
+             "Block Coverage Inference for " + F.getName());
+}
+
+void BlockCoverageInference::dump(raw_ostream &OS) const {
+  OS << "Minimal block coverage for function \'" << F.getName()
+     << "\' (Instrumented=*)\n";
+  for (auto &BB : F) {
+    OS << (shouldInstrumentBlock(BB) ? "* " : "  ") << BB.getName() << "\n";
+    auto It = PredecessorDependencies.find(&BB);
+    if (It != PredecessorDependencies.end() && It->second.size())
+      OS << "    PredDeps = " << getBlockNames(It->second) << "\n";
+    It = SuccessorDependencies.find(&BB);
+    if (It != SuccessorDependencies.end() && It->second.size())
+      OS << "    SuccDeps = " << getBlockNames(It->second) << "\n";
+  }
+  OS << "  Instrumented Blocks Hash = 0x"
+     << Twine::utohexstr(getInstrumentedBlocksHash()) << "\n";
+}
+
+std::string
+BlockCoverageInference::getBlockNames(ArrayRef<const BasicBlock *> BBs) {
+  std::string Result;
+  raw_string_ostream OS(Result);
+  OS << "[";
+  if (!BBs.empty()) {
+    OS << BBs.front()->getName();
+    BBs = BBs.drop_front();
+  }
+  for (auto *BB : BBs)
+    OS << ", " << BB->getName();
+  OS << "]";
+  return OS.str();
+}

llvm/lib/Transforms/Instrumentation/CMakeLists.txt

 add_llvm_component_library(LLVMInstrumentation
   AddressSanitizer.cpp
   BoundsChecking.cpp
   CGProfile.cpp
   ControlHeightReduction.cpp
   DataFlowSanitizer.cpp
   GCOVProfiling.cpp
+  BlockCoverageInference.cpp
   MemProfiler.cpp
   MemorySanitizer.cpp
   IndirectCallPromotion.cpp
   Instrumentation.cpp
   InstrOrderFile.cpp
   InstrProfiling.cpp
   PGOInstrumentation.cpp
   PGOMemOPSizeOpt.cpp

llvm/lib/Transforms/Instrumentation/PGOInstrumentation.cpp

 #include "llvm/Support/DOTGraphTraits.h"
 #include "llvm/Support/Debug.h"
 #include "llvm/Support/Error.h"
 #include "llvm/Support/ErrorHandling.h"
 #include "llvm/Support/GraphWriter.h"
 #include "llvm/Support/HashBuilder.h"
 #include "llvm/Support/raw_ostream.h"
 #include "llvm/Transforms/Instrumentation.h"
+#include "llvm/Transforms/Instrumentation/BlockCoverageInference.h"
 #include "llvm/Transforms/Utils/BasicBlockUtils.h"
 #include "llvm/Transforms/Utils/MisExpect.h"
 #include "llvm/Transforms/Utils/ModuleUtils.h"
 #include <algorithm>
 #include <cassert>
 #include <cstdint>
 #include <map>
 #include <memory>

 STATISTIC(NumOfCSPGOEdge, "Number of edges in CSPGO.");
 STATISTIC(NumOfCSPGOBB, "Number of basic-blocks in CSPGO.");
 STATISTIC(NumOfCSPGOSplit, "Number of critical edge splits in CSPGO.");
 STATISTIC(NumOfCSPGOFunc,
           "Number of functions having valid profile counts in CSPGO.");
 STATISTIC(NumOfCSPGOMismatch,
           "Number of functions having mismatch profile in CSPGO.");
 STATISTIC(NumOfCSPGOMissing, "Number of functions without profile in CSPGO.");
+STATISTIC(NumCoveredBlocks, "Number of basic blocks that were executed");
 
 // Command line option to specify the file to read profile from. This is
 // mainly used for testing.
 static cl::opt<std::string>
     PGOTestProfileFile("pgo-test-profile-file", cl::init(""), cl::Hidden,
                        cl::value_desc("filename"),
                        cl::desc("Specify the path of profile data file. This is"
                                 "mainly for test purpose."));
static cl::opt<bool> PGOInstrumentEntry(
     "pgo-instrument-entry", cl::init(false), cl::Hidden,
     cl::desc("Force to instrument function entry basicblock."));
 
 static cl::opt<bool> PGOFunctionEntryCoverage(
     "pgo-function-entry-coverage", cl::Hidden,
     cl::desc(
         "Use this option to enable function entry coverage instrumentation."));
 
