1//===- VectorLegalization.cpp - Legalize vectors for lowering to ArmSME ---===//
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 pass legalizes vector operations so they can be lowered to ArmSME.
10//
11// Note: In the context of this pass 'tile' always refers to an SME tile.
12//
13//===----------------------------------------------------------------------===//
14
15#include "mlir/Dialect/Arith/Utils/Utils.h"
16#include "mlir/Dialect/ArmSME/IR/ArmSME.h"
17#include "mlir/Dialect/ArmSME/Transforms/Passes.h"
18#include "mlir/Dialect/ArmSME/Utils/Utils.h"
19#include "mlir/Dialect/Func/IR/FuncOps.h"
20#include "mlir/Dialect/Func/Transforms/FuncConversions.h"
21#include "mlir/Dialect/Index/IR/IndexDialect.h"
22#include "mlir/Dialect/Index/IR/IndexOps.h"
23#include "mlir/Dialect/MemRef/IR/MemRef.h"
24#include "mlir/Dialect/SCF/IR/SCF.h"
25#include "mlir/Dialect/SCF/Transforms/Patterns.h"
26#include "mlir/Dialect/Utils/IndexingUtils.h"
27#include "mlir/Dialect/Vector/Utils/VectorUtils.h"
28#include "mlir/Transforms/DialectConversion.h"
29#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
30
31#define DEBUG_TYPE "arm-sme-vector-legalization"
32
33namespace mlir::arm_sme {
34#define GEN_PASS_DEF_VECTORLEGALIZATION
35#include "mlir/Dialect/ArmSME/Transforms/Passes.h.inc"
36} // namespace mlir::arm_sme
37
38using namespace mlir;
39using namespace mlir::arm_sme;
40
41namespace {
42
43//===----------------------------------------------------------------------===//
44// Decomposition of vector operations larger than an SME tile
45//===----------------------------------------------------------------------===//
46
47// Common match failure reasons.
48static constexpr StringLiteral kMatchFailureNotSMETileTypeMultiple(
49 "op vector size is not multiple of SME tiles");
50static constexpr StringLiteral kMatchFailureUnsupportedMaskOp(
51 "op mask is unsupported for legalization/decomposition");
52static constexpr StringLiteral
53 kMatchFailureNonPermutationMap("op affine map is not a permutation");
54static constexpr StringLiteral kMatchFailureNotIllegalToLegal(
55 "expected transpose from illegal type to legal type");
56
57/// An SMESubTile represents a single SME-sized sub-tile from decomposing a
58/// larger vector type. The (`row`, `col`) are the position of the tile in the
59/// original vector type. For example for an [8]x[8] tile with four [4]x[4]
60/// sub-tiles, we would have:
61///
62/// 8 x vscale
63/// ┌─────────────┬─────────────┐
64/// │(0,0) │(0,4) │
65/// │ │ │
66/// ├─────────────┼─────────────┤ 8 x vscale
67/// │(4,0) │(4,4) │
68/// │ │ │
69/// └─────────────┴─────────────┘
70struct SMESubTile {
71 // Note: The units of (row, col) are vscale (as SME tiles are scalable).
72 int row{0};
73 int col{0};
74 // The SME tile type.
75 VectorType type;
76};
77
78/// Adds a constant elementwise scalable offset to `indices` (which are of equal
79/// length). For example, in the 2D case this would return:
80// { indices[0] + offset[0] * vscale, indices[1] + offset[1] * vscale }
81SmallVector<Value, 2> addConstantScalableOffset(OpBuilder &builder,
82 Location loc,
83 ValueRange indices,
84 ArrayRef<int> scalableOffsets) {
85 auto vscale = builder.create<vector::VectorScaleOp>(loc);
86 return llvm::map_to_vector(
87 C: llvm::zip_equal(t&: indices, u&: scalableOffsets), F: [&](auto pair) -> Value {
88 auto [index, base] = pair;
89 auto offset = builder.create<arith::MulIOp>(
90 loc, builder.create<arith::ConstantIndexOp>(loc, base), vscale);
91 return builder.create<arith::AddIOp>(loc, index, offset);
92 });
93}
94
95/// Adjusts `indices` (e.g. from a load/store) for a larger vector type to
96/// indices for one of the SME sub-tiles it will decompose into.
97///
98/// For example, if you were to decompose an 8x8 load into four 4x4 tiles, the
99/// indices for each tile would need to be adjusted as follows:
100///
101/// initial indices = [a,b], inital size = 8x8, target size = 4x4
102/// ┌─────────────┬─────────────┐
103/// │[a,b] │[a,b+4] │
104/// │ │ │
105/// ├─────────────┼─────────────┤
106/// │[a+4,b] │[a+4,b+4] │
107/// │ │ │
108/// └─────────────┴─────────────┘
109SmallVector<Value, 2> getSMESubTileIndices(OpBuilder &builder, Location loc,
110 ValueRange indices,
111 SMESubTile smeTile) {
112 return addConstantScalableOffset(builder, loc, indices,
113 scalableOffsets: {smeTile.row, smeTile.col});
114}
115
116/// Returns true if `mask` is generated by an operation that can be decomposed
117/// for SME. Currently, that is just no mask, or vector.create_mask.
118/// TODO: Add support for vector.constant_mask once required for SME.
119bool isSupportedMaskOp(Value mask) {
120 return !mask || mask.getDefiningOp<vector::CreateMaskOp>();
121}
122
123/// Extracts a mask for an SME sub-tile from the mask of a larger vector type.
