[mlir][nvgpu] Fix nvgpu integration test #154748
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@llvm/pr-subscribers-mlir-gpu @llvm/pr-subscribers-mlir Author: lonely eagle (linuxlonelyeagle) ChangesFix nvgpu mlir file integration test. Full diff: https://github.com/llvm/llvm-project/pull/154748.diff 2 Files Affected:
diff --git a/mlir/test/Integration/GPU/CUDA/sm90/gemm_f32_f16_f16_128x128x128.mlir b/mlir/test/Integration/GPU/CUDA/sm90/gemm_f32_f16_f16_128x128x128.mlir
index a5653f395a2c4..651ccd06d9753 100644
--- a/mlir/test/Integration/GPU/CUDA/sm90/gemm_f32_f16_f16_128x128x128.mlir
+++ b/mlir/test/Integration/GPU/CUDA/sm90/gemm_f32_f16_f16_128x128x128.mlir
@@ -57,7 +57,6 @@
func.func private @printMemrefF32(memref<*xf32>)
-memref.global "private" @dynamicShmem : memref<0xf16, 3> {alignment = 16 : i64}
memref.global "private" @accShmem : memref<0xf32, 3> {alignment = 16 : i64}
func.func @main() {
@@ -148,12 +147,11 @@ func.func @main() {
%c57344 = arith.constant 57344 : index
%c40960 = arith.constant 40960 : index
- %tidx = gpu.thread_id x
- %dynamicMem = memref.get_global @dynamicShmem : memref<0xf16, 3>
- %lhsShmem = memref.reinterpret_cast %dynamicMem to offset: [0], sizes: [2, 128, 64], strides: [8192, 64, 1] : memref<0xf16, 3> to memref<2x128x64xf16, 3>
- %rhsShmem2 = memref.reinterpret_cast %dynamicMem to offset: [0], sizes: [4, 64, 128], strides: [8192,128,1] : memref<0xf16, 3> to memref<4x64x128xf16,3>
- %rhsShmem = memref.subview %rhsShmem2[2, 0, 0][2, 64, 128][1, 1, 1] : memref<4x64x128xf16,3> to memref<2x64x128xf16, strided<[8192, 128, 1], offset: 16384>, 3>
+ %tidx = gpu.thread_id x
%dynsmem = gpu.dynamic_shared_memory : memref<?xi8, #gpu.address_space<workgroup>>
+ %lhsShmem = memref.view %dynsmem[%c0][] : memref<?xi8, #gpu.address_space<workgroup>> to memref<2x128x64xf16, #gpu.address_space<workgroup>>
+ %rhsShmem = memref.view %dynsmem[%c32768][] : memref<?xi8, #gpu.address_space<workgroup>> to memref<2x64x128xf16, #gpu.address_space<workgroup>>
+
// Step 1. [GPU] Create Async Transactional Barriers (mbarriers)
%barrier = nvgpu.mbarrier.create -> !barrierType
%cnd = arith.cmpi eq, %tidx, %c0 : index
@@ -202,11 +200,11 @@ func.func @main() {
// TMA wait
%phase_c0 = arith.constant 0 : i1
nvgpu.mbarrier.try_wait.parity %barrier[%i], %phase_c0, %ticks : !barrierType
- %lhsSlice = memref.subview %lhsShmem [%i, 0, 0][1, 128, 64][1, 1, 1] : memref<2x128x64xf16, 3> to memref<128x64xf16, strided<[64, 1], offset: ?>, 3>
- %rhsSlice = memref.subview %rhsShmem [%i, 0, 0][1, 64, 128][1, 1, 1] : memref<2x64x128xf16, strided<[8192, 128, 1], offset: 16384>, 3> to memref<64x128xf16, strided<[128, 1], offset: ?>, 3>
+ %lhsSlice = memref.subview %lhsShmem [%i, 0, 0][1, 128, 64][1, 1, 1] : memref<2x128x64xf16, #gpu.address_space<workgroup>> to memref<128x64xf16, strided<[64, 1], offset: ?>, #gpu.address_space<workgroup>>
+ %rhsSlice = memref.subview %rhsShmem [%i, 0, 0][1, 64, 128][1, 1, 1] : memref<2x64x128xf16, #gpu.address_space<workgroup>> to memref<64x128xf16, strided<[128, 1], offset: ?>, #gpu.address_space<workgroup>>
