forked from OSchip/llvm-project
Use "standard" load and stores in LowerVectorTransfers
Clipping creates non-affine memory accesses, use std_load and std_store instead of affine_load and affine_store. In the future we may also want a fill with the neutral element rather than clip, this would make the accesses affine if we wanted more analyses and transformations to happen post lowering to pointwise copies. PiperOrigin-RevId: 260110503
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@ -198,6 +198,8 @@ using dim = ValueBuilder<DimOp>;
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using muli = ValueBuilder<MulIOp>;
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using ret = OperationBuilder<ReturnOp>;
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using select = ValueBuilder<SelectOp>;
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using std_load = ValueBuilder<LoadOp>;
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using std_store = OperationBuilder<StoreOp>;
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using subi = ValueBuilder<SubIOp>;
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using vector_type_cast = ValueBuilder<VectorTypeCastOp>;
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@ -263,6 +263,8 @@ VectorTransferRewriter<VectorTransferReadOp>::matchAndRewrite(
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using namespace mlir::edsc;
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using namespace mlir::edsc::op;
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using namespace mlir::edsc::intrinsics;
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using IndexedValue =
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TemplatedIndexedValue<intrinsics::std_load, intrinsics::std_store>;
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VectorTransferReadOp transfer = cast<VectorTransferReadOp>(op);
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@ -289,7 +291,7 @@ VectorTransferRewriter<VectorTransferReadOp>::matchAndRewrite(
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// Computes clippedScalarAccessExprs in the loop nest scope (ivs exist).
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local(ivs) = remote(clip(transfer, view, ivs));
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});
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ValueHandle vectorValue = affine_load(vec, {constant_index(0)});
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ValueHandle vectorValue = std_load(vec, {constant_index(0)});
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(dealloc(tmp)); // vexing parse
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// 3. Propagate.
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@ -322,6 +324,8 @@ VectorTransferRewriter<VectorTransferWriteOp>::matchAndRewrite(
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using namespace mlir::edsc;
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using namespace mlir::edsc::op;
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using namespace mlir::edsc::intrinsics;
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using IndexedValue =
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TemplatedIndexedValue<intrinsics::std_load, intrinsics::std_store>;
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VectorTransferWriteOp transfer = cast<VectorTransferWriteOp>(op);
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@ -345,7 +349,7 @@ VectorTransferRewriter<VectorTransferWriteOp>::matchAndRewrite(
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ValueHandle tmp = alloc(tmpMemRefType(transfer));
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IndexedValue local(tmp);
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ValueHandle vec = vector_type_cast(tmp, vectorMemRefType(transfer));
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affine_store(vectorValue, vec, {constant_index(0)});
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std_store(vectorValue, vec, {constant_index(0)});
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LoopNestBuilder(pivs, lbs, ubs, steps)([&] {
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// Computes clippedScalarAccessExprs in the loop nest scope (ivs exist).
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remote(clip(transfer, view, ivs)) = local(ivs);
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@ -20,7 +20,7 @@ func @materialize_read_1d() {
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// CHECK: %[[FILTERED1:.*]] = select
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// CHECK: {{.*}} = select
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// CHECK: %[[FILTERED2:.*]] = select
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// CHECK-NEXT: %{{.*}} = affine.load {{.*}}[%[[FILTERED1]], %[[FILTERED2]]] : memref<7x42xf32>
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// CHECK-NEXT: %{{.*}} = load {{.*}}[%[[FILTERED1]], %[[FILTERED2]]] : memref<7x42xf32>
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}
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}
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return
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@ -94,12 +94,12 @@ func @materialize_read(%M: index, %N: index, %O: index, %P: index) {
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// CHECK-NEXT: {{.*}} = cmpi "slt", {{.*}}, %[[C0]] : index
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// CHECK-NEXT: %[[L3:.*]] = select
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//
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// CHECK-NEXT: {{.*}} = affine.load %{{.*}}[%[[L0]], %[[L1]], %[[L2]], %[[L3]]] : memref<?x?x?x?xf32>
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// CHECK-NEXT: {{.*}} = load %{{.*}}[%[[L0]], %[[L1]], %[[L2]], %[[L3]]] : memref<?x?x?x?xf32>
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// CHECK-NEXT: store {{.*}}, %[[ALLOC]][%[[I6]], %[[I5]], %[[I4]]] : memref<5x4x3xf32>
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// CHECK-NEXT: }
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// CHECK-NEXT: }
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// CHECK-NEXT: }
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// CHECK: {{.*}} = affine.load %[[VECTOR_VIEW]][{{.*}}] : memref<1xvector<5x4x3xf32>>
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// CHECK: {{.*}} = load %[[VECTOR_VIEW]][{{.*}}] : memref<1xvector<5x4x3xf32>>
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// CHECK-NEXT: dealloc %[[ALLOC]] : memref<5x4x3xf32>
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// CHECK-NEXT: }
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// CHECK-NEXT: }
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@ -170,7 +170,7 @@ func @materialize_write(%M: index, %N: index, %O: index, %P: index) {
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// CHECK-NEXT: {{.*}} = cmpi "slt", {{.*}}, %[[C0]] : index
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// CHECK-NEXT: %[[S3:.*]] = select {{.*}}, %[[C0]], {{.*}} : index
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//
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// CHECK-NEXT: {{.*}} = affine.load {{.*}}[%[[I6]], %[[I5]], %[[I4]]] : memref<5x4x3xf32>
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// CHECK-NEXT: {{.*}} = load {{.*}}[%[[I6]], %[[I5]], %[[I4]]] : memref<5x4x3xf32>
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// CHECK: store {{.*}}, {{.*}}[%[[S0]], %[[S1]], %[[S2]], %[[S3]]] : memref<?x?x?x?xf32>
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// CHECK-NEXT: }
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// CHECK-NEXT: }
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