Add async dependencies support for gpu.launch op

[bondhugula]

Summary

Add async dependencies support for gpu.launch op: this allows specifying
a list of async tokens ("streams") as dependencies for the launch.

Update the GPU kernel outlining pass lowering to propagate async
dependencies from gpu.launch to gpu.launch_func op. Previously, a new
stream was being created and destroyed for a kernel launch. The async
deps support allows the kernel launch to be serialized on an existing
stream.

[csigg]

Not opposed to this change at all, but what's the motivation for allowing gpu-async-region to run before gpu-kernel-outlining?

[bondhugula]

Some cleanup.

[bondhugula]

Update commit summary.

[bondhugula]

In D123499#3442565, @csigg wrote:

Not opposed to this change at all, but what's the motivation for allowing gpu-async-region to run before gpu-kernel-outlining?

I didn't know that pass existed! Do let me know if that approach subsumes or is more canonical/systematic than this one. I guess if a user wishes to explicitly specify which streams the kernels should be part of and how they should be ordered/overlapped, they could go with not attaching aysnc deps on gpu.launch and let gpu-async-region mark them async with deps. If they wanted full control, they would specify these. So, there is still motivation for running gpu-async-region before gpu-kernel-outlining in pipelines -- but could I know which pipeline/use case you were referring to?

On a separate note, at least with NVIDIA GPUs, aren't all kernel launches always asynchronous (w.r.t host)? What does it mean to not mark a gpu.launch_func async?! Does the GPU dialect leave that unspecified (target-dependent)?

[csigg]

The gpu-async-region pass simply chains together sequences of gpu ops, with the intention of using async.execute to separate independent work that runs on separate streams. For that case, gpu ops can be synchronous during lowering from higher dialects because the async.execute regions specify which gpu ops should run in sequence and which ones can run in parallel.

But you are right, users might want to set dependencies though tokens manually, and might want to do that before lowering from gpu.launch to gpu.launch_func.

On a separate note, at least with NVIDIA GPUs, aren't all kernel launches always asynchronous (w.r.t host)? What does it mean to not mark a gpu.launch_func async?! Does the GPU dialect leave that unspecified (target-dependent)?

A gpu.launch_func without async implies that it is synchronous (same for gpu.memset, gpu.memcpy etc). If the lowering to the gpu runtime wouldn't reject it, it would need to insert a mgpuStreamSynchronize call.

[bondhugula]

In D123499#3442878, @csigg wrote:

A gpu.launch_func without async implies that it is synchronous (same for gpu.memset, gpu.memcpy etc). If the lowering to the gpu runtime wouldn't reject it, it would need to insert a mgpuStreamSynchronize call.

I see -- it's been made "synchronous" as a result of the synchronize call inserted below. This makes sense to me - thanks. But in that case, async with 0 async dep tokens wouldn't appear to be a meaningful configuration for the op. The lowering does check for it and fails, but should it just be disallowed? For the support in this PR, I'm not adding a result token to the op if no async deps have been specified (even if the async keyword is specified, it's dropped during the print). It should perhaps be a parse error and similarly for the launch_func op?

[bondhugula]

Add AsyncOpInterface to gpu.launch and move common methods in GPUDialect.cpp up.

[bondhugula]

Sorted order.

[csigg]

async with 0 async dep tokens wouldn't appear to be a meaningful configuration for the op. The lowering does check for it and fails, but should it just be disallowed?

I'm not sure. I would say the semantics are clear if an op uses async (the host does not wait for the op to complete) but no dependencies (it can run immediately without waiting for anything else), and it's OK for the current lowering to be limited in what it can handle and rely on gpu-async-region to bring it into lowering-compatible form. I kind of like the symmetry of these ops (including gpu.wait, where gpu.wait async [] needs to be valid).

For the support in this PR, I'm not adding a result token to the op if no async deps have been specified (even if the async keyword is specified, it's dropped during the print). It should perhaps be a parse error and similarly for the launch_func op?

I don't think this is a good idea. The 'async' keyword stands for the !gpu.async.token return type and should really be independent of the token operands inside []. I would not infer the former from the latter, but fail verification (for all but gpu.wait) if we want that.

[mehdi_amini]

In D123499#3445734, @csigg wrote:

For the support in this PR, I'm not adding a result token to the op if no async deps have been specified (even if the async keyword is specified, it's dropped during the print).

I don't understand what you're describing: you don't get to control the number of output of the operation, this is parsed by MLIR before your custom parser and if you don't provide a result type matching the number of result MLIR will fatal_error() anyway.

[bondhugula]

In D123499#3445734, @csigg wrote:

async with 0 async dep tokens wouldn't appear to be a meaningful configuration for the op. The lowering does check for it and fails, but should it just be disallowed?

I'm not sure. I would say the semantics are clear if an op uses async (the host does not wait for the op to complete) but no dependencies (it can run immediately without waiting for anything else), and it's OK for the current lowering to be limited in what it can handle and rely on gpu-async-region to bring it into lowering-compatible form. I kind of like the symmetry of these ops (including gpu.wait, where gpu.wait async [] needs to be valid).

This makes sense to me.

For the support in this PR, I'm not adding a result token to the op if no async deps have been specified (even if the async keyword is specified, it's dropped during the print). It should perhaps be a parse error and similarly for the launch_func op?