// Descriptor WGMMA
- %dA = nvgpu.warpgroup.generate.descriptor %lhsSlice, %descA : memref<128x64xf16, strided<[64, 1], offset: ?>, 3>, !lhsTensorMap -> !nvgpu.warpgroup.descriptor<tensor=memref<128x64xf16, 3>>
- %dB = nvgpu.warpgroup.generate.descriptor %rhsSlice, %descB : memref<64x128xf16, strided<[128, 1], offset: ?>, 3>, !rhsTensorMap -> !nvgpu.warpgroup.descriptor<tensor=memref<64x128xf16, 3>>
+ %dA = nvgpu.warpgroup.generate.descriptor %lhsSlice, %descA : memref<128x64xf16, strided<[64, 1], offset: ?>, #gpu.address_space<workgroup>>, !lhsTensorMap -> !nvgpu.warpgroup.descriptor<tensor=memref<128x64xf16, 3>>
+ %dB = nvgpu.warpgroup.generate.descriptor %rhsSlice, %descB : memref<64x128xf16, strided<[128, 1], offset: ?>, #gpu.address_space<workgroup>>, !rhsTensorMap -> !nvgpu.warpgroup.descriptor<tensor=memref<64x128xf16, 3>>
// Perform WGMMA 128x128x64
%md = nvgpu.warpgroup.mma %dA, %dB, %mc {transposeB} : <tensor = memref<128x64xf16,3>>, <tensor = memref<64x128xf16,3>>, <fragmented = vector<128x128xf32>> -> <fragmented = vector<128x128xf32>>
scf.yield %md : !nvgpu.warpgroup.accumulator<fragmented = vector<128x128xf32>>
@@ -271,7 +269,7 @@ func.func @main() {
vector.print str "Correct Results :"
vector.print %correctCount : i32
vector.print str "Incorrect Results :"
- vector.print %errorCount : i32
+ vector.print %errorCount : i32
return
-}
+}
\ No newline at end of file
diff --git a/mlir/test/Integration/GPU/CUDA/sm90/gemm_pred_f32_f16_f16_128x128x128.mlir b/mlir/test/Integration/GPU/CUDA/sm90/gemm_pred_f32_f16_f16_128x128x128.mlir
index 197351f1921e7..db7754c89dcac 100644
--- a/mlir/test/Integration/GPU/CUDA/sm90/gemm_pred_f32_f16_f16_128x128x128.mlir
+++ b/mlir/test/Integration/GPU/CUDA/sm90/gemm_pred_f32_f16_f16_128x128x128.mlir
@@ -57,7 +57,6 @@
func.func private @printMemrefF32(memref<*xf32>)
-memref.global "private" @dynamicShmem : memref<0xf16, 3> {alignment = 16 : i64}
memref.global "private" @accShmem : memref<0xf32, 3> {alignment = 16 : i64}
func.func @main() {
@@ -149,11 +148,10 @@ func.func @main() {
%c40960 = arith.constant 40960 : index
%tidx = gpu.thread_id x
- %dynamicMem = memref.get_global @dynamicShmem : memref<0xf16, 3>
- %lhsShmem = memref.reinterpret_cast %dynamicMem to offset: [0], sizes: [2, 128, 64], strides: [8192, 64, 1] : memref<0xf16, 3> to memref<2x128x64xf16, 3>
- %rhsShmem2 = memref.reinterpret_cast %dynamicMem to offset: [0], sizes: [4, 64, 128], strides: [8192,128,1] : memref<0xf16, 3> to memref<4x64x128xf16,3>
- %rhsShmem = memref.subview %rhsShmem2[2, 0, 0][2, 64, 128][1, 1, 1] : memref<4x64x128xf16,3> to memref<2x64x128xf16, strided<[8192, 128, 1], offset: 16384>, 3>
%dynsmem = gpu.dynamic_shared_memory : memref<?xi8, #gpu.address_space<workgroup>>
+ %lhsShmem = memref.view %dynsmem[%c0][] : memref<?xi8, #gpu.address_space<workgroup>> to memref<2x128x64xf16, #gpu.address_space<workgroup>>
+ %rhsShmem = memref.view %dynsmem[%c32768][] : memref<?xi8, #gpu.address_space<workgroup>> to memref<2x64x128xf16, #gpu.address_space<workgroup>>
+
// Step 1. [GPU] Create Async Transactional Barriers (mbarriers)