+static cl::opt<bool> PGOBlockCoverage(
+    "pgo-block-coverage",
+    cl::desc(
+        "Use this option to enable basic block coverage instrumentation."));
+
+static cl::opt<bool>
+    PGOViewBlockCoverageGraph("pgo-view-block-coverage-graph",
+                              cl::desc("Create a dot file of CFGs with block "
+                                       "coverage inference information."));
+
 static cl::opt<bool>
     PGOFixEntryCount("pgo-fix-entry-count", cl::init(true), cl::Hidden,
                      cl::desc("Fix function entry count in profile use."));
 
 static cl::opt<bool> PGOVerifyHotBFI(
     "pgo-verify-hot-bfi", cl::init(false), cl::Hidden,
     cl::desc("Print out the non-match BFI count if a hot raw profile count "
              "becomes non-hot, or a cold raw profile count becomes hot. "
if (IsCS)
     ProfileVersion |= VARIANT_MASK_CSIR_PROF;
   if (PGOInstrumentEntry)
     ProfileVersion |= VARIANT_MASK_INSTR_ENTRY;
   if (DebugInfoCorrelate)
     ProfileVersion |= VARIANT_MASK_DBG_CORRELATE;
   if (PGOFunctionEntryCoverage)
     ProfileVersion |=
         VARIANT_MASK_BYTE_COVERAGE | VARIANT_MASK_FUNCTION_ENTRY_ONLY;
+  if (PGOBlockCoverage)
+    ProfileVersion |= VARIANT_MASK_BYTE_COVERAGE;
   auto IRLevelVersionVariable = new GlobalVariable(
       M, IntTy64, true, GlobalValue::WeakAnyLinkage,
       Constant::getIntegerValue(IntTy64, APInt(64, ProfileVersion)), VarName);
   IRLevelVersionVariable->setVisibility(GlobalValue::DefaultVisibility);
   Triple TT(M.getTargetTriple());
   if (TT.supportsCOMDAT()) {
     IRLevelVersionVariable->setLinkage(GlobalValue::ExternalLinkage);
     IRLevelVersionVariable->setComdat(M.getOrInsertComdat(VarName));
struct SelectInstVisitor : public InstVisitor<SelectInstVisitor> {
   Function &F;
   unsigned NSIs = 0;             // Number of select instructions instrumented.
   VisitMode Mode = VM_counting;  // Visiting mode.
   unsigned *CurCtrIdx = nullptr; // Pointer to current counter index.
   unsigned TotalNumCtrs = 0;     // Total number of counters
   GlobalVariable *FuncNameVar = nullptr;
   uint64_t FuncHash = 0;
   PGOUseFunc *UseFunc = nullptr;
+  bool HasSingleByteCoverage;
 
-  SelectInstVisitor(Function &Func) : F(Func) {}
+  SelectInstVisitor(Function &Func, bool HasSingleByteCoverage)
+      : F(Func), HasSingleByteCoverage(HasSingleByteCoverage) {}
 
   void countSelects(Function &Func) {
     NSIs = 0;
     Mode = VM_counting;
     visit(Func);
   }
 
   // Visit the IR stream and instrument all select instructions. \p
public:
   GlobalVariable *FuncNameVar;
 
   // CFG hash value for this function.
   uint64_t FunctionHash = 0;
 
   // The Minimum Spanning Tree of function CFG.
   CFGMST<Edge, BBInfo> MST;
 
+  const Optional<BlockCoverageInference> BCI;
+
+  static Optional<BlockCoverageInference>
+  constructBCI(Function &Func, bool HasSingleByteCoverage,
+               bool InstrumentFuncEntry) {
+    if (HasSingleByteCoverage)
+      return BlockCoverageInference(Func, InstrumentFuncEntry);
+    return None;
+  }
+
   // Collect all the BBs that will be instrumented, and store them in
   // InstrumentBBs.
   void getInstrumentBBs(std::vector<BasicBlock *> &InstrumentBBs);
 
   // Give an edge, find the BB that will be instrumented.
   // Return nullptr if there is no BB to be instrumented.
   BasicBlock *getInstrBB(Edge *E);
 
MST.dumpEdges(dbgs(), Twine("Dump Function ") + FuncName + " Hash: " +
                               Twine(FunctionHash) + "\t" + Str);
   }
 
