[mlir][spirv] Implement vector unrolling for convert-to-spirv pass (#…

…100138)

### Description
This PR builds on #99872. It implements a minimal version of function
body vector unrolling to convert vector types into 1D and with a size
supported by SPIR-V (2, 3 or 4 depending on the original dimension). The
ops that are currently supported include those with elementwise traits
(e.g. `arith.addi`), `vector.reduction` and `vector.transpose`. This PR
also includes new LIT tests that only check for vector unrolling.

### Future Plans
- Support more ops

---------

Co-authored-by: Jakub Kuderski <[email protected]>

mlir/include/mlir/Conversion/Passes.td

@@ -47,7 +47,10 @@ def ConvertToSPIRVPass : Pass<"convert-to-spirv"> {
   let options = [
     Option<"runSignatureConversion", "run-signature-conversion", "bool",
     /*default=*/"true",
-    "Run function signature conversion to convert vector types">
+    "Run function signature conversion to convert vector types">,
+    Option<"runVectorUnrolling", "run-vector-unrolling", "bool",
+    /*default=*/"true",
+    "Run vector unrolling to convert vector types in function bodies">
   ];
 }
 

mlir/include/mlir/Dialect/SPIRV/Transforms/SPIRVConversion.h

@@ -19,8 +19,10 @@
 #include "mlir/Dialect/SPIRV/IR/TargetAndABI.h"
 #include "mlir/Dialect/Vector/Transforms/VectorRewritePatterns.h"
 #include "mlir/Transforms/DialectConversion.h"
+#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
 #include "mlir/Transforms/OneToNTypeConversion.h"
 #include "llvm/ADT/SmallSet.h"
+#include "llvm/Support/LogicalResult.h"
 
 namespace mlir {
 
@@ -189,6 +191,25 @@ Value getVulkanElementPtr(const SPIRVTypeConverter &typeConverter,
                           MemRefType baseType, Value basePtr,
                           ValueRange indices, Location loc, OpBuilder &builder);
 
+// Find the largest factor of size among {2,3,4} for the lowest dimension of
+// the target shape.
+int getComputeVectorSize(int64_t size);
+
+// GetNativeVectorShape implementation for reduction ops.
+SmallVector<int64_t> getNativeVectorShapeImpl(vector::ReductionOp op);
+
+// GetNativeVectorShape implementation for transpose ops.
+SmallVector<int64_t> getNativeVectorShapeImpl(vector::TransposeOp op);
+
+// For general ops.
+std::optional<SmallVector<int64_t>> getNativeVectorShape(Operation *op);
+
+// Unroll vectors in function signatures to native size.
+LogicalResult unrollVectorsInSignatures(Operation *op);
+
+// Unroll vectors in function bodies to native size.
+LogicalResult unrollVectorsInFuncBodies(Operation *op);
+
 } // namespace spirv
 } // namespace mlir
 

mlir/lib/Conversion/ConvertToSPIRV/ConvertToSPIRVPass.cpp

@@ -17,6 +17,8 @@
 #include "mlir/Dialect/SPIRV/IR/SPIRVAttributes.h"
 #include "mlir/Dialect/SPIRV/IR/SPIRVDialect.h"
 #include "mlir/Dialect/SPIRV/Transforms/SPIRVConversion.h"
+#include "mlir/Dialect/Vector/IR/VectorOps.h"
+#include "mlir/Dialect/Vector/Transforms/LoweringPatterns.h"
 #include "mlir/Dialect/Vector/Transforms/VectorRewritePatterns.h"
 #include "mlir/IR/PatternMatch.h"
 #include "mlir/Pass/Pass.h"
@@ -42,19 +44,16 @@ struct ConvertToSPIRVPass final
   using ConvertToSPIRVPassBase::ConvertToSPIRVPassBase;
 
   void runOnOperation() override {
-    MLIRContext *context = &getContext();
     Operation *op = getOperation();
+    MLIRContext *context = &getContext();
 