I don't think this is a good idea. The 'async' keyword stands for the !gpu.async.token return type and should really be independent of the token operands inside []. I would not infer the former from the latter, but fail verification (for all but gpu.wait) if we want that.

This makes sense to me too -- follows from the previous para. I'll update the revision to make sure there is a meaning to the "async" keyword (regardless of the tokens) in that it returns a token indicating async execution.

[bondhugula]

In D123499#3447326, @mehdi_amini wrote:

In D123499#3445734, @csigg wrote:

For the support in this PR, I'm not adding a result token to the op if no async deps have been specified (even if the async keyword is specified, it's dropped during the print).

I don't understand what you're describing: you don't get to control the number of output of the operation, this is parsed by MLIR before your custom parser and if you don't provide a result type matching the number of result MLIR will fatal_error() anyway.

I meant "adding a result type". A single result type will be added if there is an async keyword. Why would it be a fatal error instead of a parse error, which it should be if a user provided a number of results on the LHS that are inconsistent with the expected number?

[mehdi_amini]

In D123499#3447834, @bondhugula wrote:

In D123499#3447326, @mehdi_amini wrote:

In D123499#3445734, @csigg wrote:

For the support in this PR, I'm not adding a result token to the op if no async deps have been specified (even if the async keyword is specified, it's dropped during the print).

I don't understand what you're describing: you don't get to control the number of output of the operation, this is parsed by MLIR before your custom parser and if you don't provide a result type matching the number of result MLIR will fatal_error() anyway.

I meant "adding a result type". A single result type will be added if there is an async keyword. Why would it be a fatal error instead of a parse error, which it should be if a user provided a number of results on the LHS that are inconsistent with the expected number?

Right it'll be a parse error

[bondhugula]

Fix semantics and syntax to allow async without any deps.

[bondhugula]

In D123499#3447805, @bondhugula wrote:

In D123499#3445734, @csigg wrote:

For the support in this PR, I'm not adding a result token to the op if no async deps have been specified (even if the async keyword is specified, it's dropped during the print). It should perhaps be a parse error and similarly for the launch_func op?

I don't think this is a good idea. The 'async' keyword stands for the !gpu.async.token return type and should really be independent of the token operands inside []. I would not infer the former from the latter, but fail verification (for all but gpu.wait) if we want that.

This makes sense to me too -- follows from the previous para. I'll update the revision to make sure there is a meaning to the "async" keyword (regardless of the tokens) in that it returns a token indicating async execution.

Done and addressed. I've updated the doc comment as well. @csigg, this is ready for review now.

[bondhugula]

Missed updates for gpu.launch -> gpu.launch_func.

[bondhugula]

Add a couple more test cases for the outlining pass.

[bondhugula]

Any more comments here @csigg ?

[bondhugula]

Rebase.

[csigg]

mlir/lib/Dialect/GPU/IR/GPUDialect.cpp

486

Isn't this checked elsewhere already? Also, the error messages refers to the 'async dependencies' instead of the 'async keyword'.

[bondhugula]

Adjust error message.

[bondhugula]

mlir/lib/Dialect/GPU/IR/GPUDialect.cpp

486

Adjusted the error message to refer to 'async keyword'. This isn't checked anywhere else (not in any automatically generated verifier hooks); we check for this during (custom) parsing, but the verifier needs to separately check for it as well.

mlir/include/mlir/Dialect/GPU/GPUOps.td

let description = [{
     ```
   }];
 
   let skipDefaultBuilders = 1;
 
   let builders = [
     OpBuilder<(ins "GPUFuncOp":$kernelFunc, "KernelDim3":$gridSize,
       "KernelDim3":$blockSize, "Value":$dynamicSharedMemorySize,
-      "ValueRange":$kernelOperands)>
+      "ValueRange":$kernelOperands,
+      CArg<"Type", "nullptr">:$asyncTokenType,
+      CArg<"ValueRange", "{}">:$asyncDependencies)>
   ];
 
   let extraClassDeclaration = [{
     /// The number of operands passed to the kernel function.
     unsigned getNumKernelOperands();
 
     /// The name of the kernel's containing module.
     StringAttr getKernelModuleName();
let assemblyFormat = [{
       `blocks` `in` ` ` `(`$gridSizeX`,` $gridSizeY`,` $gridSizeZ`)`
       `threads` `in` ` ` `(`$blockSizeX`,` $blockSizeY`,` $blockSizeZ`)`
       (`dynamic_shared_memory_size` $dynamicSharedMemorySize^)?
       custom<LaunchFuncOperands>($operands, type($operands)) attr-dict
   }];
   let hasVerifier = 1;
 }
 