   FuncPGOInstrumentation(
       Function &Func, TargetLibraryInfo &TLI,
       std::unordered_multimap<Comdat *, GlobalValue *> &ComdatMembers,
       bool CreateGlobalVar = false, BranchProbabilityInfo *BPI = nullptr,
       BlockFrequencyInfo *BFI = nullptr, bool IsCS = false,
-      bool InstrumentFuncEntry = true)
+      bool InstrumentFuncEntry = true, bool HasSingleByteCoverage = false)
       : F(Func), IsCS(IsCS), ComdatMembers(ComdatMembers), VPC(Func, TLI),
-        TLI(TLI), ValueSites(IPVK_Last + 1), SIVisitor(Func),
-        MST(F, InstrumentFuncEntry, BPI, BFI) {
+        TLI(TLI), ValueSites(IPVK_Last + 1),
+        SIVisitor(Func, HasSingleByteCoverage),
+        MST(F, InstrumentFuncEntry, BPI, BFI),
+        BCI(constructBCI(Func, HasSingleByteCoverage, InstrumentFuncEntry)) {
+    if (BCI && PGOViewBlockCoverageGraph)
+      BCI->viewBlockCoverageGraph();
     // This should be done before CFG hash computation.
     SIVisitor.countSelects(Func);
     ValueSites[IPVK_MemOPSize] = VPC.get(IPVK_MemOPSize);
     if (!IsCS) {
       NumOfPGOSelectInsts += SIVisitor.getNumOfSelectInsts();
       NumOfPGOMemIntrinsics += ValueSites[IPVK_MemOPSize].size();
+      // FIXME: BBInfos include fake nodes which inflate this statistic.
       NumOfPGOBB += MST.BBInfos.size();
       ValueSites[IPVK_IndirectCallTarget] = VPC.get(IPVK_IndirectCallTarget);
     } else {
       NumOfCSPGOSelectInsts += SIVisitor.getNumOfSelectInsts();
       NumOfCSPGOMemIntrinsics += ValueSites[IPVK_MemOPSize].size();
       NumOfCSPGOBB += MST.BBInfos.size();
     }
 
if (PGOOldCFGHashing) {
     auto updateJCH = [&JCH](uint64_t Num) {
       uint8_t Data[8];
       support::endian::write64le(Data, Num);
       JCH.update(Data);
     };
     updateJCH((uint64_t)SIVisitor.getNumOfSelectInsts());
     updateJCH((uint64_t)ValueSites[IPVK_IndirectCallTarget].size());
     updateJCH((uint64_t)ValueSites[IPVK_MemOPSize].size());
+    if (BCI) {
+      updateJCH(BCI->getInstrumentedBlocksHash());
+    } else {
       updateJCH((uint64_t)MST.AllEdges.size());
+    }
 
     // Hash format for context sensitive profile. Reserve 4 bits for other
     // information.
     FunctionHash = (((uint64_t)JCH.getCRC()) << 28) + JC.getCRC();
   }
 
   // Reserve bit 60-63 for other information purpose.
   FunctionHash &= 0x0FFFFFFFFFFFFFFF;
void FuncPGOInstrumentation<Edge, BBInfo>::renameComdatFunction() {
   }
 }
 
 // Collect all the BBs that will be instruments and return them in
 // InstrumentBBs and setup InEdges/OutEdge for UseBBInfo.
 template <class Edge, class BBInfo>
 void FuncPGOInstrumentation<Edge, BBInfo>::getInstrumentBBs(
     std::vector<BasicBlock *> &InstrumentBBs) {
+  if (BCI) {
+    for (auto &BB : F)
+      if (BCI->shouldInstrumentBlock(BB))
+        InstrumentBBs.push_back(&BB);
+    return;
+  }
+
   // Use a worklist as we will update the vector during the iteration.
   std::vector<Edge *> EdgeList;
   EdgeList.reserve(MST.AllEdges.size());
   for (auto &E : MST.AllEdges)
     EdgeList.push_back(E.get());
 
   for (auto &E : EdgeList) {
     BasicBlock *InstrBB = getInstrBB(E);

 
 // Visit all edge and instrument the edges not in MST, and do value profiling.
 // Critical edges will be split.
 static void instrumentOneFunc(
     Function &F, Module *M, TargetLibraryInfo &TLI, BranchProbabilityInfo *BPI,
     BlockFrequencyInfo *BFI,
     std::unordered_multimap<Comdat *, GlobalValue *> &ComdatMembers,
     bool IsCS) {
+  if (!PGOBlockCoverage) {
     // Split indirectbr critical edges here before computing the MST rather than
     // later in getInstrBB() to avoid invalidating it.
     SplitIndirectBrCriticalEdges(F, /*IgnoreBlocksWithoutPHI=*/false, BPI, BFI);
+  }
 
   FuncPGOInstrumentation<PGOEdge, BBInfo> FuncInfo(
-      F, TLI, ComdatMembers, true, BPI, BFI, IsCS, PGOInstrumentEntry);
+      F, TLI, ComdatMembers, true, BPI, BFI, IsCS, PGOInstrumentEntry,
+      PGOBlockCoverage);
 
