[AMD] Use Linear Layout convertions for AMDWmma

Enable LL conwertions for WMMA as well as for MFMA layouts. See also: #5210 Signed-off-by: Ilya Veselov <[email protected]>
triton-lang · Nov 26, 2024 · 8287311 · 8287311
1 parent 68a08dd
commit 8287311
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diff --git a/lib/Conversion/TritonGPUToLLVM/ConvertLayoutOpToLLVM.cpp b/lib/Conversion/TritonGPUToLLVM/ConvertLayoutOpToLLVM.cpp
@@ -374,13 +374,16 @@ struct ConvertLayoutOpUsingLinearLayoutsConversion
     // TODO (Keren): Currently, we handle general mma/blocked/slice/dot(ampere)
     // -> mma/blocked/slice/dot(ampere) conversions. The following tasks must be
     // completed before we can remove the layoutIsOK check:
-    // 1. Support for AMD's WMMA
+    // 1. Support for AMD's WMMA dot operand
     std::function<bool(Attribute)> layoutIsOK = [&](Attribute layout) {
       if (auto dotOperand = dyn_cast<DotOperandEncodingAttr>(layout)) {
         layout = dotOperand.getParent();
+        if (isa<AMDWmmaEncodingAttr>(layout)) {
+          return false;
+        }
       }
 
-      if (isa<NvidiaMmaEncodingAttr, AMDMfmaEncodingAttr>(layout)) {
+      if (isa<MmaEncodingTrait>(layout)) {
         return !useLegacyMMAConversion;
       }
       if (isa<BlockedEncodingAttr, LinearEncodingAttr>(layout)) {

diff --git a/test/Conversion/amd/tritongpu_wmma_dot_to_llvm.mlir b/test/Conversion/amd/tritongpu_wmma_dot_to_llvm.mlir
@@ -1,5 +1,6 @@
 // RUN: triton-opt %s --split-input-file --convert-triton-amdgpu-to-llvm=arch=gfx1100 | FileCheck %s
 