-def GPU_LaunchOp : GPU_Op<"launch", [AutomaticAllocationScope]>,
-    Arguments<(ins Index:$gridSizeX, Index:$gridSizeY, Index:$gridSizeZ,
+def GPU_LaunchOp : GPU_Op<"launch",
+    [AutomaticAllocationScope, AttrSizedOperandSegments, GPU_AsyncOpInterface]>,
+    Arguments<(ins Variadic<GPU_AsyncToken>:$asyncDependencies,
+               Index:$gridSizeX, Index:$gridSizeY, Index:$gridSizeZ,
                Index:$blockSizeX, Index:$blockSizeY, Index:$blockSizeZ,
                Optional<I32>:$dynamicSharedMemorySize)>,
-    Results<(outs)> {
+    Results<(outs Optional<GPU_AsyncToken>:$asyncToken)> {
   let summary = "GPU kernel launch operation";
 
   let description = [{
     Launch a kernel on the specified grid of thread blocks. The body of the
     kernel is defined by the single region that this operation contains. The
-    operation takes six operands followed by an optional operand: the first
-    three operands are grid sizes along the x,y,z dimensions and the following
-    three are block sizes along the x,y,z dimensions. The last operand is
-    optional and corresponds to the amount of dynamic shared memory a kernel's
-    workgroup should be allocated; when this operand is not present, a zero size
-    is assumed.
+    operation takes an optional list of async dependencies followed by six
+    operands and an optional operand.
 
-    When a lower-dimensional kernel is required, unused sizes must
-    be explicitly set to `1`.
+    The `async` keyword indicates the kernel should be launched asynchronously;
+    the operation returns a new !gpu.async.token when the keyword is specified.
+    The kernel launched does not start executing until the ops producing its
+    async dependencies (optional operands) have completed.
+
+    The first three operands (following any async dependencies) are grid sizes
+    along the x,y,z dimensions and the following three are block sizes along the
+    x,y,z dimensions. When a lower-dimensional kernel is required, unused sizes
+    must be explicitly set to `1`.  The last operand is optional and corresponds
+    to the amount of dynamic shared memory a kernel's workgroup should be
+    allocated; when this operand is not present, a zero size is assumed.
 
     The body region has _twelve_ arguments, grouped as follows:
 
     -   three arguments that contain block identifiers along x,y,z dimensions;
     -   three arguments that contain thread identifiers along x,y,z dimensions;
     -   operands of the `gpu.launch` operation as is (i.e. the operands for
         grid and block sizes).
 
     Syntax:
 
     ```
-    operation ::= `gpu.launch` `block` `(` ssa-id-list `)` `in` ssa-reassignment
+    operation ::= `gpu.launch` (`async` (`[` ssa-id-list `]`)? )?
+                             `block` `(` ssa-id-list `)` `in` ssa-reassignment
                              `threads` `(` ssa-id-list `)` `in` ssa-reassignment
                              (dynamic_shared_memory_size ssa-use)?
                              region attr-dict?
     ssa-reassignment ::= `(` ssa-id `=` ssa-use (`,` ssa-id `=` ssa-use)* `)`
     ```
 
     Example:
 
def GPU_LaunchOp : GPU_Op<"launch",
   let regions = (region AnyRegion:$body);
 
   let skipDefaultBuilders = 1;
 
   let builders = [
     OpBuilder<(ins "Value":$gridSizeX, "Value":$gridSizeY,
       "Value":$gridSizeZ, "Value":$blockSizeX, "Value":$blockSizeY,
       "Value":$blockSizeZ,
-      CArg<"Value", "nullptr">:$dynamic_shared_memory_size)>
+      CArg<"Value", "nullptr">:$dynamicSharedMemorySize,
+      CArg<"Type", "nullptr">:$asyncTokenType,
+      CArg<"ValueRange", "{}">:$asyncDependencies)>
   ];
 
   let extraClassDeclaration = [{
     /// Get the SSA values corresponding to kernel block identifiers.
     KernelDim3 getBlockIds();
     /// Get the SSA values corresponding to kernel thread identifiers.
     KernelDim3 getThreadIds();
     /// Get the SSA values corresponding to kernel grid size.

mlir/lib/Dialect/GPU/IR/GPUDialect.cpp

auto walkResult = module.walk([&module](LaunchFuncOp launchOp) -> WalkResult {
     }
 
     return success();
   });
 
   return walkResult.wasInterrupted() ? failure() : success();
 }
 
+/// Parses an optional list of async operands.
+/// (`async` `[` ssa-id-list `]`)?
+///
+/// This method is used by the tablegen assembly format for async ops as well.
+static ParseResult parseAsyncDependencies(
+    OpAsmParser &parser, Type &asyncTokenType,
+    SmallVectorImpl<OpAsmParser::UnresolvedOperand> &asyncDependencies) {
+  auto loc = parser.getCurrentLocation();
+  if (succeeded(parser.parseOptionalKeyword("async"))) {
+    if (parser.getNumResults() == 0)
+      return parser.emitError(loc, "needs to be named when marked 'async'");
+    asyncTokenType = parser.getBuilder().getType<AsyncTokenType>();
+  }
+  return parser.parseOperandList(asyncDependencies,
+                                 OpAsmParser::Delimiter::OptionalSquare);
+}
+
+// Used by the tablegen assembly format for several async ops.
+static void printAsyncDependencies(OpAsmPrinter &printer, Operation *op,
+                                   Type asyncTokenType,
+                                   OperandRange asyncDependencies) {
+  if (asyncTokenType)
+    printer << "async ";
+  if (asyncDependencies.empty())
+    return;
+  printer << '[';
+  llvm::interleaveComma(asyncDependencies, printer);
+  printer << ']';
+}
+
+//===----------------------------------------------------------------------===//
+// AllReduceOp
+//===----------------------------------------------------------------------===//
+
 LogicalResult gpu::AllReduceOp::verifyRegions() {
   if (body().empty() != op().hasValue())
     return emitError("expected either an op attribute or a non-empty body");
   if (!body().empty()) {
     if (body().getNumArguments() != 2)
       return emitError("expected two region arguments");
     for (auto argument : body().getArguments()) {
       if (argument.getType() != getType())

