[Mlir-commits] [mlir] [mlir][linalg] Pack matmul pass (PR #89782)

llvmlistbot at llvm.org llvmlistbot at llvm.org
Tue Apr 23 09:57:10 PDT 2024


================
@@ -0,0 +1,177 @@
+//===- PackMatmul.cpp - Linalg matmul packing -----------------------------===//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+
+#include "mlir/Dialect/Linalg/Passes.h"
+
+#include "mlir/Dialect/Linalg/IR/Linalg.h"
+#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
+#include "mlir/Dialect/Linalg/Utils/Utils.h"
+#include "mlir/IR/PatternMatch.h"
+#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
+#include "llvm/ADT/SmallVector.h"
+#include "llvm/ADT/TypeSwitch.h"
+
+#include <optional>
+
+namespace mlir {
+#define GEN_PASS_DEF_LINALGPACKMATMUL
+#include "mlir/Dialect/Linalg/Passes.h.inc"
+} // namespace mlir
+
+using namespace mlir;
+using namespace mlir::linalg;
+
+static std::optional<int64_t> getConstantRange(const Range &range) {
+  std::optional<int64_t> stride = getConstantIntValue(range.stride);
+  if (!stride || *stride != 1)
+    return std::nullopt;
+  std::optional<int64_t> offset = getConstantIntValue(range.offset);
+  if (!offset)
+    return std::nullopt;
+  std::optional<int64_t> size = getConstantIntValue(range.size);
+  if (!size)
+    return std::nullopt;
+  return (*size - *offset);
+}
+
+static bool validateFullTilesOnDims(TilingInterface tileOp,
+                                    ArrayRef<OpFoldResult> tiles,
+                                    ArrayRef<size_t> dims) {
+  if (dims.size() != tiles.size() || tiles.empty())
+    return false;
+
+  OpBuilder builder(tileOp);
+  OpBuilder::InsertionGuard guard(builder);
+  SmallVector<Range> iterationDomain =
+      cast<TilingInterface>(tileOp.getOperation()).getIterationDomain(builder);
+
+  for (auto dim : llvm::enumerate(dims)) {
+    if (dim.value() >= iterationDomain.size())
+      return false;
+
+    auto tileSize = getConstantIntValue(tiles[dim.index()]);
+    auto rangeOnDim = getConstantRange(iterationDomain[dim.value()]);
+
+    // If the tile factor or the range are non-constant, the tile size is
+    // considered to be invalid.
+    if (!tileSize || !rangeOnDim)
+      return false;
+
+    // The dimension must be fully divisible by the tile.
+    if (*rangeOnDim % *tileSize != 0)
+      return false;
+  }
+
+  return true;
+}
+
+static FailureOr<linalg::LinalgOp>
+packMatmulOp(RewriterBase &rewriter, linalg::LinalgOp matmulOp,
+             ArrayRef<OpFoldResult> mnkTiles) {
+  if (!(isa<linalg::MatmulOp>(matmulOp) ||
+        isa<linalg::BatchMatmulOp>(matmulOp))) {
+    return rewriter.notifyMatchFailure(matmulOp, "not a matmul-like operation");
+  }
+
+  if (mnkTiles.size() != 3)
+    return rewriter.notifyMatchFailure(matmulOp, "require 3 tile factors");
+
+  if (matmulOp.hasDynamicShape())
+    return rewriter.notifyMatchFailure(matmulOp, "require static shape");
+
+  if (matmulOp.hasPureBufferSemantics())
+    return rewriter.notifyMatchFailure(matmulOp, "require tensor semantics");
+
+  SmallVector<size_t, 3> dims{0, 1, 2};
+  // Skip the batch dimension if present.
+  bool isBatchMatmulOp = isa<linalg::BatchMatmulOp>(matmulOp);
+  if (isBatchMatmulOp)
+    dims = {1, 2, 3};
+
+  if (!validateFullTilesOnDims(cast<TilingInterface>(matmulOp.getOperation()),
+                               mnkTiles, dims)) {
+    return rewriter.notifyMatchFailure(matmulOp,
+                                       "expect packing full tiles only");
+  }
+
+  OpBuilder::InsertionGuard guard(rewriter);
+  // The op is replaced, we need to set the insertion point after it.
+  rewriter.setInsertionPointAfter(matmulOp);
+
+  auto packedCanonicalMatmul = packMatmulGreedily(
+      rewriter, matmulOp, mnkTiles, /*mnkPaddedSizesNextMultipleOf=*/{},
+      /*mnkOrder=*/{0, 1, 2});
+  if (failed(packedCanonicalMatmul))
+    return failure();
+
+  assert(packedCanonicalMatmul->packOps.size() == 3 && "failed matmul packing");
+  assert(packedCanonicalMatmul->unPackOps.size() == 1 &&
+         "failed matmul unpacking");
+
+  SmallVector<int64_t> innerPerm = {1, 0};
+  SmallVector<int64_t> outerPerm = {1, 0};
+  // Leave the batch dimension as is.
+  if (isBatchMatmulOp)
+    outerPerm = {0, 2, 1};
+
+  auto packedMatmul =
+      packTranspose(rewriter, packedCanonicalMatmul->packOps[1],
+                    packedCanonicalMatmul->packedLinalgOp,
+                    /*maybeUnPackOp=*/nullptr, outerPerm, innerPerm);
+  if (failed(packedMatmul))
+    return failure();
+
+  return packedMatmul->transposedLinalgOp;
+}
+
+namespace {
+template <typename OpTy>
+struct PackMatmul : public OpRewritePattern<OpTy> {
+  PackMatmul(MLIRContext *context, ArrayRef<int64_t> blockFactors,
+             PatternBenefit benefit = 1)
+      : OpRewritePattern<OpTy>(context, benefit), blockFactors(blockFactors) {}
+
+  LogicalResult matchAndRewrite(OpTy matmulOp,
+                                PatternRewriter &rewriter) const override {
+    if (blockFactors.empty())
+      return failure();
+    auto packedMatmul =
+        packMatmulOp(rewriter, matmulOp,
+                     getAsOpFoldResult(rewriter.getI64ArrayAttr(blockFactors)));
+    if (failed(packedMatmul))
+      return failure();
+    return success();
+  }
+
+private:
+  SmallVector<int64_t> blockFactors;
+};
+
+// Entry point for packing matmul operations.
+// Pack MatmulOp as following:
+// [MB][NB][mb][nb] += [MB][KB][mb][kb] * [NB][KB][kb][nb]
+// Pack a BatchMatmulOp as following:
+// [B][MB][NB][mb][nb] += [B][MB][KB][mb][kb] * [B][NB][KB][kb][nb]
+struct LinalgPackMatmul : public impl::LinalgPackMatmulBase<LinalgPackMatmul> {
----------------
MaheshRavishankar wrote:

I dont see much value in a pass in MLIR.  I think what is more valuable is the `packMatmulOp` method here.



https://github.com/llvm/llvm-project/pull/89782


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