-    if (runSignatureConversion) {
-      // Unroll vectors in function signatures to native vector size.
-      RewritePatternSet patterns(context);
-      populateFuncOpVectorRewritePatterns(patterns);
-      populateReturnOpVectorRewritePatterns(patterns);
-      GreedyRewriteConfig config;
-      config.strictMode = GreedyRewriteStrictness::ExistingOps;
-      if (failed(applyPatternsAndFoldGreedily(op, std::move(patterns), config)))
-        return signalPassFailure();
-    }
+    // Unroll vectors in function signatures to native size.
+    if (runSignatureConversion && failed(spirv::unrollVectorsInSignatures(op)))
+      return signalPassFailure();
+
+    // Unroll vectors in function bodies to native size.
+    if (runVectorUnrolling && failed(spirv::unrollVectorsInFuncBodies(op)))
+      return signalPassFailure();
 
     spirv::TargetEnvAttr targetAttr = spirv::lookupTargetEnvOrDefault(op);
     std::unique_ptr<ConversionTarget> target =

mlir/lib/Dialect/SPIRV/Transforms/SPIRVConversion.cpp

@@ -20,17 +20,21 @@
 #include "mlir/Dialect/SPIRV/IR/TargetAndABI.h"
 #include "mlir/Dialect/Utils/IndexingUtils.h"
 #include "mlir/Dialect/Vector/IR/VectorOps.h"
+#include "mlir/Dialect/Vector/Transforms/LoweringPatterns.h"
 #include "mlir/Dialect/Vector/Transforms/VectorRewritePatterns.h"
 #include "mlir/IR/BuiltinTypes.h"
 #include "mlir/IR/Operation.h"
 #include "mlir/IR/PatternMatch.h"
+#include "mlir/Pass/Pass.h"
 #include "mlir/Support/LLVM.h"
 #include "mlir/Transforms/DialectConversion.h"
+#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
 #include "mlir/Transforms/OneToNTypeConversion.h"
 #include "llvm/ADT/STLExtras.h"
 #include "llvm/ADT/SmallVector.h"
 #include "llvm/ADT/StringExtras.h"
 #include "llvm/Support/Debug.h"
+#include "llvm/Support/LogicalResult.h"
 #include "llvm/Support/MathExtras.h"
 
 #include <functional>
@@ -46,14 +50,6 @@ namespace {
 // Utility functions
 //===----------------------------------------------------------------------===//
 
-static int getComputeVectorSize(int64_t size) {
-  for (int i : {4, 3, 2}) {
-    if (size % i == 0)
-      return i;
-  }
-  return 1;
-}
-
 static std::optional<SmallVector<int64_t>> getTargetShape(VectorType vecType) {
   LLVM_DEBUG(llvm::dbgs() << "Get target shape\n");
   if (vecType.isScalable()) {
@@ -62,8 +58,8 @@ static std::optional<SmallVector<int64_t>> getTargetShape(VectorType vecType) {
     return std::nullopt;
   }
   SmallVector<int64_t> unrollShape = llvm::to_vector<4>(vecType.getShape());
-  std::optional<SmallVector<int64_t>> targetShape =
-      SmallVector<int64_t>(1, getComputeVectorSize(vecType.getShape().back()));
+  std::optional<SmallVector<int64_t>> targetShape = SmallVector<int64_t>(
+      1, mlir::spirv::getComputeVectorSize(vecType.getShape().back()));
   if (!targetShape) {
     LLVM_DEBUG(llvm::dbgs() << "--no unrolling target shape defined\n");
     return std::nullopt;
@@ -1098,13 +1094,20 @@ struct ReturnOpVectorUnroll final : OpRewritePattern<func::ReturnOp> {
       // the original operand of illegal type.
       auto originalShape =
           llvm::to_vector_of<int64_t, 4>(origVecType.getShape());
-      SmallVector<int64_t> strides(targetShape->size(), 1);
+      SmallVector<int64_t> strides(originalShape.size(), 1);
+      SmallVector<int64_t> extractShape(originalShape.size(), 1);
+      extractShape.back() = targetShape->back();
       SmallVector<Type> newTypes;
       Value returnValue = returnOp.getOperand(origResultNo);
       for (SmallVector<int64_t> offsets :
            StaticTileOffsetRange(originalShape, *targetShape)) {
         Value result = rewriter.create<vector::ExtractStridedSliceOp>(
-            loc, returnValue, offsets, *targetShape, strides);
+            loc, returnValue, offsets, extractShape, strides);
+        if (originalShape.size() > 1) {
+          SmallVector<int64_t> extractIndices(originalShape.size() - 1, 0);
+          result =
+              rewriter.create<vector::ExtractOp>(loc, result, extractIndices);
+        }
         newOperands.push_back(result);
         newTypes.push_back(unrolledType);
       }
@@ -1285,6 +1288,118 @@ Value mlir::spirv::getElementPtr(const SPIRVTypeConverter &typeConverter,
                              builder);
 }
 