   Type *I8PtrTy = Type::getInt8PtrTy(M->getContext());
   auto Name = ConstantExpr::getBitCast(FuncInfo.FuncNameVar, I8PtrTy);
   auto CFGHash = ConstantInt::get(Type::getInt64Ty(M->getContext()),
                                   FuncInfo.FunctionHash);
   if (PGOFunctionEntryCoverage) {
     auto &EntryBB = F.getEntryBlock();
     IRBuilder<> Builder(&EntryBB, EntryBB.getFirstInsertionPt());
static void instrumentOneFunc(
   uint32_t I = 0;
   for (auto *InstrBB : InstrumentBBs) {
     IRBuilder<> Builder(InstrBB, InstrBB->getFirstInsertionPt());
     assert(Builder.GetInsertPoint() != InstrBB->end() &&
            "Cannot get the Instrumentation point");
     // llvm.instrprof.increment(i8* <name>, i64 <hash>, i32 <num-counters>,
     //                          i32 <index>)
     Builder.CreateCall(
-        Intrinsic::getDeclaration(M, Intrinsic::instrprof_increment),
+        Intrinsic::getDeclaration(M, PGOBlockCoverage
+                                         ? Intrinsic::instrprof_cover
+                                         : Intrinsic::instrprof_increment),
         {Name, CFGHash, Builder.getInt32(NumCounters), Builder.getInt32(I++)});
   }
 
   // Now instrument select instructions:
   FuncInfo.SIVisitor.instrumentSelects(F, &I, NumCounters, FuncInfo.FuncNameVar,
                                        FuncInfo.FunctionHash);
   assert(I == NumCounters);
 

 
 namespace {
 
 class PGOUseFunc {
 public:
   PGOUseFunc(Function &Func, Module *Modu, TargetLibraryInfo &TLI,
              std::unordered_multimap<Comdat *, GlobalValue *> &ComdatMembers,
              BranchProbabilityInfo *BPI, BlockFrequencyInfo *BFIin,
-             ProfileSummaryInfo *PSI, bool IsCS, bool InstrumentFuncEntry)
+             ProfileSummaryInfo *PSI, bool IsCS, bool InstrumentFuncEntry,
+             bool HasSingleByteCoverage)
       : F(Func), M(Modu), BFI(BFIin), PSI(PSI),
         FuncInfo(Func, TLI, ComdatMembers, false, BPI, BFIin, IsCS,
-                 InstrumentFuncEntry),
+                 InstrumentFuncEntry, HasSingleByteCoverage),
         FreqAttr(FFA_Normal), IsCS(IsCS) {}
 
+  void handleInstrProfError(Error Err, uint64_t MismatchedFuncSum);
+
   // Read counts for the instrumented BB from profile.
   bool readCounters(IndexedInstrProfReader *PGOReader, bool &AllZeros,
                     InstrProfRecord::CountPseudoKind &PseudoKind);
 
   // Read memprof data for the instrumented function from profile.
   bool readMemprof(IndexedInstrProfReader *PGOReader);
 
   // Populate the counts for all BBs.
   void populateCounters();
 
+  // Set block coverage based on profile coverage values.
+  void populateCoverage(IndexedInstrProfReader *PGOReader);
+
   // Set the branch weights based on the count values.
   void setBranchWeights();
 
   // Annotate the value profile call sites for all value kind.
   void annotateValueSites();
 
   // Annotate the value profile call sites for one value kind.
   void annotateValueSites(uint32_t Kind);
for (auto &I : BB) {
         }
       }
     }
   }
 
   return true;
 }
 
-// Read the profile from ProfileFileName and assign the value to the
-// instrumented BB and the edges. This function also updates ProgramMaxCount.
-// Return true if the profile are successfully read, and false on errors.
-bool PGOUseFunc::readCounters(IndexedInstrProfReader *PGOReader, bool &AllZeros,
-                              InstrProfRecord::CountPseudoKind &PseudoKind) {
+void PGOUseFunc::handleInstrProfError(Error Err, uint64_t MismatchedFuncSum) {
+  handleAllErrors(std::move(Err), [&](const InstrProfError &IPE) {
     auto &Ctx = M->getContext();
-  uint64_t MismatchedFuncSum = 0;
-  Expected<InstrProfRecord> Result = PGOReader->getInstrProfRecord(
-      FuncInfo.FuncName, FuncInfo.FunctionHash, &MismatchedFuncSum);
-  if (Error E = Result.takeError()) {
-    handleAllErrors(std::move(E), [&](const InstrProfError &IPE) {
-      auto Err = IPE.get();
-      bool SkipWarning = false;
-      LLVM_DEBUG(dbgs() << "Error in reading profile for Func "
-                        << FuncInfo.FuncName << ": ");
-      if (Err == instrprof_error::unknown_function) {
-        IsCS ? NumOfCSPGOMissing++ : NumOfPGOMissing++;
-        SkipWarning = !PGOWarnMissing;
-        LLVM_DEBUG(dbgs() << "unknown function");
-      } else if (Err == instrprof_error::hash_mismatch ||
-                 Err == instrprof_error::malformed) {
-        IsCS ? NumOfCSPGOMismatch++ : NumOfPGOMismatch++;
-        SkipWarning =
-            NoPGOWarnMismatch ||
-            (NoPGOWarnMismatchComdatWeak &&
-             (F.hasComdat() || F.getLinkage() == GlobalValue::WeakAnyLinkage ||
-              F.getLinkage() == GlobalValue::AvailableExternallyLinkage));
-        LLVM_DEBUG(dbgs() << "hash mismatch (hash= " << FuncInfo.FunctionHash
-                          << " skip=" << SkipWarning << ")");
-        // Emit function metadata indicating PGO profile mismatch.
-        annotateFunctionWithHashMismatch(F, M->getContext());
-      }
 