 
 //===----------------------------------------------------------------------===//
 // LaunchOp
 //===----------------------------------------------------------------------===//
 
 void LaunchOp::build(OpBuilder &builder, OperationState &result,
                      Value gridSizeX, Value gridSizeY, Value gridSizeZ,
                      Value blockSizeX, Value blockSizeY, Value blockSizeZ,
-                     Value dynamicSharedMemorySize) {
+                     Value dynamicSharedMemorySize, Type asyncTokenType,
+                     ValueRange asyncDependencies) {
+  result.addOperands(asyncDependencies);
+  if (asyncTokenType)
+    result.types.push_back(builder.getType<AsyncTokenType>());
+
   // Add grid and block sizes as op operands, followed by the data operands.
   result.addOperands(
       {gridSizeX, gridSizeY, gridSizeZ, blockSizeX, blockSizeY, blockSizeZ});
   if (dynamicSharedMemorySize)
     result.addOperands(dynamicSharedMemorySize);
 
   // Create a kernel body region with kNumConfigRegionAttributes + N arguments,
   // where the first kNumConfigRegionAttributes arguments have `index` type and
   // the rest have the same types as the data operands.
   Region *kernelRegion = result.addRegion();
   Block *body = new Block();
   for (unsigned i = 0; i < kNumConfigRegionAttributes; ++i)
     body->addArgument(builder.getIndexType(), result.location);
   kernelRegion->push_back(body);
+  SmallVector<int32_t, 8> segmentSizes(8, 1);
+  segmentSizes.front() = asyncDependencies.size();
+  segmentSizes.back() = dynamicSharedMemorySize ? 1 : 0;
+  result.addAttribute(getOperandSegmentSizeAttr(),
+                      builder.getI32VectorAttr(segmentSizes));
 }
 
 KernelDim3 LaunchOp::getBlockIds() {
   assert(!body().empty() && "LaunchOp body must not be empty.");
   auto args = body().getArguments();
   return KernelDim3{args[0], args[1], args[2]};
 }
 

 
 KernelDim3 LaunchOp::getBlockSize() {
   assert(!body().empty() && "LaunchOp body must not be empty.");
   auto args = body().getArguments();
   return KernelDim3{args[9], args[10], args[11]};
 }
 
 KernelDim3 LaunchOp::getGridSizeOperandValues() {
-  return KernelDim3{getOperand(0), getOperand(1), getOperand(2)};
+  auto operands = getOperands().drop_front(asyncDependencies().size());
+  return KernelDim3{operands[0], operands[1], operands[2]};
 }
 
 KernelDim3 LaunchOp::getBlockSizeOperandValues() {
-  return KernelDim3{getOperand(3), getOperand(4), getOperand(5)};
+  auto operands = getOperands().drop_front(asyncDependencies().size());
+  return KernelDim3{operands[3], operands[4], operands[5]};
 }
 
 LogicalResult LaunchOp::verifyRegions() {
   // Kernel launch takes kNumConfigOperands leading operands for grid/block
   // sizes and transforms them into kNumConfigRegionAttributes region arguments
   // for block/thread identifiers and grid/block sizes.
   if (!body().empty()) {
-    if (body().getNumArguments() != LaunchOp::kNumConfigOperands +
-                                        getNumOperands() -
-                                        (dynamicSharedMemorySize() ? 1 : 0))
+    if (body().getNumArguments() !=
+        LaunchOp::kNumConfigOperands + getNumOperands() -
+            (dynamicSharedMemorySize() ? 1 : 0) - asyncDependencies().size())
       return emitOpError("unexpected number of region arguments");
   }
 
   // Block terminators without successors are expected to exit the kernel region
   // and must be `gpu.terminator`.
   for (Block &block : body()) {
     if (block.empty())
       continue;
     if (block.back().getNumSuccessors() != 0)
       continue;
     if (!isa<gpu::TerminatorOp>(&block.back())) {
       return block.back()
           .emitError()
           .append("expected '", gpu::TerminatorOp::getOperationName(),
                   "' or a terminator with successors")
           .attachNote(getLoc())
           .append("in '", LaunchOp::getOperationName(), "' body region");
     }
   }
 
+  if (getNumResults() == 0 && asyncToken())
+    return emitOpError(
+        "needs to be named when async dependencies are specified");
+
   return success();
 }
 