+//===----------------------------------------------------------------------===//
+// Public functions for vector unrolling
+//===----------------------------------------------------------------------===//
+
+int mlir::spirv::getComputeVectorSize(int64_t size) {
+  for (int i : {4, 3, 2}) {
+    if (size % i == 0)
+      return i;
+  }
+  return 1;
+}
+
+SmallVector<int64_t>
+mlir::spirv::getNativeVectorShapeImpl(vector::ReductionOp op) {
+  VectorType srcVectorType = op.getSourceVectorType();
+  assert(srcVectorType.getRank() == 1); // Guaranteed by semantics
+  int64_t vectorSize =
+      mlir::spirv::getComputeVectorSize(srcVectorType.getDimSize(0));
+  return {vectorSize};
+}
+
+SmallVector<int64_t>
+mlir::spirv::getNativeVectorShapeImpl(vector::TransposeOp op) {
+  VectorType vectorType = op.getResultVectorType();
+  SmallVector<int64_t> nativeSize(vectorType.getRank(), 1);
+  nativeSize.back() =
+      mlir::spirv::getComputeVectorSize(vectorType.getShape().back());
+  return nativeSize;
+}
+
+std::optional<SmallVector<int64_t>>
+mlir::spirv::getNativeVectorShape(Operation *op) {
+  if (OpTrait::hasElementwiseMappableTraits(op) && op->getNumResults() == 1) {
+    if (auto vecType = dyn_cast<VectorType>(op->getResultTypes()[0])) {
+      SmallVector<int64_t> nativeSize(vecType.getRank(), 1);
+      nativeSize.back() =
+          mlir::spirv::getComputeVectorSize(vecType.getShape().back());
+      return nativeSize;
+    }
+  }
+
+  return TypeSwitch<Operation *, std::optional<SmallVector<int64_t>>>(op)
+      .Case<vector::ReductionOp, vector::TransposeOp>(
+          [](auto typedOp) { return getNativeVectorShapeImpl(typedOp); })
+      .Default([](Operation *) { return std::nullopt; });
+}
+
+LogicalResult mlir::spirv::unrollVectorsInSignatures(Operation *op) {
+  MLIRContext *context = op->getContext();
+  RewritePatternSet patterns(context);
+  populateFuncOpVectorRewritePatterns(patterns);
+  populateReturnOpVectorRewritePatterns(patterns);
+  // We only want to apply signature conversion once to the existing func ops.
+  // Without specifying strictMode, the greedy pattern rewriter will keep
+  // looking for newly created func ops.
+  GreedyRewriteConfig config;
+  config.strictMode = GreedyRewriteStrictness::ExistingOps;
+  return applyPatternsAndFoldGreedily(op, std::move(patterns), config);
+}
+
+LogicalResult mlir::spirv::unrollVectorsInFuncBodies(Operation *op) {
+  MLIRContext *context = op->getContext();
+
+  // Unroll vectors in function bodies to native vector size.
+  {
+    RewritePatternSet patterns(context);
+    auto options = vector::UnrollVectorOptions().setNativeShapeFn(
+        [](auto op) { return mlir::spirv::getNativeVectorShape(op); });
+    populateVectorUnrollPatterns(patterns, options);
+    if (failed(applyPatternsAndFoldGreedily(op, std::move(patterns))))
+      return failure();
+  }
+
+  // Convert transpose ops into extract and insert pairs, in preparation of
+  // further transformations to canonicalize/cancel.
+  {
+    RewritePatternSet patterns(context);
+    auto options = vector::VectorTransformsOptions().setVectorTransposeLowering(
+        vector::VectorTransposeLowering::EltWise);
+    vector::populateVectorTransposeLoweringPatterns(patterns, options);
+    vector::populateVectorShapeCastLoweringPatterns(patterns);
+    if (failed(applyPatternsAndFoldGreedily(op, std::move(patterns))))
+      return failure();
+  }
+
+  // Run canonicalization to cast away leading size-1 dimensions.
+  {
+    RewritePatternSet patterns(context);
+
+    // We need to pull in casting way leading one dims.
+    vector::populateCastAwayVectorLeadingOneDimPatterns(patterns);
+    vector::ReductionOp::getCanonicalizationPatterns(patterns, context);
+    vector::TransposeOp::getCanonicalizationPatterns(patterns, context);
+
+    // Decompose different rank insert_strided_slice and n-D
+    // extract_slided_slice.
+    vector::populateVectorInsertExtractStridedSliceDecompositionPatterns(
+        patterns);
+    vector::InsertOp::getCanonicalizationPatterns(patterns, context);
+    vector::ExtractOp::getCanonicalizationPatterns(patterns, context);
+
+    // Trimming leading unit dims may generate broadcast/shape_cast ops. Clean
+    // them up.
+    vector::BroadcastOp::getCanonicalizationPatterns(patterns, context);
+    vector::ShapeCastOp::getCanonicalizationPatterns(patterns, context);
+
+    if (failed(applyPatternsAndFoldGreedily(op, std::move(patterns))))
+      return failure();
+  }
+  return success();
+}
+
 //===----------------------------------------------------------------------===//
 // SPIR-V TypeConverter
 //===----------------------------------------------------------------------===//