-      LLVM_DEBUG(dbgs() << " IsCS=" << IsCS << "\n");
-      if (SkipWarning)
-        return;
 
-      std::string Msg =
-          IPE.message() + std::string(" ") + F.getName().str() +
-          std::string(" Hash = ") + std::to_string(FuncInfo.FunctionHash) +
-          std::string(" up to ") + std::to_string(MismatchedFuncSum) +
-          std::string(" count discarded");
 
-      Ctx.diagnose(
-          DiagnosticInfoPGOProfile(M->getName().data(), Msg, DS_Warning));
-    });
+}
+
+// Read the profile from ProfileFileName and assign the value to the
+// instrumented BB and the edges. This function also updates ProgramMaxCount.
+// Return true if the profile are successfully read, and false on errors.
+bool PGOUseFunc::readCounters(IndexedInstrProfReader *PGOReader, bool &AllZeros,
+                              InstrProfRecord::CountPseudoKind &PseudoKind) {
+  auto &Ctx = M->getContext();
+  uint64_t MismatchedFuncSum = 0;
+  Expected<InstrProfRecord> Result = PGOReader->getInstrProfRecord(
+      FuncInfo.FuncName, FuncInfo.FunctionHash, &MismatchedFuncSum);
+  if (Error E = Result.takeError()) {
+    handleInstrProfError(std::move(E), MismatchedFuncSum);
     return false;
   }
   ProfileRecord = std::move(Result.get());
   PseudoKind = ProfileRecord.getCountPseudoKind();
   if (PseudoKind != InstrProfRecord::NotPseudo) {
     return true;
   }
   std::vector<uint64_t> &CountFromProfile = ProfileRecord.Counts;
Ctx.diagnose(DiagnosticInfoPGOProfile(
         + Twine(": the profile may be stale or there is a function name collision."),
         DS_Warning));
     return false;
   }
   ProgramMaxCount = PGOReader->getMaximumFunctionCount(IsCS);
   return true;
 }
 