 // Pretty-print the kernel grid/block size assignment as
 //   (%iter-x, %iter-y, %iter-z) in
 //   (%size-x = %ssa-use, %size-y = %ssa-use, %size-z = %ssa-use)
 // where %size-* and %iter-* will correspond to the body region arguments.
 static void printSizeAssignment(OpAsmPrinter &p, KernelDim3 size,
                                 KernelDim3 operands, KernelDim3 ids) {
   p << '(' << ids.x << ", " << ids.y << ", " << ids.z << ") in (";
   p << size.x << " = " << operands.x << ", ";
   p << size.y << " = " << operands.y << ", ";
   p << size.z << " = " << operands.z << ')';
 }
 
 void LaunchOp::print(OpAsmPrinter &p) {
+  if (asyncToken()) {
+    p << " async";
+    if (!asyncDependencies().empty())
+      p << " [" << asyncDependencies() << ']';
+  }
   // Print the launch configuration.
   p << ' ' << getBlocksKeyword();
   printSizeAssignment(p, getGridSize(), getGridSizeOperandValues(),
                       getBlockIds());
   p << ' ' << getThreadsKeyword();
   printSizeAssignment(p, getBlockSize(), getBlockSizeOperandValues(),
                       getThreadIds());
   if (dynamicSharedMemorySize())
     p << ' ' << getDynamicSharedMemorySizeKeyword() << ' '
       << dynamicSharedMemorySize();
 
   p << ' ';
   p.printRegion(body(), /*printEntryBlockArgs=*/false);
-  p.printOptionalAttrDict((*this)->getAttrs());
+  p.printOptionalAttrDict((*this)->getAttrs(), /*elidedAttrs=*/{
+                              LaunchOp::getOperandSegmentSizeAttr()});
 }
 
 // Parse the size assignment blocks for blocks and threads.  These have the form
 //   (%region_arg, %region_arg, %region_arg) in
 //   (%region_arg = %operand, %region_arg = %operand, %region_arg = %operand)
 // where %region_arg are percent-identifiers for the region arguments to be
 // introduced further (SSA defs), and %operand are percent-identifiers for the
 // SSA value uses.
if (parser.parseRegionArgument(regionSizes[i]) || parser.parseEqual() ||
         parser.parseOperand(sizes[i]))
       return failure();
   }
 
   return parser.parseRParen();
 }
 
 /// Parses a Launch operation.
-/// operation ::= `gpu.launch` `blocks` `(` ssa-id-list `)` `in`
-/// ssa-reassignment
-///                           `threads` `(` ssa-id-list `)` `in`
-///                           ssa-reassignment
-///                            region attr-dict?
+/// operation ::= `gpu.launch` (`async` `[` ssa-id-list `]`)?
+//        `blocks` `(` ssa-id-list `)` `in` ssa-reassignment
+///       `threads` `(` ssa-id-list `)` `in` ssa-reassignment
+///       region attr-dict?
 /// ssa-reassignment ::= `(` ssa-id `=` ssa-use (`,` ssa-id `=` ssa-use)* `)`
 ParseResult LaunchOp::parse(OpAsmParser &parser, OperationState &result) {
   // Sizes of the grid and block.
   SmallVector<OpAsmParser::UnresolvedOperand, LaunchOp::kNumConfigOperands>
       sizes(LaunchOp::kNumConfigOperands);
   MutableArrayRef<OpAsmParser::UnresolvedOperand> sizesRef(sizes);
 
   // Actual (data) operands passed to the kernel.
   SmallVector<OpAsmParser::UnresolvedOperand, 4> dataOperands;
 
   // Region arguments to be created.
   SmallVector<OpAsmParser::UnresolvedOperand, 16> regionArgs(
       LaunchOp::kNumConfigRegionAttributes);
   MutableArrayRef<OpAsmParser::UnresolvedOperand> regionArgsRef(regionArgs);
 
+  // Parse optional async dependencies.
+  SmallVector<OpAsmParser::UnresolvedOperand, 4> asyncDependencies;
+  Type asyncTokenType;
+  if (failed(
+          parseAsyncDependencies(parser, asyncTokenType, asyncDependencies)) ||
+      parser.resolveOperands(asyncDependencies, asyncTokenType,
+                             result.operands))
+    return failure();
+  if (parser.getNumResults() > 0)
+    result.types.push_back(asyncTokenType);
+
   // Parse the size assignment segments: the first segment assigns grid sizes
   // and defines values for block identifiers; the second segment assigns block
   // sizes and defines values for thread identifiers.  In the region argument
   // list, identifiers precede sizes, and block-related values precede
   // thread-related values.
   if (parser.parseKeyword(LaunchOp::getBlocksKeyword().data()) ||
       parseSizeAssignment(parser, sizesRef.take_front(3),
                           regionArgsRef.slice(6, 3),
                           regionArgsRef.slice(0, 3)) ||
       parser.parseKeyword(LaunchOp::getThreadsKeyword().data()) ||
       parseSizeAssignment(parser, sizesRef.drop_front(3),
                           regionArgsRef.slice(9, 3),
                           regionArgsRef.slice(3, 3)) ||
       parser.resolveOperands(sizes, parser.getBuilder().getIndexType(),
                              result.operands))
     return failure();
 
   OpAsmParser::UnresolvedOperand dynamicSharedMemorySize;
+  bool hasDynamicSharedMemorySize = false;
   if (!parser.parseOptionalKeyword(
-          LaunchOp::getDynamicSharedMemorySizeKeyword()))
+          LaunchOp::getDynamicSharedMemorySizeKeyword())) {
+    hasDynamicSharedMemorySize = true;
     if (parser.parseOperand(dynamicSharedMemorySize) ||
         parser.resolveOperand(dynamicSharedMemorySize,
                               parser.getBuilder().getI32Type(),
                               result.operands))
       return failure();
+  }
 