mlir/test/Conversion/ConvertToSPIRV/arith.mlir

@@ -1,4 +1,4 @@
-// RUN: mlir-opt -convert-to-spirv="run-signature-conversion=false" -split-input-file %s | FileCheck %s
+// RUN: mlir-opt -convert-to-spirv="run-signature-conversion=false run-vector-unrolling=false" -split-input-file %s | FileCheck %s
 
 //===----------------------------------------------------------------------===//
 // arithmetic ops

mlir/test/Conversion/ConvertToSPIRV/combined.mlir

@@ -1,4 +1,4 @@
-// RUN: mlir-opt -convert-to-spirv="run-signature-conversion=false" %s | FileCheck %s
+// RUN: mlir-opt -convert-to-spirv="run-signature-conversion=false run-vector-unrolling=false" -split-input-file %s | FileCheck %s
 
 // CHECK-LABEL: @combined
 // CHECK: %[[C0_F32:.*]] = spirv.Constant 0.000000e+00 : f32

mlir/test/Conversion/ConvertToSPIRV/func-signature-vector-unroll.mlir

@@ -66,6 +66,28 @@ func.func @simple_vector_8(%arg0 : vector<8xi32>) -> vector<8xi32> {
 
 // -----
 
+// CHECK-LABEL: @simple_vector_2d
+// CHECK-SAME: (%[[ARG0:.+]]: vector<4xi32>, %[[ARG1:.+]]: vector<4xi32>, %[[ARG2:.+]]: vector<4xi32>, %[[ARG3:.+]]: vector<4xi32>)
+func.func @simple_vector_2d(%arg0 : vector<4x4xi32>) -> vector<4x4xi32> {
+  // CHECK: %[[CST:.*]] = arith.constant dense<0> : vector<4x4xi32>
+  // CHECK: %[[INSERT0:.*]] = vector.insert_strided_slice %[[ARG0]], %[[CST]] {offsets = [0, 0], strides = [1]} : vector<4xi32> into vector<4x4xi32>
+  // CHECK: %[[INSERT1:.*]] = vector.insert_strided_slice %[[ARG1]], %[[INSERT0]] {offsets = [1, 0], strides = [1]} : vector<4xi32> into vector<4x4xi32>
+  // CHECK: %[[INSERT2:.*]] = vector.insert_strided_slice %[[ARG2]], %[[INSERT1]] {offsets = [2, 0], strides = [1]} : vector<4xi32> into vector<4x4xi32>
+  // CHECK: %[[INSERT3:.*]] = vector.insert_strided_slice %[[ARG3]], %[[INSERT2]] {offsets = [3, 0], strides = [1]} : vector<4xi32> into vector<4x4xi32>
+  // CHECK: %[[EXTRACT0:.*]] = vector.extract_strided_slice %[[INSERT3]] {offsets = [0, 0], sizes = [1, 4], strides = [1, 1]} : vector<4x4xi32> to vector<1x4xi32>
+  // CHECK: %[[EXTRACT0_1:.*]] = vector.extract %[[EXTRACT0]][0] : vector<4xi32> from vector<1x4xi32>
+  // CHECK: %[[EXTRACT1:.*]] = vector.extract_strided_slice %[[INSERT3]] {offsets = [1, 0], sizes = [1, 4], strides = [1, 1]} : vector<4x4xi32> to vector<1x4xi32>
+  // CHECK: %[[EXTRACT1_1:.*]] = vector.extract %[[EXTRACT1]][0] : vector<4xi32> from vector<1x4xi32>
+  // CHECK: %[[EXTRACT2:.*]] = vector.extract_strided_slice %[[INSERT3]] {offsets = [2, 0], sizes = [1, 4], strides = [1, 1]} : vector<4x4xi32> to vector<1x4xi32>
+  // CHECK: %[[EXTRACT2_1:.*]] = vector.extract %[[EXTRACT2]][0] : vector<4xi32> from vector<1x4xi32>
+  // CHECK: %[[EXTRACT3:.*]] = vector.extract_strided_slice %[[INSERT3]] {offsets = [3, 0], sizes = [1, 4], strides = [1, 1]} : vector<4x4xi32> to vector<1x4xi32>
+  // CHECK: %[[EXTRACT3_1:.*]] = vector.extract %[[EXTRACT3]][0] : vector<4xi32> from vector<1x4xi32>
+  // CHECK: return %[[EXTRACT0_1]], %[[EXTRACT1_1]], %[[EXTRACT2_1]], %[[EXTRACT3_1]] : vector<4xi32>, vector<4xi32>, vector<4xi32>, vector<4xi32>
+  return %arg0 : vector<4x4xi32>
+}
+
+// -----
+
 // CHECK-LABEL: @vector_6and8
 // CHECK-SAME: (%[[ARG0:.+]]: vector<3xi32>, %[[ARG1:.+]]: vector<3xi32>, %[[ARG2:.+]]: vector<4xi32>, %[[ARG3:.+]]: vector<4xi32>)
 func.func @vector_6and8(%arg0 : vector<6xi32>, %arg1 : vector<8xi32>) -> (vector<6xi32>, vector<8xi32>) {
@@ -113,6 +135,28 @@ func.func @scalar_vector(%arg0 : vector<8xi32>, %arg1 : vector<3xi32>, %arg2 : i
 
