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[flang][cuda] Convert gpu.launch_func with result (#137231)

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We cannot use `replaceOp` because the newly created operation has not
the same number of results.
This commit is contained in:
Valentin Clement (バレンタイン クレメン)
2025-04-24 12:13:30 -07:00
committed by GitHub
parent 7cce38beea
commit c8dc3ed9c4
2 changed files with 30 additions and 4 deletions
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10
flang/lib/Optimizer/Transforms/CUFGPUToLLVMConversion.cpp
View File

@@ -147,14 +147,15 @@ struct GPULaunchKernelConversion
stream = adaptor.getAsyncDependencies().front();
}
rewriter.replaceOpWithNewOp<mlir::LLVM::CallOp>(
op, funcTy, cufLaunchClusterKernel,
rewriter.create<mlir::LLVM::CallOp>(
loc, funcTy, cufLaunchClusterKernel,
mlir::ValueRange{kernelPtr, adaptor.getClusterSizeX(),
adaptor.getClusterSizeY(), adaptor.getClusterSizeZ(),
adaptor.getGridSizeX(), adaptor.getGridSizeY(),
adaptor.getGridSizeZ(), adaptor.getBlockSizeX(),
adaptor.getBlockSizeY(), adaptor.getBlockSizeZ(),
stream, dynamicMemorySize, kernelArgs, nullPtr});
rewriter.eraseOp(op);
} else {
auto procAttr =
op->getAttrOfType<cuf::ProcAttributeAttr>(cuf::getProcAttrName());
@@ -189,13 +190,14 @@ struct GPULaunchKernelConversion
stream = adaptor.getAsyncDependencies().front();
}
rewriter.replaceOpWithNewOp<mlir::LLVM::CallOp>(
op, funcTy, cufLaunchKernel,
rewriter.create<mlir::LLVM::CallOp>(
loc, funcTy, cufLaunchKernel,
mlir::ValueRange{kernelPtr, adaptor.getGridSizeX(),
adaptor.getGridSizeY(), adaptor.getGridSizeZ(),
adaptor.getBlockSizeX(), adaptor.getBlockSizeY(),
adaptor.getBlockSizeZ(), stream, dynamicMemorySize,
kernelArgs, nullPtr});
rewriter.eraseOp(op);
}
return mlir::success();

24
flang/test/Fir/CUDA/cuda-gpu-launch-func.mlir
View File

@@ -229,3 +229,27 @@ module attributes {dlti.dl_spec = #dlti.dl_spec<#dlti.dl_entry<i1, dense<8> : ve
// CHECK-LABEL: llvm.func @_QMmod1Phost_sub()
// CHECK: %[[STREAM:.*]] = llvm.alloca %{{.*}} x i64 : (i64) -> !llvm.ptr
// CHECK: llvm.call @_FortranACUFLaunchCooperativeKernel(%{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[STREAM]], %{{.*}}, %{{.*}}, %{{.*}}) : (!llvm.ptr, i64, i64, i64, i64, i64, i64, !llvm.ptr, i32, !llvm.ptr, !llvm.ptr) -> ()
// -----
module attributes {dlti.dl_spec = #dlti.dl_spec<#dlti.dl_entry<!llvm.ptr<272>, dense<64> : vector<4xi64>>, #dlti.dl_entry<!llvm.ptr, dense<64> : vector<4xi64>>, #dlti.dl_entry<i64, dense<64> : vector<2xi64>>, #dlti.dl_entry<!llvm.ptr<270>, dense<32> : vector<4xi64>>, #dlti.dl_entry<!llvm.ptr<271>, dense<32> : vector<4xi64>>, #dlti.dl_entry<f64, dense<64> : vector<2xi64>>, #dlti.dl_entry<f128, dense<128> : vector<2xi64>>, #dlti.dl_entry<f16, dense<16> : vector<2xi64>>, #dlti.dl_entry<i32, dense<32> : vector<2xi64>>, #dlti.dl_entry<f80, dense<128> : vector<2xi64>>, #dlti.dl_entry<i8, dense<8> : vector<2xi64>>, #dlti.dl_entry<i16, dense<16> : vector<2xi64>>, #dlti.dl_entry<i128, dense<128> : vector<2xi64>>, #dlti.dl_entry<i1, dense<8> : vector<2xi64>>, #dlti.dl_entry<"dlti.endianness", "little">, #dlti.dl_entry<"dlti.stack_alignment", 128 : i64>>, fir.defaultkind = "a1c4d8i4l4r4", fir.kindmap = "", gpu.container_module, llvm.data_layout = "e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-i128:128-f80:128-n8:16:32:64-S128", llvm.ident = "flang version 20.0.0 (git@github.com:clementval/llvm-project.git 4116c1370ff76adf1e58eb3c39d0a14721794c70)", llvm.target_triple = "x86_64-unknown-linux-gnu"} {
llvm.func @_FortranACUFLaunchClusterKernel(!llvm.ptr, i64, i64, i64, i64, i64, i64, i64, i64, i64, !llvm.ptr, i32, !llvm.ptr, !llvm.ptr) attributes {sym_visibility = "private"}
llvm.func @_QMmod1Psub1() attributes {cuf.cluster_dims = #cuf.cluster_dims<x = 2 : i64, y = 2 : i64, z = 1 : i64>} {
llvm.return
}
llvm.func @_QQmain() attributes {fir.bindc_name = "test"} {
%0 = llvm.mlir.constant(1 : index) : i64
%1 = llvm.mlir.constant(2 : index) : i64
%2 = llvm.mlir.constant(0 : i32) : i32
%3 = llvm.mlir.constant(10 : index) : i64
%stream = llvm.alloca %0 x i64 : (i64) -> !llvm.ptr
%token = cuf.stream_cast %stream : !llvm.ptr
%4 = gpu.launch_func async [%token] @cuda_device_mod::@_QMmod1Psub1 blocks in (%3, %3, %0) threads in (%3, %3, %0) : i64 dynamic_shared_memory_size %2 {cuf.proc_attr = #cuf.cuda_proc<global>}
llvm.return
}
gpu.binary @cuda_device_mod [#gpu.object<#nvvm.target, "">]
}
// CHECK-LABEL: llvm.func @_QQmain()
// CHECK: %[[STREAM:.*]] = llvm.alloca %{{.*}} x i64 : (i64) -> !llvm.ptr
// CHECK: llvm.call @_FortranACUFLaunchKernel(%{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %{{.*}}, %[[STREAM]], %{{.*}}, %{{.*}}, %{{.*}})