   // Introduce the body region and parse it. The region has
   // kNumConfigRegionAttributes arguments that correspond to
   // block/thread identifiers and grid/block sizes, all of the `index` type.
   Type index = parser.getBuilder().getIndexType();
   SmallVector<Type, LaunchOp::kNumConfigRegionAttributes> dataTypes(
       LaunchOp::kNumConfigRegionAttributes, index);
   Region *body = result.addRegion();
-  return failure(parser.parseRegion(*body, regionArgs, dataTypes) ||
-                 parser.parseOptionalAttrDict(result.attributes));
+  if (parser.parseRegion(*body, regionArgs, dataTypes) ||
+      parser.parseOptionalAttrDict(result.attributes))
+    return failure();
+
+  SmallVector<int32_t, 8> segmentSizes(8, 1);
+  segmentSizes.front() = asyncDependencies.size();
+  segmentSizes.back() = hasDynamicSharedMemorySize ? 1 : 0;
+  result.addAttribute(LaunchOp::getOperandSegmentSizeAttr(),
+                      parser.getBuilder().getI32VectorAttr(segmentSizes));
+  return success();
 }
 
 /// Simplify the gpu.launch when the range of a thread or block ID is
 /// trivially known to be one.
 struct FoldLaunchArguments : public OpRewritePattern<LaunchOp> {
   using OpRewritePattern<LaunchOp>::OpRewritePattern;
   LogicalResult matchAndRewrite(LaunchOp op,
                                 PatternRewriter &rewriter) const override {

 
 //===----------------------------------------------------------------------===//
 // LaunchFuncOp
 //===----------------------------------------------------------------------===//
 
 void LaunchFuncOp::build(OpBuilder &builder, OperationState &result,
                          GPUFuncOp kernelFunc, KernelDim3 gridSize,
                          KernelDim3 blockSize, Value dynamicSharedMemorySize,
-                         ValueRange kernelOperands) {
+                         ValueRange kernelOperands, Type asyncTokenType,
+                         ValueRange asyncDependencies) {
+  result.addOperands(asyncDependencies);
+  if (asyncTokenType)
+    result.types.push_back(builder.getType<AsyncTokenType>());
+
   // Add grid and block sizes as op operands, followed by the data operands.
   result.addOperands({gridSize.x, gridSize.y, gridSize.z, blockSize.x,
                       blockSize.y, blockSize.z});
   if (dynamicSharedMemorySize)
     result.addOperands(dynamicSharedMemorySize);
   result.addOperands(kernelOperands);
   auto kernelModule = kernelFunc->getParentOfType<GPUModuleOp>();
   auto kernelSymbol =
       SymbolRefAttr::get(kernelModule.getNameAttr(),
                          {SymbolRefAttr::get(kernelFunc.getNameAttr())});
   result.addAttribute(getKernelAttrName(), kernelSymbol);
   SmallVector<int32_t, 9> segmentSizes(9, 1);
-  segmentSizes.front() = 0; // Initially no async dependencies.
+  segmentSizes.front() = asyncDependencies.size();
   segmentSizes[segmentSizes.size() - 2] = dynamicSharedMemorySize ? 1 : 0;
   segmentSizes.back() = static_cast<int32_t>(kernelOperands.size());
   result.addAttribute(getOperandSegmentSizeAttr(),
                       builder.getI32VectorAttr(segmentSizes));
 }
 
 unsigned LaunchFuncOp::getNumKernelOperands() {
   return getNumOperands() - asyncDependencies().size() - kNumConfigOperands -
if (getElementTypeOrSelf(srcType) != getElementTypeOrSelf(dstType))
     return emitOpError("arguments have incompatible element type");
 
   if (failed(verifyCompatibleShape(srcType, dstType)))
     return emitOpError("arguments have incompatible shape");
 
   return success();
 }
 
-static ParseResult parseAsyncDependencies(
-    OpAsmParser &parser, Type &asyncTokenType,
-    SmallVectorImpl<OpAsmParser::UnresolvedOperand> &asyncDependencies) {
-  auto loc = parser.getCurrentLocation();
-  if (succeeded(parser.parseOptionalKeyword("async"))) {
-    if (parser.getNumResults() == 0)
-      return parser.emitError(loc, "needs to be named when marked 'async'");
-    asyncTokenType = parser.getBuilder().getType<AsyncTokenType>();
-  }
-  return parser.parseOperandList(asyncDependencies,
-                                 OpAsmParser::Delimiter::OptionalSquare);
-}
-
-static void printAsyncDependencies(OpAsmPrinter &printer, Operation *op,
-                                   Type asyncTokenType,
-                                   OperandRange asyncDependencies) {
-  if (asyncTokenType)
-    printer << "async ";
-  if (asyncDependencies.empty())
-    return;
-  printer << "[";
-  llvm::interleaveComma(asyncDependencies, printer);
-  printer << "]";
-}
-
 //===----------------------------------------------------------------------===//
 // GPU_SubgroupMmaLoadMatrixOp
 //===----------------------------------------------------------------------===//
 