 // -----
 
+// CHECK-LABEL: @vector_2dand1d
+// CHECK-SAME: (%[[ARG0:.+]]: vector<3xi32>, %[[ARG1:.+]]: vector<3xi32>, %[[ARG2:.+]]: vector<3xi32>, %[[ARG3:.+]]: vector<3xi32>, %[[ARG4:.+]]: vector<4xi32>)
+func.func @vector_2dand1d(%arg0 : vector<2x6xi32>, %arg1 : vector<4xi32>) -> (vector<2x6xi32>, vector<4xi32>) {
+  // CHECK: %[[CST:.*]] = arith.constant dense<0> : vector<2x6xi32>
+  // CHECK: %[[INSERT0:.*]] = vector.insert_strided_slice %[[ARG0]], %[[CST]] {offsets = [0, 0], strides = [1]} : vector<3xi32> into vector<2x6xi32>
+  // CHECK: %[[INSERT1:.*]] = vector.insert_strided_slice %[[ARG1]], %[[INSERT0]] {offsets = [0, 3], strides = [1]} : vector<3xi32> into vector<2x6xi32>
+  // CHECK: %[[INSERT2:.*]] = vector.insert_strided_slice %[[ARG2]], %[[INSERT1]] {offsets = [1, 0], strides = [1]} : vector<3xi32> into vector<2x6xi32>
+  // CHECK: %[[INSERT3:.*]] = vector.insert_strided_slice %[[ARG3]], %[[INSERT2]] {offsets = [1, 3], strides = [1]} : vector<3xi32> into vector<2x6xi32>
+  // CHECK: %[[EXTRACT0:.*]]  = vector.extract_strided_slice %[[INSERT3]] {offsets = [0, 0], sizes = [1, 3], strides = [1, 1]} : vector<2x6xi32> to vector<1x3xi32>
+  // CHECK: %[[EXTRACT0_1:.*]]  = vector.extract %[[EXTRACT0]][0] : vector<3xi32> from vector<1x3xi32>
+  // CHECK: %[[EXTRACT1:.*]]  = vector.extract_strided_slice %[[INSERT3]] {offsets = [0, 3], sizes = [1, 3], strides = [1, 1]} : vector<2x6xi32> to vector<1x3xi32>
+  // CHECK: %[[EXTRACT1_1:.*]]  = vector.extract %[[EXTRACT1]][0] : vector<3xi32> from vector<1x3xi32>
+  // CHECK: %[[EXTRACT2:.*]]  = vector.extract_strided_slice %[[INSERT3]] {offsets = [1, 0], sizes = [1, 3], strides = [1, 1]} : vector<2x6xi32> to vector<1x3xi32>
+  // CHECK: %[[EXTRACT2_1:.*]]  = vector.extract %[[EXTRACT2]][0] : vector<3xi32> from vector<1x3xi32>
+  // CHECK: %[[EXTRACT3:.*]]  = vector.extract_strided_slice %[[INSERT3]] {offsets = [1, 3], sizes = [1, 3], strides = [1, 1]} : vector<2x6xi32> to vector<1x3xi32>