124Value extractSMEMask(OpBuilder &builder, Location loc, Value mask,
125 SMESubTile smeTile) {
126 assert(isSupportedMaskOp(mask));
127 if (!mask)
128 return Value{};
129 auto createMask = mask.getDefiningOp<vector::CreateMaskOp>();
130 // The operands of `vector.create_mask` (from a 2D perspective) are the
131 // coordinates where the mask ends. So we subtract where this tile starts,
132 // from the mask operands to get the parameters for this sub-tile.
133 auto smeTileMaskDims = addConstantScalableOffset(
134 builder, loc, createMask.getOperands(), {-smeTile.row, -smeTile.col});
135 auto smeTileCreateMask = builder.create<vector::CreateMaskOp>(
136 loc, smeTile.type.clone(builder.getI1Type()), smeTileMaskDims);
137 return smeTileCreateMask.getResult();
138}
139
140/// Constructs an iterator that returns each SME tile (with coordinates)
141/// contained within a VectorType. For example, if decomposing an [8]x[8] into
142/// [4]x[4] tiles, the iterator would yield the tiles: (0, 0), (0, 4), (4, 0),
143/// (4, 4).
144auto decomposeToSMETiles(OpBuilder &builder, VectorType type,
145 VectorType smeTileType,
146 bool transposeIndices = false) {
147 return llvm::map_range(
148 StaticTileOffsetRange(
149 type.getShape(),
150 {std::min(type.getDimSize(0), smeTileType.getDimSize(0)),
151 std::min(type.getDimSize(1), smeTileType.getDimSize(1))}),
152 [=](auto indices) {
153 int row = int(indices[0]);
154 int col = int(indices[1]);
155 if (transposeIndices)
156 std::swap(a&: row, b&: col);
157 return SMESubTile{row, col, smeTileType};
158 });
159}
160
161/// Returns the number of SME tiles that fit into the (2D-scalable) vector type
162/// `type`.
163int getNumberOfSMETilesForVectorType(VectorType type) {
164 assert(isMultipleOfSMETileVectorType(type) &&
165 "`type` not multiple of SME tiles");
166 int64_t vectorRows = type.getDimSize(0);
167 int64_t vectorCols = type.getDimSize(1);
168 auto elementType = type.getElementType();
169 unsigned minNumElts = getSMETileSliceMinNumElts(elementType);
170 return (vectorRows * vectorCols) / (minNumElts * minNumElts);
171}
172
173/// Legalize `arith.constant dense<value>` splat operations to fit within SME
174/// tiles by decomposing them into tile-sized operations.
175struct LegalizeArithConstantOpsByDecomposition
176 : public OpConversionPattern<arith::ConstantOp> {
177 using OpConversionPattern::OpConversionPattern;
178
179 LogicalResult
180 matchAndRewrite(arith::ConstantOp constantOp, OpAdaptor adaptor,
181 ConversionPatternRewriter &rewriter) const override {
182 auto vectorType = dyn_cast<VectorType>(constantOp.getType());
183 auto denseAttr = dyn_cast<DenseElementsAttr>(constantOp.getValueAttr());
184 if (!vectorType || !denseAttr || !denseAttr.isSplat())
185 return failure();
186
187 if (!isMultipleOfSMETileVectorType(vectorType))
188 return rewriter.notifyMatchFailure(constantOp,
189 kMatchFailureNotSMETileTypeMultiple);
190
191 auto smeTileType = getSMETileTypeForElement(vectorType.getElementType());
192 auto tileCount = getNumberOfSMETilesForVectorType(vectorType);
193 auto tileSplat = rewriter.create<arith::ConstantOp>(
194 constantOp.getLoc(), denseAttr.resizeSplat(smeTileType));
195 SmallVector<Value> repl(tileCount, tileSplat);
196 rewriter.replaceOpWithMultiple(constantOp, {repl});
197
198 return success();
199 }
200};
201
202/// Legalize `vector.outerproduct` operations to fit within SME tiles by
203/// decomposing them into tile-sized operations.
204struct LegalizeVectorOuterProductOpsByDecomposition
205 : public OpConversionPattern<vector::OuterProductOp> {
206 using OpConversionPattern::OpConversionPattern;
207
208 LogicalResult
209 matchAndRewrite(vector::OuterProductOp outerProductOp,
210 OneToNOpAdaptor adaptor,
211 ConversionPatternRewriter &rewriter) const override {
212 auto vectorType = outerProductOp.getResultVectorType();
213 if (!isMultipleOfSMETileVectorType(vectorType))
214 return rewriter.notifyMatchFailure(outerProductOp,
215 kMatchFailureNotSMETileTypeMultiple);
216
217 Value mask;
218 Operation *rootOp = outerProductOp;
219 auto loc = outerProductOp.getLoc();
220 if (outerProductOp.isMasked()) {
221 auto maskOp = outerProductOp.getMaskingOp();
222 mask = maskOp.getMask();
223 rootOp = maskOp;
224 rewriter.setInsertionPoint(rootOp);
225 }
226
227 if (!isSupportedMaskOp(mask))
228 return rewriter.notifyMatchFailure(outerProductOp,
229 kMatchFailureUnsupportedMaskOp);
230
231 ValueRange accSMETiles = adaptor.getAcc();
232 auto smeTileType = getSMETileTypeForElement(vectorType.getElementType());
233 VectorType sliceType = VectorType::Builder(smeTileType).dropDim(0);
234
235 SmallVector<Value> resultSMETiles;
236 for (auto [index, smeTile] : llvm::enumerate(
237 decomposeToSMETiles(rewriter, vectorType, smeTileType))) {
238
239 auto smeMask = extractSMEMask(rewriter, loc, mask, smeTile);
240 auto lhs = rewriter.create<vector::ScalableExtractOp>(
241 loc, sliceType, outerProductOp.getLhs(), smeTile.row);
242 auto rhs = rewriter.create<vector::ScalableExtractOp>(
243 loc, sliceType, outerProductOp.getRhs(), smeTile.col);
244 auto smeOuterProduct = rewriter.create<vector::OuterProductOp>(
245 loc, smeTileType, lhs, rhs,
246 !accSMETiles.empty() ? accSMETiles[index] : Value{},
247 outerProductOp.getKind());
248
249 auto maskedOuterProduct =
250 vector::maskOperation(rewriter, smeOuterProduct, smeMask);
251 resultSMETiles.push_back(maskedOuterProduct->getResult(0));
252 }
253
254 rewriter.replaceOpWithMultiple(op: rootOp, newValues: {resultSMETiles});
255 return success();
256 }
257};
258
259// Workaround for `vector.mask`. We want to match on `vector.outerproduct` (to
260// get the help of the type conversion), but doing so results in the type
261// conversion adding target materializations in the `vector.mask` region
262// (invalid). This pattern matches on `vector.mask` then calls into the
263// `vector.outerproduct` pattern to work around this issue.