 /// Return true if the last dimension of the MemRefType has unit stride. Also
 /// return true for memrefs with no strides.
 static bool isLastMemrefDimUnitStride(MemRefType type) {
   int64_t offset;

mlir/lib/Dialect/GPU/Transforms/KernelOutlining.cpp

 /// launching `kernelFunc`. The kernel func contains the body of the
 /// `gpu.launch` with constant region arguments inlined.
 static void convertToLaunchFuncOp(gpu::LaunchOp launchOp,
                                   gpu::GPUFuncOp kernelFunc,
                                   ValueRange operands) {
   OpBuilder builder(launchOp);
   // The launch op has an optional dynamic shared memory size. If it doesn't
   // exist, we use zero.
-  builder.create<gpu::LaunchFuncOp>(
+  Value asyncToken = launchOp.asyncToken();
+  auto launchFunc = builder.create<gpu::LaunchFuncOp>(
       launchOp.getLoc(), kernelFunc, launchOp.getGridSizeOperandValues(),
       launchOp.getBlockSizeOperandValues(), launchOp.dynamicSharedMemorySize(),
-      operands);
+      operands, asyncToken ? asyncToken.getType() : nullptr,
+      launchOp.asyncDependencies());
+  launchOp.replaceAllUsesWith(launchFunc);
   launchOp.erase();
 }
 
 namespace {
 /// Pass that moves ops which are likely an index computation into gpu.launch
 /// body.
 class GpuLaunchSinkIndexComputationsPass
     : public GpuLaunchSinkIndexComputationsBase<

mlir/test/Dialect/GPU/invalid.mlir

 // RUN: mlir-opt -split-input-file -verify-diagnostics %s
 
 func @not_enough_sizes(%sz : index) {
   // expected-error@+1 {{expected 6 or more operands, but found 5}}
   "gpu.launch"(%sz, %sz, %sz, %sz, %sz) ({
     gpu.return
-  }) : (index, index, index, index, index) -> ()
+  }) {operand_segment_sizes = dense<[0, 1, 1, 1, 1, 1, 1, 0]> : vector<8xi32>} : (index, index, index, index, index) -> ()
   return
 }
 
 // -----
 
 func @no_region_attrs(%sz : index) {
   // expected-error@+1 {{unexpected number of region arguments}}
   "gpu.launch"(%sz, %sz, %sz, %sz, %sz, %sz) ({
   ^bb1(%bx: index, %by: index, %bz: index,
        %tx: index, %ty: index, %tz: index):
     gpu.terminator
-  }) : (index, index, index, index, index, index) -> ()
+  }) {operand_segment_sizes = dense<[0, 1, 1, 1, 1, 1, 1, 0]> : vector<8xi32>} : (index, index, index, index, index, index) -> ()
   return
 }
 
 // -----
 
 func @launch_requires_gpu_return(%sz : index) {
   // @expected-note@+1 {{in 'gpu.launch' body region}}
   gpu.launch blocks(%bx, %by, %bz) in (%sbx = %sz, %sby = %sz, %sbz = %sz)

mlir/test/Dialect/GPU/ops.mlir

 // RUN: mlir-opt -allow-unregistered-dialect %s | FileCheck %s
+// Verify the printed output can be parsed.
+// RUN: mlir-opt -allow-unregistered-dialect %s | mlir-opt -allow-unregistered-dialect | FileCheck %s
+// Verify the generic form can be parsed.
+// RUN: mlir-opt -allow-unregistered-dialect -mlir-print-op-generic %s | mlir-opt -allow-unregistered-dialect | FileCheck %s
 
 module attributes {gpu.container_module} {
 
   // CHECK-LABEL:func @no_args(%{{.*}}: index)
   func @no_args(%sz : index) {
     // CHECK: gpu.launch blocks(%{{.*}}, %{{.*}}, %{{.*}}) in (%{{.*}} = %{{.*}}, %{{.*}} = %{{.*}}, %{{.*}} = %{{.*}}) threads(%{{.*}}, %{{.*}}, %{{.*}}) in (%{{.*}} = %{{.*}}, %{{.*}} = %{{.*}}, %{{.*}} = %{{.*}})
     gpu.launch blocks(%bx, %by, %bz) in (%grid_x = %sz, %grid_y = %sz, %grid_z = %sz)
                threads(%tx, %ty, %tz) in (%block_x = %sz, %block_y = %sz, %block_z = %sz) {
gpu.launch blocks(%bx, %by, %bz) in (%grid_x = %blk, %grid_y = %blk, %grid_z = %blk)
       "use"(%float) : (f32) -> ()
       "use"(%data) : (memref<?xf32,1>) -> ()
       // CHECK: gpu.terminator
       gpu.terminator
     }
     return
   }
 