+void PGOUseFunc::populateCoverage(IndexedInstrProfReader *PGOReader) {
+  uint64_t MismatchedFuncSum = 0;
+  Expected<InstrProfRecord> Result = PGOReader->getInstrProfRecord(
+      FuncInfo.FuncName, FuncInfo.FunctionHash, &MismatchedFuncSum);
+  if (auto Err = Result.takeError()) {
+    handleInstrProfError(std::move(Err), MismatchedFuncSum);
+    return;
+  }
+
+  std::vector<uint64_t> &CountsFromProfile = Result.get().Counts;
+  DenseMap<const BasicBlock *, bool> Coverage;
+  unsigned Index = 0;
+  for (auto &BB : F)
+    if (FuncInfo.BCI->shouldInstrumentBlock(BB))
+      Coverage[&BB] = (CountsFromProfile[Index++] != 0);
+  assert(Index == CountsFromProfile.size());
+
+  // Infer coverage of the non-instrumented blocks.
+  bool WasChanged = true;
+  while (WasChanged) {
+    WasChanged = false;
+    // It is possible to infer coverage in one pass, but the speedup might not
+    // be impactful for small CFGs.
+    for (auto &BB : F) {
+      if (Coverage.count(&BB))
+        continue;
+      for (auto *Dep : FuncInfo.BCI->getDependencies(BB)) {
+        if (Coverage.count(Dep) && Coverage[Dep]) {
+          Coverage[&BB] = true;
+          WasChanged = true;
+          continue;
+        }
+      }
+    }
+  }
+
+  // Annotate block coverage.
+  MDBuilder MDB(F.getContext());
+  // We set the entry count to 10000 if the entry block is covered so that BFI
+  // can propagate a fraction of this count to the other covered blocks.
+  F.setEntryCount(Coverage[&F.getEntryBlock()] ? 10000 : 0);
+  for (auto &BB : F) {
+    // For a block A and its successor B, we set the edge weight as follows:
+    // If A is covered and B is covered, set weight=1.
+    // If A is covered and B is uncovered, set weight=0.
+    // If A is uncovered, set weight=1.
+    // This setup will allow BFI to give nonzero profile counts to only covered
+    // blocks.
+    SmallVector<unsigned, 4> Weights;
+    for (auto *Succ : successors(&BB))
+      Weights.push_back((Coverage[Succ] || !Coverage[&BB]) ? 1 : 0);
+    if (Weights.size() >= 2)
+      BB.getTerminator()->setMetadata(LLVMContext::MD_prof,
+                                      MDB.createBranchWeights(Weights));
+  }
+
+  unsigned NumCorruptCoverage = 0;
+  DominatorTree DT(F);
+  LoopInfo LI(DT);
+  BranchProbabilityInfo BPI(F, LI);
+  BlockFrequencyInfo BFI(F, BPI, LI);
+  auto IsBlockDead = [&](const BasicBlock &BB) {
+    return BFI.getBlockProfileCount(&BB).transform(
+        [](auto C) { return C == 0; });
+  };
+  LLVM_DEBUG(dbgs() << "Block Coverage: (Instrumented=*, Covered=X)\n");
+  for (auto &BB : F) {
+    LLVM_DEBUG(dbgs() << (FuncInfo.BCI->shouldInstrumentBlock(BB) ? "* " : "  ")
+                      << (Coverage[&BB] ? "X " : "  ") << " " << BB.getName()
+                      << "\n");
+    // In some cases it is possible to find a covered block that has no covered
+    // successors, e.g., when a block calls a function that may call exit(). In
+    // those cases, BFI could find its successor to be covered while BCI could
+    // find its successor to be dead.
+    if (Coverage[&BB] == IsBlockDead(BB).value_or(false)) {
+      LLVM_DEBUG(
+          dbgs() << "Found inconsistent block covearge for " << BB.getName()
+                 << ": BCI=" << (Coverage[&BB] ? "Covered" : "Dead") << " BFI="
+                 << (IsBlockDead(BB).value() ? "Dead" : "Covered") << "\n");
+      NumCorruptCoverage++;
+    }
+    if (Coverage[&BB])
+      ++NumCoveredBlocks;
+  }
+  if (PGOVerifyBFI && NumCorruptCoverage) {
+    auto &Ctx = M->getContext();
+    Ctx.diagnose(DiagnosticInfoPGOProfile(
+        M->getName().data(),
+        Twine("Found inconsistent block coverage for function ") + F.getName() +
+            " in " + Twine(NumCorruptCoverage) + " blocks.",
+        DS_Warning));
+  }
+  if (PGOViewBlockCoverageGraph)
+    FuncInfo.BCI->viewBlockCoverageGraph(&Coverage);
+}
+
 // Populate the counters from instrumented BBs to all BBs.
 // In the end of this operation, all BBs should have a valid count value.
 void PGOUseFunc::populateCounters() {
   bool Changes = true;
   unsigned NumPasses = 0;
   while (Changes) {
     NumPasses++;
     Changes = false;
if (BFI->isIrrLoopHeader(&BB) || isIndirectBrTarget(&BB)) {
       Instruction *TI = BB.getTerminator();
       const UseBBInfo &BBCountInfo = getBBInfo(&BB);
       setIrrLoopHeaderMetadata(M, TI, BBCountInfo.CountValue);
     }
   }
 }
 
 void SelectInstVisitor::instrumentOneSelectInst(SelectInst &SI) {
-  if (PGOFunctionEntryCoverage)
-    return;
   Module *M = F.getParent();
   IRBuilder<> Builder(&SI);
   Type *Int64Ty = Builder.getInt64Ty();
   Type *I8PtrTy = Builder.getInt8PtrTy();
   auto *Step = Builder.CreateZExt(SI.getCondition(), Int64Ty);
   Builder.CreateCall(
       Intrinsic::getDeclaration(M, Intrinsic::instrprof_increment_step),
       {ConstantExpr::getBitCast(FuncNameVar, I8PtrTy),
void SelectInstVisitor::annotateOneSelectInst(SelectInst &SI) {
   // False Count
   SCounts[1] = (TotalCount > SCounts[0] ? TotalCount - SCounts[0] : 0);
   uint64_t MaxCount = std::max(SCounts[0], SCounts[1]);
   if (MaxCount)
     setProfMetadata(F.getParent(), &SI, SCounts, MaxCount);
 }
 
 void SelectInstVisitor::visitSelectInst(SelectInst &SI) {
-  if (!PGOInstrSelect)
+  // TODO: We can instrument coverage on selects by adding a new
+  // llvm.instrprof.cover.select intrinsic.
+  if (!PGOInstrSelect || PGOFunctionEntryCoverage || HasSingleByteCoverage)
     return;
   // FIXME: do not handle this yet.
   if (SI.getCondition()->getType()->isVectorTy())
     return;
 
   switch (Mode) {
   case VM_counting:
     NSIs++;
if (!PGOReader->hasCSIRLevelProfile() && IsCS)
     return false;
 