264struct LegalizeMaskedVectorOuterProductOpsByDecomposition
265 : public OpConversionPattern<vector::MaskOp> {
266 using OpConversionPattern::OpConversionPattern;
267
268 LogicalResult
269 matchAndRewrite(vector::MaskOp maskOp, OneToNOpAdaptor adaptor,
270 ConversionPatternRewriter &rewriter) const override {
271 if (auto outerProductOp = llvm::dyn_cast_or_null<vector::OuterProductOp>(
272 maskOp.getMaskableOp())) {
273 LegalizeVectorOuterProductOpsByDecomposition pattern(*getTypeConverter(),
274 getContext());
275 return static_cast<RewritePattern &>(pattern).matchAndRewrite(
276 outerProductOp, rewriter);
277 }
278 return failure();
279 }
280};
281
282/// Legalize `vector.transfer_read` operations to fit within SME tiles by
283/// decomposing them into tile-sized operations.
284struct LegalizeTransferReadOpsByDecomposition
285 : public OpConversionPattern<vector::TransferReadOp> {
286 using OpConversionPattern::OpConversionPattern;
287
288 LogicalResult
289 matchAndRewrite(vector::TransferReadOp readOp, OneToNOpAdaptor adaptor,
290 ConversionPatternRewriter &rewriter) const override {
291 auto vectorType = readOp.getVectorType();
292 if (!isMultipleOfSMETileVectorType(vectorType))
293 return rewriter.notifyMatchFailure(readOp,
294 kMatchFailureNotSMETileTypeMultiple);
295
296 auto mask = readOp.getMask();
297 if (!isSupportedMaskOp(mask))
298 return rewriter.notifyMatchFailure(readOp,
299 kMatchFailureUnsupportedMaskOp);
300
301 auto permutationMap = readOp.getPermutationMap();
302 if (!permutationMap.isPermutation())
303 return rewriter.notifyMatchFailure(readOp,
304 kMatchFailureNonPermutationMap);
305
306 // Note: For 2D vector types the only non-identity permutation is a simple
307 // transpose [1, 0].
308 bool transposed = !permutationMap.isIdentity();
309
310 auto loc = readOp.getLoc();
311 auto smeTileType = getSMETileTypeForElement(vectorType.getElementType());
312
313 SmallVector<Value> resultSMETiles;
314 for (SMESubTile smeTile :
315 decomposeToSMETiles(rewriter, vectorType, smeTileType, transposed)) {
316 auto smeMask = extractSMEMask(rewriter, loc, mask, smeTile);
317 auto smeRead = rewriter.create<vector::TransferReadOp>(
318 loc, smeTileType, readOp.getBase(),
319 getSMESubTileIndices(rewriter, loc, readOp.getIndices(), smeTile),
320 readOp.getPermutationMapAttr(), readOp.getPadding(), smeMask,
321 readOp.getInBoundsAttr());
322 resultSMETiles.push_back(smeRead);
323 }
324
325 rewriter.replaceOpWithMultiple(readOp, {resultSMETiles});
326 return success();
327 }
328};
329
330/// Legalize `vector.transfer_write` operations to fit within SME tiles by
331/// decomposing them into tile-sized operations.
332struct LegalizeTransferWriteOpsByDecomposition
333 : public OpConversionPattern<vector::TransferWriteOp> {
334 using OpConversionPattern::OpConversionPattern;
335
336 LogicalResult
337 matchAndRewrite(vector::TransferWriteOp writeOp, OneToNOpAdaptor adaptor,
338 ConversionPatternRewriter &rewriter) const override {
339 auto vectorType = writeOp.getVectorType();
340 if (!isMultipleOfSMETileVectorType(vectorType))
341 return rewriter.notifyMatchFailure(writeOp,
342 kMatchFailureNotSMETileTypeMultiple);
343
344 auto mask = writeOp.getMask();
345 if (!isSupportedMaskOp(mask))
346 return rewriter.notifyMatchFailure(writeOp,
347 kMatchFailureUnsupportedMaskOp);
348
349 auto permutationMap = writeOp.getPermutationMap();
350 if (!permutationMap.isPermutation())
351 return rewriter.notifyMatchFailure(writeOp,
352 kMatchFailureNonPermutationMap);
353
354 // Note: For 2D vector types the only non-identity permutation is a simple
355 // transpose [1, 0].