+#blocked = #triton_gpu.blocked<{sizePerThread = [1, 1], threadsPerWarp = [32, 1], warpsPerCTA = [4, 1], order = [0, 1]}>
 #shared = #triton_gpu.shared<{vec = 1, perPhase = 1, maxPhase = 1, order = [1, 0], hasLeadingOffset = false}>
 #mma1 = #triton_gpu.amd_wmma<{version = 1, warpsPerCTA = [2, 2]}>
 #mma2 = #triton_gpu.amd_wmma<{version = 2, warpsPerCTA = [2, 2]}>
@@ -97,6 +98,70 @@ module attributes {"triton_gpu.num-ctas" = 1 : i32, "triton_gpu.num-warps" = 4 :
     // CHECK-COUNT-8: llvm.insertvalue {{.*}} : !llvm.struct<(f16, f16, f16, f16, f16, f16, f16, f16)>
     tt.return
   }
+
+  //  CHECK-LABEL: blocked_to_wmma1
+  tt.func @blocked_to_wmma1(%arg0: tensor<128x16xi32, #blocked>) {
+    // CHECK-COUNT-16: llvm.extractvalue {{.*}} : !llvm.struct<(i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32)>
+    // CHECK-COUNT-32: llvm.insertvalue {{.*}} : !llvm.struct<(i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32)>
+    %0 = triton_gpu.convert_layout %arg0 {allocation.offset = 0 : i32} : tensor<128x16xi32, #blocked> -> tensor<128x16xi32, #mma1>
+    tt.return
+  }
+
+  //  CHECK-LABEL: slice_blocked_to_wmma1
+  tt.func @slice_blocked_to_wmma1(%arg0: tensor<16xi32, #triton_gpu.slice<{dim = 0, parent = #blocked}>>) {
+    // CHECK-COUNT-16: llvm.extractvalue {{.*}} : !llvm.struct<(i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32)>
+    // CHECK-COUNT-1: llvm.insertvalue {{.*}} : !llvm.struct<(i32)>
+    %0 = triton_gpu.convert_layout %arg0 {allocation.offset = 0 : i32} : tensor<16xi32, #triton_gpu.slice<{dim = 0, parent = #blocked}>> -> tensor<16xi32, #triton_gpu.slice<{dim = 0, parent = #mma1}>>
+    tt.return
+  }
+
+  //  CHECK-LABEL: wmma1_to_blocked
+  tt.func @wmma1_to_blocked(%arg0: tensor<128x16xi32, #mma1>) {
+    // CHECK-COUNT-32: llvm.extractvalue {{.*}} : !llvm.struct<(i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32)>
+    // CHECK-COUNT-16: llvm.insertvalue {{.*}} : !llvm.struct<(i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32)>
+    %0 = triton_gpu.convert_layout %arg0 {allocation.offset = 0 : i32} : tensor<128x16xi32, #mma1> -> tensor<128x16xi32, #blocked>
+    tt.return
+  }
+
+  //  CHECK-LABEL: slice_wmma1_to_blocked
+  tt.func @slice_wmma1_to_blocked(%arg0: tensor<16xi32, #triton_gpu.slice<{dim = 0, parent = #mma1}>>) {
+    // CHECK-COUNT-1: llvm.extractvalue {{.*}} : !llvm.struct<(i32)>
+    // CHECK-COUNT-16: llvm.insertvalue {{.*}} : !llvm.struct<(i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32)>
+    %0 = triton_gpu.convert_layout %arg0 {allocation.offset = 0 : i32} : tensor<16xi32, #triton_gpu.slice<{dim = 0, parent = #mma1}>> -> tensor<16xi32, #triton_gpu.slice<{dim = 0, parent = #blocked}>>
+    tt.return
+  }
+
+  //  CHECK-LABEL: blocked_to_wmma2
+  tt.func @blocked_to_wmma2(%arg0: tensor<128x16xi32, #blocked>) {
+    // CHECK-COUNT-16: llvm.extractvalue {{.*}} : !llvm.struct<(i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32)>
+    // CHECK-COUNT-32: llvm.insertvalue {{.*}} : !llvm.struct<(i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32)>
+    %0 = triton_gpu.convert_layout %arg0 {allocation.offset = 0 : i32} : tensor<128x16xi32, #blocked> -> tensor<128x16xi32, #mma2>
+    tt.return
+  }
+
+  //  CHECK-LABEL: slice_blocked_to_wmma2
+  tt.func @slice_blocked_to_wmma2(%arg0: tensor<16xi32, #triton_gpu.slice<{dim = 0, parent = #blocked}>>) {
+    // CHECK-COUNT-16: llvm.extractvalue {{.*}} : !llvm.struct<(i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32)>
+    // CHECK-COUNT-1: llvm.insertvalue {{.*}} : !llvm.struct<(i32)>
+    %0 = triton_gpu.convert_layout %arg0 {allocation.offset = 0 : i32} : tensor<16xi32, #triton_gpu.slice<{dim = 0, parent = #blocked}>> -> tensor<16xi32, #triton_gpu.slice<{dim = 0, parent = #mma2}>>
+    tt.return
+  }
+
+  //  CHECK-LABEL: wmma2_to_blocked
+  tt.func @wmma2_to_blocked(%arg0: tensor<128x16xi32, #mma2>) {
+    // CHECK-COUNT-32: llvm.extractvalue {{.*}} : !llvm.struct<(i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32)>
+    // CHECK-COUNT-16: llvm.insertvalue {{.*}} : !llvm.struct<(i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32)>
+    %0 = triton_gpu.convert_layout %arg0 {allocation.offset = 0 : i32} : tensor<128x16xi32, #mma2> -> tensor<128x16xi32, #blocked>
+    tt.return
+  }
+
+  //  CHECK-LABEL: slice_wmma2_to_blocked
+  tt.func @slice_wmma2_to_blocked(%arg0: tensor<16xi32, #triton_gpu.slice<{dim = 0, parent = #mma2}>>) {
+    // CHECK-COUNT-1: llvm.extractvalue {{.*}} : !llvm.struct<(i32)>
+    // CHECK-COUNT-16: llvm.insertvalue {{.*}} : !llvm.struct<(i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32, i32)>
+    %0 = triton_gpu.convert_layout %arg0 {allocation.offset = 0 : i32} : tensor<16xi32, #triton_gpu.slice<{dim = 0, parent = #mma2}>> -> tensor<16xi32, #triton_gpu.slice<{dim = 0, parent = #blocked}>>
+    tt.return
+  }
 }
 
 // -----