%barrier = nvgpu.mbarrier.create -> !barrierType
@@ -210,11 +208,11 @@ func.func @main() {
// TMA wait
%phase_c0 = arith.constant 0 : i1
nvgpu.mbarrier.try_wait.parity %barrier[%i], %phase_c0, %ticks : !barrierType
- %lhsSlice = memref.subview %lhsShmem [%i, 0, 0][1, 128, 64][1, 1, 1] : memref<2x128x64xf16, 3> to memref<128x64xf16, strided<[64, 1], offset: ?>, 3>
- %rhsSlice = memref.subview %rhsShmem [%i, 0, 0][1, 64, 128][1, 1, 1] : memref<2x64x128xf16, strided<[8192, 128, 1], offset: 16384>, 3> to memref<64x128xf16, strided<[128, 1], offset: ?>, 3>
+ %lhsSlice = memref.subview %lhsShmem [%i, 0, 0][1, 128, 64][1, 1, 1] : memref<2x128x64xf16, #gpu.address_space<workgroup>> to memref<128x64xf16, strided<[64, 1], offset: ?>, #gpu.address_space<workgroup>>
+ %rhsSlice = memref.subview %rhsShmem [%i, 0, 0][1, 64, 128][1, 1, 1] : memref<2x64x128xf16, #gpu.address_space<workgroup>> to memref<64x128xf16, strided<[128, 1], offset: ?>, #gpu.address_space<workgroup>>
// Descriptor WGMMA
- %dA = nvgpu.warpgroup.generate.descriptor %lhsSlice, %descA : memref<128x64xf16, strided<[64, 1], offset: ?>, 3>, !lhsTensorMap -> !nvgpu.warpgroup.descriptor<tensor=memref<128x64xf16, 3>>
- %dB = nvgpu.warpgroup.generate.descriptor %rhsSlice, %descB : memref<64x128xf16, strided<[128, 1], offset: ?>, 3>, !rhsTensorMap -> !nvgpu.warpgroup.descriptor<tensor=memref<64x128xf16, 3>>
+ %dA = nvgpu.warpgroup.generate.descriptor %lhsSlice, %descA : memref<128x64xf16, strided<[64, 1], offset: ?>, #gpu.address_space<workgroup>>, !lhsTensorMap -> !nvgpu.warpgroup.descriptor<tensor=memref<128x64xf16, 3>>
+ %dB = nvgpu.warpgroup.generate.descriptor %rhsSlice, %descB : memref<64x128xf16, strided<[128, 1], offset: ?>, #gpu.address_space<workgroup>>, !rhsTensorMap -> !nvgpu.warpgroup.descriptor<tensor=memref<64x128xf16, 3>>
// Perform WGMMA 128x128x64
%md = nvgpu.warpgroup.mma %dA, %dB, %mc {transposeB} : <tensor = memref<128x64xf16,3>>, <tensor = memref<64x128xf16,3>>, <fragmented = vector<128x128xf32>> -> <fragmented = vector<128x128xf32>>
scf.yield %md : !nvgpu.warpgroup.accumulator<fragmented = vector<128x128xf32>>
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fix #133122 |
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The test for matmul.py has also failed.However, the reason should be different from the one mentioned in this PR, and I'm not quite sure why. |
linuxlonelyeagle
changed the title
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linuxlonelyeagle
requested review from
durga4github,
schwarzschild-radius and
Wolfram70
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Thank you. |
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LLVM Buildbot has detected a new failure on builder Full details are available at: https://lab.llvm.org/buildbot/#/builders/116/builds/17412 Here is the relevant piece of the build log for the reference |
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Fix nvgpu mlir file integration test. This PR fixes the bug by removing memref.get_global and then using memref.view.