356 bool transposed = !permutationMap.isIdentity();
357
358 auto loc = writeOp.getLoc();
359 auto smeTileType = getSMETileTypeForElement(vectorType.getElementType());
360 auto inputSMETiles = adaptor.getValueToStore();
361
362 Value destTensorOrMemref = writeOp.getBase();
363 for (auto [index, smeTile] : llvm::enumerate(decomposeToSMETiles(
364 rewriter, vectorType, smeTileType, transposed))) {
365 auto smeMask = extractSMEMask(rewriter, loc, mask, smeTile);
366 auto smeWrite = rewriter.create<vector::TransferWriteOp>(
367 loc, inputSMETiles[index], destTensorOrMemref,
368 getSMESubTileIndices(rewriter, loc, writeOp.getIndices(), smeTile),
369 writeOp.getPermutationMapAttr(), smeMask, writeOp.getInBoundsAttr());
370 if (writeOp.hasPureTensorSemantics())
371 destTensorOrMemref = smeWrite.getResult();
372 }
373
374 if (writeOp.hasPureTensorSemantics())
375 rewriter.replaceOp(writeOp, destTensorOrMemref);
376 else
377 rewriter.eraseOp(op: writeOp);
378
379 return success();
380 }
381};
382
383/// Legalize a multi-tile transfer_write as a single store loop. This is done as
384/// part of type decomposition as at this level we know each tile write is
385/// disjoint, but that information is lost after decomposition (without analysis
386/// to reconstruct it).
387///
388/// Example (pseudo-MLIR):
389///
390/// ```
391/// vector.transfer_write %vector, %dest[%y, %x], %mask
392/// : vector<[16]x[8]xi16>, memref<?x?xi16>
393/// ```
394/// Is rewritten to:
395/// ```
396/// scf.for %slice_idx = %c0 to %c8_vscale step %c1 {
397/// %upper_slice_mask = vector.extract %mask[%slice_idx] ─┐
398/// : vector<[8]xi1> from vector<[16]x[8]xi1> |
399/// %upper_slice = vector.extract %upper_tile[%slice_idx] |- Store upper tile
400/// : vector<[8]xi16> from vector<[8]x[8]xi16> |
401/// vector.transfer_write %upper_slice, |
402/// %dest[%slice_idx + %y, %x], %upper_slice_mask |
403/// : vector<[8]xi16>, memref<?x?xi16> ┘
404/// %lower_slice_idx = %slice_idx + %c8_vscale ─┐
405/// %lower_slice_mask = vector.extract %mask[%lower_slice_idx] |
406/// : vector<[8]xi1> from vector<[16]x[8]xi1> |
407/// %lower_slice = vector.extract %lower_tile[%slice_idx] |- Store lower
408/// : vector<[8]xi16> from vector<[8]x[8]xi16> | tile
409/// vector.transfer_write %lower_slice, |
410/// %dest[%lower_slice_idx + %y, %x], %lower_slice_mask |
411/// : vector<[8]xi16>, memref<?x?xi16> ┘
412/// }
413/// ```
414struct LegalizeMultiTileTransferWriteAsStoreLoop
415 : public OpConversionPattern<vector::TransferWriteOp> {
416 using OpConversionPattern::OpConversionPattern;
417
418 LogicalResult
419 matchAndRewrite(vector::TransferWriteOp writeOp, OneToNOpAdaptor adaptor,
420 ConversionPatternRewriter &rewriter) const override {
421 if (writeOp.hasPureTensorSemantics())
422 return rewriter.notifyMatchFailure(
423 writeOp, "TODO: tensor semantics are unsupported");
424
425 auto permutationMap = writeOp.getPermutationMap();
426 if (!permutationMap.isPermutation())
427 return rewriter.notifyMatchFailure(writeOp,
428 kMatchFailureNonPermutationMap);
429
430 bool transposed = !permutationMap.isIdentity();
431 if (transposed)
432 return rewriter.notifyMatchFailure(writeOp,
433 "TODO: transpose unsupported");
434
435 auto vectorType = writeOp.getVectorType();
436 if (!isMultipleOfSMETileVectorType(vectorType))
437 return rewriter.notifyMatchFailure(writeOp,
438 kMatchFailureNotSMETileTypeMultiple);
439
440 // Note: We also disallow masks where any dimension is > 16 because that
441 // prevents the masking from being lowered to use arm_sve.psel.
442 auto mask = writeOp.getMask();
443 if (!isSupportedMaskOp(mask) || (mask && (vectorType.getDimSize(0) > 16 ||
444 vectorType.getDimSize(1) > 16)))
445 return rewriter.notifyMatchFailure(writeOp,
446 kMatchFailureUnsupportedMaskOp);
447
448 auto loc = writeOp.getLoc();
449 auto createVscaleMultiple =
450 vector::makeVscaleConstantBuilder(rewriter, loc: loc);
451
452 // Get SME tile and slice types.
453 auto smeTileType = getSMETileTypeForElement(vectorType.getElementType());
454 auto minTileSlices = smeTileType.getDimSize(0);
455 VectorType sliceMaskType =
456 VectorType::get(minTileSlices, rewriter.getI1Type(), true);
457
458 // Create loop over all tile slices.
459 auto lowerBound = rewriter.create<arith::ConstantIndexOp>(loc, 0);
460 auto upperBound = createVscaleMultiple(minTileSlices);
461 auto step = rewriter.create<arith::ConstantIndexOp>(loc, 1);
462 auto storeLoop =
463 rewriter.create<scf::ForOp>(loc, lowerBound, upperBound, step);
464 rewriter.setInsertionPointToStart(storeLoop.getBody());
465
466 // For each sub-tile of the multi-tile `vectorType`.