+  // CHECK: %[[EXTRACT3_1:.*]]  = vector.extract %[[EXTRACT3]][0] : vector<3xi32> from vector<1x3xi32>
+  // CHECK: return %[[EXTRACT0_1]], %[[EXTRACT1_1]], %[[EXTRACT2_1]], %[[EXTRACT3_1]], %[[ARG4]] : vector<3xi32>, vector<3xi32>, vector<3xi32>, vector<3xi32>, vector<4xi32>
+  return %arg0, %arg1 : vector<2x6xi32>, vector<4xi32>
+}
+
+// -----
+
 // CHECK-LABEL: @reduction
 // CHECK-SAME: (%[[ARG0:.+]]: vector<4xi32>, %[[ARG1:.+]]: vector<4xi32>, %[[ARG2:.+]]: vector<4xi32>, %[[ARG3:.+]]: vector<4xi32>, %[[ARG4:.+]]: i32)
 func.func @reduction(%arg0 : vector<8xi32>, %arg1 : vector<8xi32>, %arg2 : i32) -> (i32) {

mlir/test/Conversion/ConvertToSPIRV/index.mlir

@@ -1,4 +1,4 @@
-// RUN: mlir-opt %s -convert-to-spirv="run-signature-conversion=false" | FileCheck %s
+// RUN: mlir-opt -convert-to-spirv="run-signature-conversion=false run-vector-unrolling=false" -split-input-file %s | FileCheck %s
 
 // CHECK-LABEL: @basic
 func.func @basic(%a: index, %b: index) {

mlir/test/Conversion/ConvertToSPIRV/scf.mlir

@@ -1,4 +1,4 @@
-// RUN: mlir-opt -convert-to-spirv="run-signature-conversion=false" %s | FileCheck %s
+// RUN: mlir-opt -convert-to-spirv="run-signature-conversion=false run-vector-unrolling=false" -split-input-file %s | FileCheck %s
 
 // CHECK-LABEL: @if_yield
 // CHECK: %[[VAR:.*]] = spirv.Variable : !spirv.ptr<f32, Function>

mlir/test/Conversion/ConvertToSPIRV/simple.mlir

@@ -1,4 +1,4 @@
-// RUN: mlir-opt -convert-to-spirv="run-signature-conversion=false" %s | FileCheck %s
+// RUN: mlir-opt -convert-to-spirv="run-signature-conversion=false run-vector-unrolling=false" -split-input-file %s | FileCheck %s
 
 // CHECK-LABEL: @return_scalar
 // CHECK-SAME: %[[ARG0:.*]]: i32

mlir/test/Conversion/ConvertToSPIRV/ub.mlir

@@ -1,4 +1,4 @@
-// RUN: mlir-opt -convert-to-spirv="run-signature-conversion=false" %s | FileCheck %s
+// RUN: mlir-opt -convert-to-spirv="run-signature-conversion=false run-vector-unrolling=false" -split-input-file %s | FileCheck %s
 
 // CHECK-LABEL: @ub
 // CHECK: %[[UNDEF:.*]] = spirv.Undef : i32