+  // CHECK-LABEL:func @launch_async(%{{.*}}: index, %{{.*}}: index) {
+  func @launch_async(%blk : index, %thrd : index) {
+    // CHECK: gpu.launch async [%{{.+}}] blocks(%{{.*}}, %{{.*}}, %{{.*}}) in (%{{.*}} = %{{.*}}, %{{.*}} = %{{.*}}, %{{.*}} = %{{.*}}) threads(%{{.*}}, %{{.*}}, %{{.*}}) in (%{{.*}} = %{{.*}}, %{{.*}} = %{{.*}}, %{{.*}} = %{{.*}})
+    %t = gpu.wait async
+    %name = gpu.launch async [%t] blocks(%arg0, %arg1, %arg2) in (%grid_x = %blk, %grid_y = %blk, %grid_z = %blk)
+               threads(%arg3, %arg4, %arg5) in (%block_x = %thrd, %block_y = %thrd, %block_z = %thrd) {
+      gpu.terminator
+    }
+    return
+  }
+
+  // CHECK-LABEL:func @launch_async_no_deps(%{{.*}}: index, %{{.*}}: index) {
+  func @launch_async_no_deps(%blk : index, %thrd : index) {
+    // CHECK: %{{.*}} = gpu.launch async blocks(%{{.*}}, %{{.*}}, %{{.*}}) in (%{{.*}} = %{{.*}}, %{{.*}} = %{{.*}}, %{{.*}} = %{{.*}}) threads(%{{.*}}, %{{.*}}, %{{.*}}) in (%{{.*}} = %{{.*}}, %{{.*}} = %{{.*}}, %{{.*}} = %{{.*}})
+    %t0 = gpu.launch async blocks(%arg0, %arg1, %arg2) in (%grid_x = %blk, %grid_y = %blk, %grid_z = %blk)
+               threads(%arg3, %arg4, %arg5) in (%block_x = %thrd, %block_y = %thrd, %block_z = %thrd) {
+      gpu.terminator
+    }
+    // CHECK: gpu.launch async blocks(%{{.*}}, %{{.*}}, %{{.*}}) in (%{{.*}} = %{{.*}}, %{{.*}} = %{{.*}}, %{{.*}} = %{{.*}}) threads(%{{.*}}, %{{.*}}, %{{.*}}) in (%{{.*}} = %{{.*}}, %{{.*}} = %{{.*}}, %{{.*}} = %{{.*}})
+    %t1 = gpu.launch async [] blocks(%arg0, %arg1, %arg2) in (%grid_x = %blk, %grid_y = %blk, %grid_z = %blk)
+               threads(%arg3, %arg4, %arg5) in (%block_x = %thrd, %block_y = %thrd, %block_z = %thrd) {
+      gpu.terminator
+    }
+    return
+  }
+
   gpu.module @kernels {
     gpu.func @kernel_1(%arg0 : f32, %arg1 : memref<?xf32, 1>) kernel {
       %tIdX = gpu.thread_id x
       %tIdY = gpu.thread_id y
       %tIdZ = gpu.thread_id z
 
       %bDimX = gpu.block_dim x
       %bDimY = gpu.block_dim y

mlir/test/Dialect/GPU/outlining.mlir

func @multiple_launches() {
   }
   // CHECK: gpu.launch_func @multiple_launches_kernel_0::@multiple_launches_kernel blocks in (%[[CST]], %[[CST]], %[[CST]]) threads in (%[[CST]], %[[CST]], %[[CST]])
   gpu.launch blocks(%bx2, %by2, %bz2) in (%grid_x2 = %cst, %grid_y2 = %cst,
                                           %grid_z2 = %cst)
              threads(%tx2, %ty2, %tz2) in (%block_x2 = %cst, %block_y2 = %cst,
                                            %block_z2 = %cst) {
     gpu.terminator
   }
+
+  // With async and async deps.
+  // CHECK: %[[TOKEN:.*]] = gpu.wait async
+  // CHECK: gpu.launch_func async [%[[TOKEN]]] @multiple_launches_kernel_1::@multiple_launches_kernel blocks in (%[[CST]], %[[CST]], %[[CST]]) threads in (%[[CST]], %[[CST]], %[[CST]])
+  %t = gpu.wait async
+  %u = gpu.launch async [%t] blocks(%bx2, %by2, %bz2) in (%grid_x2 = %cst, %grid_y2 = %cst,
+                                          %grid_z2 = %cst)
+             threads(%tx2, %ty2, %tz2) in (%block_x2 = %cst, %block_y2 = %cst,
+                                           %block_z2 = %cst) {
+    gpu.terminator
+  }
+
+  // CHECK: gpu.launch_func async @multiple_launches_kernel_2::@multiple_launches_kernel blocks in (%[[CST]], %[[CST]], %[[CST]]) threads in (%[[CST]], %[[CST]], %[[CST]])
+  %v = gpu.launch async blocks(%bx2, %by2, %bz2) in (%grid_x2 = %cst, %grid_y2 = %cst,
+                                     %grid_z2 = %cst)
+             threads(%tx2, %ty2, %tz2) in (%block_x2 = %cst, %block_y2 = %cst,
+                                           %block_z2 = %cst) {
+    gpu.terminator
+  }
+
   return
 }
 
 // CHECK-DL-LABEL: gpu.module @multiple_launches_kernel attributes {dlti.dl_spec = #dlti.dl_spec<#dlti.dl_entry<index, 32 : i32>>}
 // CHECK-DL-LABEL: gpu.module @multiple_launches_kernel_0 attributes {dlti.dl_spec = #dlti.dl_spec<#dlti.dl_entry<index, 32 : i32>>}
 
 // CHECK: gpu.module @multiple_launches_kernel
 // CHECK: func @multiple_launches_kernel