467 auto inputSMETiles = adaptor.getValueToStore();
468 auto tileSliceIndex = storeLoop.getInductionVar();
469 for (auto [index, smeTile] : llvm::enumerate(
470 decomposeToSMETiles(rewriter, vectorType, smeTileType))) {
471 // The coordinates of the tile within `vectorType`.
472 auto tileRow = createVscaleMultiple(smeTile.row);
473 auto tileCol = createVscaleMultiple(smeTile.col);
474
475 // The current slice of `vectorType` we are processing.
476 auto sliceIndex =
477 rewriter.create<arith::AddIOp>(loc, tileRow, tileSliceIndex);
478
479 // Where in the destination memref the current slice will be stored.
480 auto storeRow = rewriter.create<arith::AddIOp>(loc, sliceIndex,
481 writeOp.getIndices()[0]);
482 auto storeCol =
483 rewriter.create<arith::AddIOp>(loc, tileCol, writeOp.getIndices()[1]);
484
485 // Extract the mask for the current slice.
486 Value sliceMask = nullptr;
487 if (mask) {
488 sliceMask = rewriter.create<vector::ExtractOp>(
489 loc, mask, OpFoldResult(sliceIndex));
490 if (sliceMaskType != sliceMask.getType())
491 sliceMask = rewriter.create<vector::ScalableExtractOp>(
492 loc, sliceMaskType, sliceMask, smeTile.col);
493 }
494
495 // Extract and store the current slice.
496 Value tile = inputSMETiles[index];
497 auto slice =
498 rewriter.create<vector::ExtractOp>(loc, tile, tileSliceIndex);
499 rewriter.create<vector::TransferWriteOp>(
500 loc, slice, writeOp.getBase(), ValueRange{storeRow, storeCol},
501 AffineMapAttr::get(writeOp.getPermutationMap().dropResult(0)),
502 sliceMask,
503 rewriter.getBoolArrayAttr(
504 ArrayRef<bool>(writeOp.getInBoundsValues()).drop_front()));
505 }
506
507 rewriter.eraseOp(op: writeOp);
508 return success();
509 }
510};
511
512//===----------------------------------------------------------------------===//
513// ArmSME-specific fixup canonicalizations/folds
514//===----------------------------------------------------------------------===//
515
516/// Folds an extract from a 3D `vector.create_mask` (which is a vector of
517/// SME-like masks), into a compare and a 2D `vector.create_mask`. This is
518/// necessary for the mask to be lowered to ArmSME.
519///
520/// Example:
521///
522/// BEFORE:
523/// ```mlir
524/// %mask = vector.create_mask %nonConstantDim, %a, %b : vector<4x[4]x[4]xi1>
525/// %subMask = vector.extract %mask[2]
526/// : vector<[4]x[4]xi1> from vector<4x[4]x[4]xi1>
527/// ```
528///
529/// AFTER:
530/// ```mlir
531/// %extractionInTrueRegion = arith.cmpi slt, %c2, %nonConstantDim : index
532/// %newMaskFrontDim = arith.select %extractionInTrueRegion, %a, %c0 : index
533/// %subMask = vector.create_mask %newMaskFrontDim, %b : vector<[4]x[4]xi1>
534/// ```
535struct FoldExtractFromVectorOfSMELikeCreateMasks
536 : public OpRewritePattern<vector::ExtractOp> {
537 using OpRewritePattern<vector::ExtractOp>::OpRewritePattern;
538
539 LogicalResult matchAndRewrite(vector::ExtractOp extractOp,
540 PatternRewriter &rewriter) const override {
541 auto loc = extractOp.getLoc();
542 auto createMaskOp =
543 extractOp.getVector().getDefiningOp<vector::CreateMaskOp>();
544 if (!createMaskOp)
545 return rewriter.notifyMatchFailure(
546 extractOp, "extract not from vector.create_mask op");
547
548 VectorType extractedMaskType =
549 llvm::dyn_cast<VectorType>(extractOp.getResult().getType());
550 if (!extractedMaskType)
551 return rewriter.notifyMatchFailure(extractOp,
552 "extracted type is not a vector type");
553
554 auto numScalable = extractedMaskType.getNumScalableDims();
555 if (numScalable != 2)
556 return rewriter.notifyMatchFailure(
557 extractOp, "expected extracted type to be an SME-like mask");
558
559 // TODO: Support multiple extraction indices.
560 if (extractOp.getStaticPosition().size() != 1)
561 return rewriter.notifyMatchFailure(
562 extractOp, "only a single extraction index is supported");
563
564 auto frontMaskDim = createMaskOp.getOperand(0);
565 if (frontMaskDim.getDefiningOp<arith::ConstantOp>())
566 return rewriter.notifyMatchFailure(
567 extractOp,
568 "constant vector.create_masks dims should be folded elsewhere");
569
570 auto zero = rewriter.create<arith::ConstantIndexOp>(loc, 0);
571 auto extractionIndex = getValueOrCreateConstantIndexOp(
572 rewriter, loc, extractOp.getMixedPosition()[0]);
573 auto extractionInTrueRegion = rewriter.create<arith::CmpIOp>(
574 loc, rewriter.getI1Type(), arith::CmpIPredicate::slt, extractionIndex,
575 frontMaskDim);
576 auto newMaskFrontDim = rewriter.create<arith::SelectOp>(
577 loc, extractionInTrueRegion, createMaskOp.getOperand(1), zero);
578
579 rewriter.replaceOpWithNewOp<vector::CreateMaskOp>(
580 extractOp, extractedMaskType,
581 ValueRange{newMaskFrontDim, createMaskOp.getOperand(2)});
582 return success();
583 }
584};
585
586/// A vector type where no fixed dimension comes after a scalable dimension.
