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// RUN: mlir-opt %s \
// RUN: | mlir-opt -gpu-kernel-outlining \
// RUN: | mlir-opt -pass-pipeline='builtin.module(gpu.module(strip-debuginfo,convert-gpu-to-nvvm,gpu-to-cubin))' \
// RUN: | mlir-opt -gpu-to-llvm \
// RUN: | mlir-cpu-runner \
// RUN: --shared-libs=%mlir_cuda_runtime \
// RUN: --shared-libs=%mlir_runner_utils \
// RUN: --shared-libs=%mlir_c_runner_utils \
// RUN: --entry-point-result=void \
// RUN: | FileCheck %s
func.func @other_func(%arg0 : f32, %arg1 : memref<?xf32>) {
%cst = arith.constant 1 : index
%c0 = arith.constant 0 : index
%cst2 = memref.dim %arg1, %c0 : memref<?xf32>
gpu.launch blocks(%bx, %by, %bz) in (%grid_x = %cst, %grid_y = %cst, %grid_z = %cst)
threads(%tx, %ty, %tz) in (%block_x = %cst2, %block_y = %cst, %block_z = %cst) {
memref.store %arg0, %arg1[%tx] : memref<?xf32>
gpu.terminator
}
return
}
// CHECK: [1, 1, 1, 1, 1]
// CHECK: ( 1, 1 )
func.func @main() {
%v0 = arith.constant 0.0 : f32
%c0 = arith.constant 0: index
%arg0 = memref.alloc() : memref<5xf32>
%21 = arith.constant 5 : i32
%22 = memref.cast %arg0 : memref<5xf32> to memref<?xf32>
%23 = memref.cast %22 : memref<?xf32> to memref<*xf32>
gpu.host_register %23 : memref<*xf32>
call @printMemrefF32(%23) : (memref<*xf32>) -> ()
%24 = arith.constant 1.0 : f32
call @other_func(%24, %22) : (f32, memref<?xf32>) -> ()
call @printMemrefF32(%23) : (memref<*xf32>) -> ()
%val1 = vector.transfer_read %arg0[%c0], %v0: memref<5xf32>, vector<2xf32>
vector.print %val1: vector<2xf32>
return
}
func.func private @printMemrefF32(%ptr : memref<*xf32>)
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