[flang][cuda] Convert gpu.launch_func with result

[clementval]

We cannot use replaceOp because the newly created operation has not the same number of results.

[llvmbot]

@llvm/pr-subscribers-flang-fir-hlfir

Author: Valentin Clement (バレンタイン クレメン) (clementval)

Changes

We cannot use replaceOp because the newly created operation has not the same number of results.

---

Full diff: https://github.com/llvm/llvm-project/pull/137231.diff

2 Files Affected:

• (modified) flang/lib/Optimizer/Transforms/CUFGPUToLLVMConversion.cpp (+6-4)
• (modified) flang/test/Fir/CUDA/cuda-gpu-launch-func.mlir (+24)

diff --git a/flang/lib/Optimizer/Transforms/CUFGPUToLLVMConversion.cpp b/flang/lib/Optimizer/Transforms/CUFGPUToLLVMConversion.cpp
index ef6b80b5739c6..2549fdcb8baee 100644
--- a/flang/lib/Optimizer/Transforms/CUFGPUToLLVMConversion.cpp
+++ b/flang/lib/Optimizer/Transforms/CUFGPUToLLVMConversion.cpp
@@ -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();
diff --git a/flang/test/Fir/CUDA/cuda-gpu-launch-func.mlir b/flang/test/Fir/CUDA/cuda-gpu-launch-func.mlir
index a2f89d822c455..5d0c4438cbda4 100644
--- a/flang/test/Fir/CUDA/cuda-gpu-launch-func.mlir
+++ b/flang/test/Fir/CUDA/cuda-gpu-launch-func.mlir
@@ -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 ([email protected]: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]], %{{.*}}, %{{.*}}, %{{.*}})