587bool isLegalVectorType(VectorType vType) {
588 bool seenFixedDim = false;
589 for (bool scalableFlag : llvm::reverse(vType.getScalableDims())) {
590 seenFixedDim |= !scalableFlag;
591 if (seenFixedDim && scalableFlag)
592 return false;
593 }
594 return true;
595}
596
597/// Lifts an illegal vector.transpose and vector.transfer_read to a
598/// memref.subview + memref.transpose, followed by a legal read.
599///
600/// 'Illegal' here means a leading scalable dimension and a fixed trailing
601/// dimension, which has no valid lowering.
602///
603/// The memref.transpose is metadata-only transpose that produces a strided
604/// memref, which eventually becomes a loop reading individual elements.
605///
606/// Example:
607///
608/// BEFORE:
609/// ```mlir
610/// %illegalRead = vector.transfer_read %memref[%a, %b]
611/// : memref<?x?xf32>, vector<[8]x4xf32>
612/// %legalType = vector.transpose %illegalRead, [1, 0]
613/// : vector<[8]x4xf32> to vector<4x[8]xf32>
614/// ```
615///
616/// AFTER:
617/// ```mlir
618/// %readSubview = memref.subview %memref[%a, %b] [%c8_vscale, %c4] [%c1, %c1]
619/// : memref<?x?xf32> to memref<?x?xf32>
620/// %transpose = memref.transpose %readSubview (d0, d1) -> (d1, d0)
621/// : memref<?x?xf32> to memref<?x?xf32>
622/// %legalType = vector.transfer_read %transpose[%c0, %c0]
623/// : memref<?x?xf32>, vector<4x[8]xf32>
624/// ```
625struct LiftIllegalVectorTransposeToMemory
626 : public OpRewritePattern<vector::TransposeOp> {
627 using OpRewritePattern<vector::TransposeOp>::OpRewritePattern;
628
629 static Value getExtensionSource(Operation *op) {
630 if (isa_and_present<arith::ExtSIOp, arith::ExtUIOp, arith::ExtFOp>(op))
631 return op->getOperand(idx: 0);
632 return {};
633 }
634
635 LogicalResult matchAndRewrite(vector::TransposeOp transposeOp,
636 PatternRewriter &rewriter) const override {
637 auto sourceType = transposeOp.getSourceVectorType();
638 auto resultType = transposeOp.getResultVectorType();
639 if (isLegalVectorType(sourceType) || !isLegalVectorType(resultType))
640 return rewriter.notifyMatchFailure(transposeOp,
641 kMatchFailureNotIllegalToLegal);
642
643 // Look through extend for transfer_read.
644 Value maybeRead = transposeOp.getVector();
645 auto *transposeSourceOp = maybeRead.getDefiningOp();
646 Operation *extendOp = nullptr;
647 if (Value extendSource = getExtensionSource(op: transposeSourceOp)) {
648 maybeRead = extendSource;
649 extendOp = transposeSourceOp;
650 }
651
652 auto illegalRead = maybeRead.getDefiningOp<vector::TransferReadOp>();
653 if (!illegalRead)
654 return rewriter.notifyMatchFailure(
655 transposeOp,
656 "expected source to be (possibly extended) transfer_read");
657
658 if (!illegalRead.getPermutationMap().isIdentity())
659 return rewriter.notifyMatchFailure(
660 illegalRead, "expected read to have identity permutation map");
661
662 auto loc = transposeOp.getLoc();
663 auto zero = rewriter.create<arith::ConstantIndexOp>(loc, 0);
664 auto one = rewriter.create<arith::ConstantIndexOp>(loc, 1);
665
666 // Create a subview that matches the size of the illegal read vector type.
667 auto readType = illegalRead.getVectorType();
668 auto readSizes = llvm::map_to_vector(
669 llvm::zip_equal(readType.getShape(), readType.getScalableDims()),
670 [&](auto dim) -> Value {
671 auto [size, isScalable] = dim;
672 auto dimSize = rewriter.create<arith::ConstantIndexOp>(loc, size);
673 if (!isScalable)
674 return dimSize;
675 auto vscale = rewriter.create<vector::VectorScaleOp>(loc);
676 return rewriter.create<arith::MulIOp>(loc, vscale, dimSize);
677 });
678 SmallVector<Value> strides(readType.getRank(), Value(one));
679 auto readSubview = rewriter.create<memref::SubViewOp>(
680 loc, illegalRead.getBase(), illegalRead.getIndices(), readSizes,
681 strides);
682
683 // Apply the transpose to all values/attributes of the transfer_read:
684 // - The mask
685 Value mask = illegalRead.getMask();
686 if (mask) {
687 // Note: The transpose for the mask should fold into the
688 // vector.create_mask/constant_mask op, which will then become legal.
