Fix matmul.transpose_b for big tiles

Signed-off-by: dchigarev <[email protected]>

Author: dchigarev

lib/gc/Transforms/GPU/LinalgToXeGPU.cpp

@@ -706,13 +706,12 @@ static SmallVector<Value> createNdDescriptorTiles(
     Value newRowOffs = rewriter.create<arith::ConstantIndexOp>(loc, i);
     for (int j = 0; j < loadShape[1]; j += descTile[1] * arrayLength) {
       Value newColOffs = rewriter.create<arith::ConstantIndexOp>(loc, j);
-      if (transpose) {
-        std::swap(newRowOffs, newColOffs);
-      }
       auto tile = rewriter
                       .create<xegpu::UpdateNdOffsetOp>(
                           loc, descType, rootTile,
-                          /*offsets=*/ValueRange{newRowOffs, newColOffs},
+                          /*offsets=*/
+                              transpose ? ValueRange{newColOffs, newRowOffs}
+                                        : ValueRange{newRowOffs, newColOffs},
                           SmallVector<int64_t>{ShapedType::kDynamic,
                                                ShapedType::kDynamic})
                       .getResult();

test/mlir/test/gc/Transforms/GPU/linalg-to-xegpu-dpas-transpose.mlir

@@ -3,13 +3,14 @@
 module {
   func.func @matmul_transpose_b(%arg0: memref<1024x1024xf16>, %arg1: memref<1024x1024xf16>, %arg2: memref<1024x1024xf16>) {
     %c0 = arith.constant 0 : index
-    %c32 = arith.constant 32 : index
+    %c16 = arith.constant 16 : index
+    %c64 = arith.constant 64 : index
     %c1024 = arith.constant 1024 : index
-    scf.parallel (%arg3, %arg4) = (%c0, %c0) to (%c1024, %c1024) step (%c32, %c32) {
-      %subview_0 = memref.subview %arg2[%arg3, %arg4] [32, 32] [1, 1] : memref<1024x1024xf16> to memref<32x32xf16, strided<[1024, 1], offset: ?>>
-      %subview_1 = memref.subview %arg0[%arg3, 0] [32, 1024] [1, 1] : memref<1024x1024xf16> to memref<32x1024xf16, strided<[1024, 1], offset: ?>>
-      %subview_2 = memref.subview %arg1[%arg4, 0] [32, 1024] [1, 1] : memref<1024x1024xf16> to memref<32x1024xf16, strided<[1024, 1], offset: ?>>
-      linalg.matmul_transpose_b ins(%subview_1, %subview_2 : memref<32x1024xf16, strided<[1024, 1], offset: ?>>, memref<32x1024xf16, strided<[1024, 1], offset: ?>>) outs(%subview_0 : memref<32x32xf16, strided<[1024, 1], offset: ?>>)
+    scf.parallel (%arg3, %arg4) = (%c0, %c0) to (%c1024, %c1024) step (%c16, %c64) {
+      %subview_0 = memref.subview %arg2[%arg3, %arg4] [16, 64] [1, 1] : memref<1024x1024xf16> to memref<16x64xf16, strided<[1024, 1], offset: ?>>
+      %subview_1 = memref.subview %arg0[%arg3, 0] [16, 1024] [1, 1] : memref<1024x1024xf16> to memref<16x1024xf16, strided<[1024, 1], offset: ?>>
+      %subview_2 = memref.subview %arg1[%arg4, 0] [64, 1024] [1, 1] : memref<1024x1024xf16> to memref<64x1024xf16, strided<[1024, 1], offset: ?>>
+      linalg.matmul_transpose_b ins(%subview_1, %subview_2 : memref<16x1024xf16, strided<[1024, 1], offset: ?>>, memref<64x1024xf16, strided<[1024, 1], offset: ?>>) outs(%subview_0 : memref<16x64xf16, strided<[1024, 1], offset: ?>>)
       scf.reduce
     }
     return
@@ -19,7 +20,7 @@ module {
 // CHECK-LABEL: func.func @matmul_transpose_b
 // CHECK-SAME:  %[[Ap:.+]]: memref<1024x1024xf16>, %[[Bp:.+]]: memref<1024x1024xf16>, %[[Cp:.+]]: memref<1024x1024xf16>
 
-// CHECK: scf.parallel (%[[iter1:.+]], %[[iter2:.+]]) = (%c0, %c0) to (%c1024, %c1024) step (%c32, %c32) {
+// CHECK: scf.parallel (%[[iter1:.+]], %[[iter2:.+]]) = (%c0, %c0) to (%c1024, %c1024) step (%c16, %c64) {
 // CHECK: %[[C:.+]] = memref.subview %[[Cp]][%[[iter1]], %[[iter2]]] {{.*}}
 // CHECK: %[[A:.+]] = memref.subview %[[Ap]][%[[iter1]], 0] {{.*}}
 // CHECK: %[[B:.+]] = memref.subview %[[Bp]][%[[iter2]], 0] {{.*}}
@@ -43,9 +44,11 @@ module {
 // CHECK: %[[rootB:.+]] = xegpu.create_nd_tdesc %[[B]]
 // CHECK: %[[tB:.+]] = xegpu.update_nd_offset %[[rootB]], [%c0, %c0]
 // CHECK: %[[tB1:.+]] = xegpu.update_nd_offset %[[rootB]], [%c16, %c0]
+// CHECK: %[[tB2:.+]] = xegpu.update_nd_offset %[[rootB]], [%c32, %c0]
+// CHECK: %[[tB3:.+]] = xegpu.update_nd_offset %[[rootB]], [%c48, %c0]
 
 // Create DPAS computation loop over tiled reduction dimension.
-// CHECK: %[[res:.+]]:11 = scf.for{{.*}}%c0 to %c1024 step %c16
+// CHECK: %[[res:.+]]:13 = scf.for{{.*}}%c0 to %c1024 step %c16
 // CHECK-SAME: iter_args(%[[acc:.+]] = %[[vC_f32]],{{.*}}%[[iterA:.+]] = %[[tA]],{{.*}}%[[iterB:.+]] = %[[tB]],{{.*}}%[[iterB1:.+]] = %[[tB1]]
 // CHECK-SAME: {
 
@@ -66,10 +69,10 @@ module {
 
 // Extract DPAS-sized chunks from larger loaded tile A.
 // Tile B is already in the correct shape.
-// CHECK:   %[[vA_flat:.+]] = vector.shape_cast %[[vA]] : vector<32x16xf16> to vector<512xf16>
-// CHECK:   %[[vA_dpas_flat:.+]] = vector.extract_strided_slice{{.*}}: vector<512xf16> to vector<128xf16>
+// CHECK:   %[[vA_flat:.+]] = vector.shape_cast %[[vA]] : vector<16x16xf16> to vector<256xf16>
+// CHECK:   %[[vA_dpas_flat:.+]] = vector.extract_strided_slice{{.*}}: vector<256xf16> to vector<128xf16>
 // CHECK:   %[[vA_dpas:.+]] = vector.shape_cast %[[vA_dpas_flat]] : vector<128xf16> to vector<8x16xf16>
-// CHECK-COUNT-3: vector.extract_strided_slice
+// CHECK-COUNT-1: vector.extract_strided_slice
 
 // Perform DPAS computation.
 // CHECK:   %[[dpas:.+]] = xegpu.dpas %[[vA_dpas]], %[[vB]], %[[acc]]