   // TODO: might need to change the warning once the clang option is finalized.
   if (!PGOReader->isIRLevelProfile() && !PGOReader->hasMemoryProfile()) {
     Ctx.diagnose(DiagnosticInfoPGOProfile(
         ProfileFileName.data(), "Not an IR level instrumentation profile"));
     return false;
   }
-  if (PGOReader->hasSingleByteCoverage()) {
-    Ctx.diagnose(DiagnosticInfoPGOProfile(
-        ProfileFileName.data(),
-        "Cannot use coverage profiles for optimization"));
-    return false;
-  }
   if (PGOReader->functionEntryOnly()) {
     Ctx.diagnose(DiagnosticInfoPGOProfile(
         ProfileFileName.data(),
         "Function entry profiles are not yet supported for optimization"));
     return false;
   }
 
   // Add the profile summary (read from the header of the indexed summary) here
static bool annotateAllFunctions(
   std::vector<Function *> HotFunctions;
   std::vector<Function *> ColdFunctions;
 
   // If the profile marked as always instrument the entry BB, do the
   // same. Note this can be overwritten by the internal option in CFGMST.h
   bool InstrumentFuncEntry = PGOReader->instrEntryBBEnabled();
   if (PGOInstrumentEntry.getNumOccurrences() > 0)
     InstrumentFuncEntry = PGOInstrumentEntry;
+  bool HasSingleByteCoverage = PGOReader->hasSingleByteCoverage();
   for (auto &F : M) {
     if (F.isDeclaration())
       continue;
     auto &TLI = LookupTLI(F);
     auto *BPI = LookupBPI(F);
     auto *BFI = LookupBFI(F);
-    // Split indirectbr critical edges here before computing the MST rather than
-    // later in getInstrBB() to avoid invalidating it.
-    SplitIndirectBrCriticalEdges(F, /*IgnoreBlocksWithoutPHI=*/false, BPI, BFI);
+    if (!HasSingleByteCoverage) {
+      // Split indirectbr critical edges here before computing the MST rather
+      // than later in getInstrBB() to avoid invalidating it.
+      SplitIndirectBrCriticalEdges(F, /*IgnoreBlocksWithoutPHI=*/false, BPI,
+                                   BFI);
+    }
     PGOUseFunc Func(F, &M, TLI, ComdatMembers, BPI, BFI, PSI, IsCS,
-                    InstrumentFuncEntry);
+                    InstrumentFuncEntry, HasSingleByteCoverage);
     // Read and match memprof first since we do this via debug info and can
     // match even if there is an IR mismatch detected for regular PGO below.
     if (PGOReader->hasMemoryProfile())
       Func.readMemprof(PGOReader.get());
 
     if (!PGOReader->isIRLevelProfile())
       continue;
 
+    if (HasSingleByteCoverage) {
+      Func.populateCoverage(PGOReader.get());
+      continue;
+    }
     // When PseudoKind is set to a vaule other than InstrProfRecord::NotPseudo,
     // it means the profile for the function is unrepresentative and this
     // function is actually hot / warm. We will reset the function hot / cold
     // attribute and drop all the profile counters.
     InstrProfRecord::CountPseudoKind PseudoKind = InstrProfRecord::NotPseudo;
     bool AllZeros = false;
     if (!Func.readCounters(PGOReader.get(), AllZeros, PseudoKind))
       continue;

llvm/test/Transforms/PGOProfile/coverage.ll

-; RUN: opt < %s -passes=pgo-instr-gen -pgo-function-entry-coverage -S | FileCheck %s
+; RUN: opt < %s -passes=pgo-instr-gen -pgo-function-entry-coverage -S | FileCheck %s --implicit-check-not="instrprof.cover" --check-prefixes=CHECK,ENTRY
+; RUN: opt < %s -passes=pgo-instr-gen -pgo-block-coverage -S | FileCheck %s --implicit-check-not="instrprof.cover" --check-prefixes=CHECK,BLOCK
 target datalayout = "e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-f80:128-n8:16:32:64-S128"
 target triple = "x86_64-unknown-linux-gnu"
 
-define i32 @foo(i32 %i) {
+define void @foo() {
+; CHECK-LABEL: entry:
 entry:
-  ; CHECK: call void @llvm.instrprof.cover({{.*}})
-  %cmp = icmp sgt i32 %i, 0
-  br i1 %cmp, label %if.then, label %if.else
+  ; ENTRY: call void @llvm.instrprof.cover({{.*}})
+  %c = call i1 @choice()
+  br i1 %c, label %if.then, label %if.else
 
+; CHECK-LABEL: if.then:
 if.then:
-  ; CHECK-NOT: llvm.instrprof.cover(
-  %add = add nsw i32 %i, 2
-  %s = select i1 %cmp, i32 %add, i32 0
+  ; BLOCK: call void @llvm.instrprof.cover({{.*}})
   br label %if.end
 
