xref: /llvm-project/mlir/lib/Dialect/Vector/Transforms/LowerVectorInterleave.cpp (revision cf40c93b5be5cd0011ebbf3a9eead224f7b7079a)
1 //===- LowerVectorInterleave.cpp - Lower 'vector.interleave' operation ----===//
2 //
3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
4 // See https://llvm.org/LICENSE.txt for license information.
5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
6 //
7 //===----------------------------------------------------------------------===//
8 //
9 // This file implements target-independent rewrites and utilities to lower the
10 // 'vector.interleave' operation.
11 //
12 //===----------------------------------------------------------------------===//
13 
14 #include "mlir/Dialect/Vector/IR/VectorOps.h"
15 #include "mlir/Dialect/Vector/Transforms/LoweringPatterns.h"
16 #include "mlir/Dialect/Vector/Utils/VectorUtils.h"
17 #include "mlir/IR/BuiltinTypes.h"
18 #include "mlir/IR/PatternMatch.h"
19 #include "mlir/Support/LogicalResult.h"
20 
21 #define DEBUG_TYPE "vector-interleave-lowering"
22 
23 using namespace mlir;
24 using namespace mlir::vector;
25 
26 namespace {
27 
28 /// A one-shot unrolling of vector.interleave to the `targetRank`.
29 ///
30 /// Example:
31 ///
32 /// ```mlir
33 /// vector.interleave %a, %b : vector<1x2x3x4xi64>
34 /// ```
35 /// Would be unrolled to:
36 /// ```mlir
37 /// %result = arith.constant dense<0> : vector<1x2x3x8xi64>
38 /// %0 = vector.extract %a[0, 0, 0]                 ─┐
39 ///        : vector<4xi64> from vector<1x2x3x4xi64>  |
40 /// %1 = vector.extract %b[0, 0, 0]                  |
41 ///        : vector<4xi64> from vector<1x2x3x4xi64>  | - Repeated 6x for
42 /// %2 = vector.interleave %0, %1 : vector<4xi64>    |   all leading positions
43 /// %3 = vector.insert %2, %result [0, 0, 0]         |
44 ///        : vector<8xi64> into vector<1x2x3x8xi64>  ┘
45 /// ```
46 ///
47 /// Note: If any leading dimension before the `targetRank` is scalable the
48 /// unrolling will stop before the scalable dimension.
49 class UnrollInterleaveOp : public OpRewritePattern<vector::InterleaveOp> {
50 public:
51   UnrollInterleaveOp(int64_t targetRank, MLIRContext *context,
52                      PatternBenefit benefit = 1)
53       : OpRewritePattern(context, benefit), targetRank(targetRank){};
54 
55   LogicalResult matchAndRewrite(vector::InterleaveOp op,
56                                 PatternRewriter &rewriter) const override {
57     VectorType resultType = op.getResultVectorType();
58     auto unrollIterator = vector::createUnrollIterator(resultType, targetRank);
59     if (!unrollIterator)
60       return failure();
61 
62     auto loc = op.getLoc();
63     Value result = rewriter.create<arith::ConstantOp>(
64         loc, resultType, rewriter.getZeroAttr(resultType));
65     for (auto position : *unrollIterator) {
66       Value extractLhs = rewriter.create<ExtractOp>(loc, op.getLhs(), position);
67       Value extractRhs = rewriter.create<ExtractOp>(loc, op.getRhs(), position);
68       Value interleave =
69           rewriter.create<InterleaveOp>(loc, extractLhs, extractRhs);
70       result = rewriter.create<InsertOp>(loc, interleave, result, position);
71     }
72 
73     rewriter.replaceOp(op, result);
74     return success();
75   }
76 
77 private:
78   int64_t targetRank = 1;
79 };
80 
81 /// Rewrite vector.interleave op into an equivalent vector.shuffle op, when
82 /// applicable: `sourceType` must be 1D and non-scalable.
83 ///
84 /// Example:
85 ///
86 /// ```mlir
87 /// vector.interleave %a, %b : vector<7xi16>
88 /// ```
89 ///
90 /// Is rewritten into:
91 ///
92 /// ```mlir
93 /// vector.shuffle %arg0, %arg1 [0, 7, 1, 8, 2, 9, 3, 10, 4, 11, 5, 12, 6, 13]
94 ///   : vector<7xi16>, vector<7xi16>
95 /// ```
96 class InterleaveToShuffle : public OpRewritePattern<vector::InterleaveOp> {
97 public:
98   InterleaveToShuffle(MLIRContext *context, PatternBenefit benefit = 1)
99       : OpRewritePattern(context, benefit) {};
100 
101   LogicalResult matchAndRewrite(vector::InterleaveOp op,
102                                 PatternRewriter &rewriter) const override {
103     VectorType sourceType = op.getSourceVectorType();
104     if (sourceType.getRank() != 1 || sourceType.isScalable()) {
105       return failure();
106     }
107     int64_t n = sourceType.getNumElements();
108     auto seq = llvm::seq<int64_t>(2 * n);
109     auto zip = llvm::to_vector(llvm::map_range(
110         seq, [n](int64_t i) { return (i % 2 ? n : 0) + i / 2; }));
111     rewriter.replaceOpWithNewOp<ShuffleOp>(op, op.getLhs(), op.getRhs(), zip);
112     return success();
113   }
114 };
115 
116 } // namespace
117 
118 void mlir::vector::populateVectorInterleaveLoweringPatterns(
119     RewritePatternSet &patterns, int64_t targetRank, PatternBenefit benefit) {
120   patterns.add<UnrollInterleaveOp>(targetRank, patterns.getContext(), benefit);
121 }
122 
123 void mlir::vector::populateVectorInterleaveToShufflePatterns(
124     RewritePatternSet &patterns, PatternBenefit benefit) {
125   patterns.add<InterleaveToShuffle>(patterns.getContext(), benefit);
126 }
127