689 mask = rewriter.create<vector::TransposeOp>(loc, mask,
690 transposeOp.getPermutation());
691 }
692 // - The source memref
693 mlir::AffineMap transposeMap = AffineMap::getPermutationMap(
694 transposeOp.getPermutation(), getContext());
695 auto transposedSubview = rewriter.create<memref::TransposeOp>(
696 loc, readSubview, AffineMapAttr::get(transposeMap));
697 ArrayAttr inBoundsAttr = illegalRead.getInBoundsAttr();
698 // - The `in_bounds` attribute
699 if (inBoundsAttr) {
700 SmallVector<Attribute> inBoundsValues(inBoundsAttr.begin(),
701 inBoundsAttr.end());
702 applyPermutationToVector(inBoundsValues, transposeOp.getPermutation());
703 inBoundsAttr = rewriter.getArrayAttr(inBoundsValues);
704 }
705
706 VectorType legalReadType = resultType.clone(readType.getElementType());
707 // Note: The indices are all zero as the subview is already offset.
708 SmallVector<Value> readIndices(illegalRead.getIndices().size(), zero);
709 auto legalRead = rewriter.create<vector::TransferReadOp>(
710 loc, legalReadType, transposedSubview, readIndices,
711 illegalRead.getPermutationMapAttr(), illegalRead.getPadding(), mask,
712 inBoundsAttr);
713
714 // Replace the transpose with the new read, extending the result if
715 // necessary.
716 rewriter.replaceOp(transposeOp, [&]() -> Operation * {
717 if (extendOp)
718 return rewriter.create(loc, extendOp->getName().getIdentifier(),
719 Value(legalRead), resultType);
720 return legalRead;
721 }());
722
723 return success();
724 }
725};
726
727/// A rewrite to turn unit dim transpose-like vector.shape_casts into
728/// vector.transposes. The shape_cast has to be from an illegal vector type to a
729/// legal one (as defined by isLegalVectorType).
730///
731/// The reasoning for this is if we've got to this pass and we still have
732/// shape_casts of illegal types, then they likely will not cancel out. Turning
733/// them into transposes gives LiftIllegalVectorTransposeToMemory a chance to
734/// eliminate them.
735///
736/// Example:
737///
738/// BEFORE:
739/// ```mlir
740/// %0 = vector.shape_cast %a : vector<[4]x1xf32> to vector<1x[4]xf32>
741/// ```
742///
743/// AFTER:
744/// ```mlir
745/// %0 = vector.transpose %0, [1, 0] : vector<[4]x1xf32> to vector<1x[4]xf32>
746/// ```
747struct ConvertIllegalShapeCastOpsToTransposes
748 : public OpRewritePattern<vector::ShapeCastOp> {
749 using OpRewritePattern<vector::ShapeCastOp>::OpRewritePattern;
750
751 LogicalResult matchAndRewrite(vector::ShapeCastOp shapeCastOp,
752 PatternRewriter &rewriter) const override {
753 auto sourceType = shapeCastOp.getSourceVectorType();
754 auto resultType = shapeCastOp.getResultVectorType();
755 if (isLegalVectorType(sourceType) || !isLegalVectorType(resultType))
756 return rewriter.notifyMatchFailure(shapeCastOp,
757 kMatchFailureNotIllegalToLegal);
758
759 // Note: If we know that `sourceType` is an illegal vector type (and 2D)
760 // then dim 0 is scalable and dim 1 is fixed.
761 if (sourceType.getRank() != 2 || sourceType.getDimSize(1) != 1)
762 return rewriter.notifyMatchFailure(
763 shapeCastOp, "expected source to be a 2D scalable vector with a "
764 "trailing unit dim");
765
766 auto loc = shapeCastOp.getLoc();
767 auto transpose = rewriter.create<vector::TransposeOp>(
768 loc, shapeCastOp.getSource(), ArrayRef<int64_t>{1, 0});
769
770 if (resultType.getRank() == 1)
771 rewriter.replaceOpWithNewOp<vector::ShapeCastOp>(shapeCastOp, resultType,
772 transpose);
773 else
774 rewriter.replaceOp(shapeCastOp, transpose);
775
776 return success();
777 }
778};
779
780/// Rewrites an illegal/unsupported SVE transfer_write(transpose) to instead use
781/// the ZA state. This workaround rewrite to support these transposes when ZA is
782/// available.
783///
784/// Example:
785///
786/// BEFORE:
787/// ```mlir
788/// %transpose = vector.transpose %vec, [1, 0]
789/// : vector<2x[4]xf32> to vector<[4]x2xf32>
790/// vector.transfer_write %transpose, %dest[%y, %x]
791/// : vector<[4]x2xf32>, memref<?x?xf32>
792/// ```
793///
794/// AFTER:
795/// ```mlir
796/// %0 = arm_sme.get_tile : vector<[4]x[4]xf32>
797/// %1 = vector.extract %vec[0] : vector<[4]xf32> from vector<2x[4]xf32>
798/// %2 = vector.insert %1, %0 [0] : vector<[4]xf32> into vector<[4]x[4]xf32>
799/// %3 = vector.extract %vec[1] : vector<[4]xf32> from vector<2x[4]xf32>
800/// %4 = vector.insert %3, %2 [1] : vector<[4]xf32> into vector<[4]x[4]xf32>
801/// %c4_vscale = arith.muli %vscale, %c4 : index
802/// %mask = vector.create_mask %c4_vscale, %c2 : vector<[4]x[4]xi1>
803/// vector.transfer_write %4, %dest[%y, %x], %mask
804/// {permutation_map = affine_map<(d0, d1) -> (d1, d0)>}
805/// : vector<[4]x[4]xf32>, memref<?x?xf32>
806/// ```
807///
808/// Values larger than a single tile are supported via decomposition.