+; CHECK-LABEL: if.else:
 if.else:
-  %sub = sub nsw i32 %i, 2
+  ; BLOCK: call void @llvm.instrprof.cover({{.*}})
+  br label %if.end
+
+; CHECK-LABEL: if.end:
+if.end:
+  ret void
+}
+
+define void @bar() {
+; CHECK-LABEL: entry:
+entry:
+  ; ENTRY: call void @llvm.instrprof.cover({{.*}})
+  %c = call i1 @choice()
+  br i1 %c, label %if.then, label %if.end
+
+; CHECK-LABEL: if.then:
+if.then:
+  ; BLOCK: call void @llvm.instrprof.cover({{.*}})
   br label %if.end
 
+; CHECK-LABEL: if.end:
 if.end:
-  %retv = phi i32 [ %add, %if.then ], [ %sub, %if.else ]
-  ret i32 %retv
+  ; BLOCK: call void @llvm.instrprof.cover({{.*}})
+  ret void
+}
+
+define void @goo() {
+; CHECK-LABEL: entry:
+entry:
+  ; CHECK: call void @llvm.instrprof.cover({{.*}})
+  ret void
+}
+
+define void @loop() {
+; CHECK-LABEL: entry:
+entry:
+  ; CHECK: call void @llvm.instrprof.cover({{.*}})
+  br label %while
+while:
+  ; BLOCK: call void @llvm.instrprof.cover({{.*}})
+  br label %while
+}
+
+; Function Attrs: noinline nounwind ssp uwtable
+define void @hoo(i32 %a) #0 {
+; CHECK-LABEL: entry:
+entry:
+  ; ENTRY: call void @llvm.instrprof.cover({{.*}})
+  %a.addr = alloca i32, align 4
+  %i = alloca i32, align 4
+  store i32 %a, i32* %a.addr, align 4
+  %0 = load i32, i32* %a.addr, align 4
+  %rem = srem i32 %0, 2
+  %cmp = icmp eq i32 %rem, 0
+  br i1 %cmp, label %if.then, label %if.else
+
+; CHECK-LABEL: if.then:
+if.then:                                          ; preds = %entry
+  ; BLOCK: call void @llvm.instrprof.cover({{.*}})
+  br label %if.end
+
+; CHECK-LABEL: if.else:
+if.else:                                          ; preds = %entry
+  ; BLOCK: call void @llvm.instrprof.cover({{.*}})
+  br label %if.end
+
+; CHECK-LABEL: if.end:
+if.end:                                           ; preds = %if.else, %if.then
+  store i32 1, i32* %i, align 4
+  br label %for.cond
+
+; CHECK-LABEL: for.cond:
+for.cond:                                         ; preds = %for.inc, %if.end
+  %1 = load i32, i32* %i, align 4
+  %2 = load i32, i32* %a.addr, align 4
+  %cmp1 = icmp slt i32 %1, %2
+  br i1 %cmp1, label %for.body, label %for.end
+
+; CHECK-LABEL: for.body:
+for.body:                                         ; preds = %for.cond
+  %3 = load i32, i32* %a.addr, align 4
+  %rem2 = srem i32 %3, 3
+  %cmp3 = icmp eq i32 %rem2, 0
+  br i1 %cmp3, label %if.then4, label %if.else5
+
+; CHECK-LABEL: if.then4:
+if.then4:                                         ; preds = %for.body
+  ; BLOCK: call void @llvm.instrprof.cover({{.*}})
+  br label %if.end10
+
+; CHECK-LABEL: if.else5:
+if.else5:                                         ; preds = %for.body
+  %4 = load i32, i32* %a.addr, align 4
+  %rem6 = srem i32 %4, 1001
+  %cmp7 = icmp eq i32 %rem6, 0
+  br i1 %cmp7, label %if.then8, label %if.end9
+
+; CHECK-LABEL: if.then8:
+if.then8:                                         ; preds = %if.else5
+  ; BLOCK: call void @llvm.instrprof.cover({{.*}})
+  br label %return
+
+; CHECK-LABEL: if.end9:
+if.end9:                                          ; preds = %if.else5
+  ; BLOCK: call void @llvm.instrprof.cover({{.*}})
+  br label %if.end10
+
+; CHECK-LABEL: if.end10:
+if.end10:                                         ; preds = %if.end9, %if.then4
+  br label %for.inc
+
+; CHECK-LABEL: for.inc:
+for.inc:                                          ; preds = %if.end10
+  %5 = load i32, i32* %i, align 4
+  %inc = add nsw i32 %5, 1
+  store i32 %inc, i32* %i, align 4
+  br label %for.cond
+
+; CHECK-LABEL: for.end:
+for.end:                                          ; preds = %for.cond
+  ; BLOCK: call void @llvm.instrprof.cover({{.*}})
+  br label %return
+
+; CHECK-LABEL: return:
+return:                                           ; preds = %for.end, %if.then8
+  ret void
 }
 
-; CHECK: declare void @llvm.instrprof.cover(
+declare i1 @choice()
+
+; CHECK: declare void @llvm.instrprof.cover({{.*}})