809struct LowerIllegalTransposeStoreViaZA
810 : public OpRewritePattern<vector::TransferWriteOp> {
811 using OpRewritePattern::OpRewritePattern;
812
813 LogicalResult matchAndRewrite(vector::TransferWriteOp writeOp,
814 PatternRewriter &rewriter) const override {
815 if (!isSupportedMaskOp(writeOp.getMask()))
816 return rewriter.notifyMatchFailure(writeOp,
817 kMatchFailureUnsupportedMaskOp);
818
819 auto permutationMap = writeOp.getPermutationMap();
820 if (!permutationMap.isIdentity())
821 return rewriter.notifyMatchFailure(writeOp,
822 kMatchFailureNonPermutationMap);
823
824 auto transposeOp = writeOp.getVector().getDefiningOp<vector::TransposeOp>();
825 if (!transposeOp)
826 return failure();
827
828 auto sourceType = transposeOp.getSourceVectorType();
829 auto resultType = transposeOp.getResultVectorType();
830
831 if (resultType.getRank() != 2)
832 return rewriter.notifyMatchFailure(transposeOp, "TransposeOp not rank 2");
833
834 if (!isLegalVectorType(sourceType) || isLegalVectorType(resultType))
835 return rewriter.notifyMatchFailure(
836 transposeOp, "not illegal/unsupported SVE transpose");
837
838 auto smeTileType = getSMETileTypeForElement(resultType.getElementType());
839 VectorType smeSliceType = VectorType::Builder(smeTileType).dropDim(0);
840
841 if (sourceType.getDimSize(0) <= 1 ||
842 sourceType.getDimSize(1) % smeSliceType.getDimSize(0) != 0)
843 return rewriter.notifyMatchFailure(writeOp, "unsupported source shape");
844
845 auto loc = writeOp.getLoc();
846 auto createVscaleMultiple =
847 vector::makeVscaleConstantBuilder(rewriter, loc: loc);
848
849 auto transposeMap = AffineMapAttr::get(
850 AffineMap::getPermutationMap(ArrayRef<int64_t>{1, 0}, getContext()));
851
852 // Note: We need to use `get_tile` as there's no vector-level `undef`.
853 Value undefTile = rewriter.create<arm_sme::GetTileOp>(loc, smeTileType);
854 Value destTensorOrMemref = writeOp.getBase();
855 auto numSlicesPerTile =
856 std::min(sourceType.getDimSize(0), smeTileType.getDimSize(0));
857 auto numSlices =
858 rewriter.create<arith::ConstantIndexOp>(loc, numSlicesPerTile);
859 for (auto [index, smeTile] : llvm::enumerate(
860 decomposeToSMETiles(rewriter, sourceType, smeTileType))) {
861 // 1. _Deliberately_ drop a scalable dimension and insert a fixed number
862 // of slices from the source type into the SME tile. Without checking
863 // vscale (and emitting multiple implementations) we can't make use of the
864 // rows of the tile after 1*vscale rows.
865 Value tile = undefTile;
866 for (int d = 0; d < numSlicesPerTile; ++d) {
867 Value vector = rewriter.create<vector::ExtractOp>(
868 loc, transposeOp.getVector(),
869 rewriter.getIndexAttr(d + smeTile.row));
870 if (vector.getType() != smeSliceType) {
871 vector = rewriter.create<vector::ScalableExtractOp>(
872 loc, smeSliceType, vector, smeTile.col);
873 }
874 tile = rewriter.create<vector::InsertOp>(loc, vector, tile, d);
875 }
876
877 // 2. Transpose the tile position.
878 auto transposedRow = createVscaleMultiple(smeTile.col);
879 auto transposedCol =
880 rewriter.create<arith::ConstantIndexOp>(loc, smeTile.row);
881
882 // 3. Compute mask for tile store.
883 Value maskRows;
884 Value maskCols;
885 if (auto mask = writeOp.getMask()) {
886 auto createMask = mask.getDefiningOp<vector::CreateMaskOp>();
887 maskRows = rewriter.create<arith::SubIOp>(loc, createMask.getOperand(0),
888 transposedRow);
889 maskCols = rewriter.create<arith::SubIOp>(loc, createMask.getOperand(1),
890 transposedCol);
891 maskCols = rewriter.create<index::MinSOp>(loc, maskCols, numSlices);
892 } else {
893 maskRows = createVscaleMultiple(smeTileType.getDimSize(0));
894 maskCols = numSlices;
895 }
896 auto subMask = rewriter.create<vector::CreateMaskOp>(
897 loc, smeTileType.clone(rewriter.getI1Type()),
898 ValueRange{maskRows, maskCols});
899
900 // 4. Emit a transposed tile write.
901 auto writeIndices = writeOp.getIndices();
902 Value destRow =
903 rewriter.create<arith::AddIOp>(loc, transposedRow, writeIndices[0]);
904 Value destCol =
905 rewriter.create<arith::AddIOp>(loc, transposedCol, writeIndices[1]);
906 auto smeWrite = rewriter.create<vector::TransferWriteOp>(
907 loc, tile, destTensorOrMemref, ValueRange{destRow, destCol},
908 transposeMap, subMask, writeOp.getInBounds());
909
910 if (writeOp.hasPureTensorSemantics())
911 destTensorOrMemref = smeWrite.getResult();
912 }
913
914 if (writeOp.hasPureTensorSemantics())
915 rewriter.replaceOp(writeOp, destTensorOrMemref);
916 else
917 rewriter.eraseOp(op: writeOp);
918
919 return success();
920 }
921};
922
923struct VectorLegalizationPass
924 : public arm_sme::impl::VectorLegalizationBase<VectorLegalizationPass> {
925 void runOnOperation() override {
926 auto *context = &getContext();
927 TypeConverter converter;
928 RewritePatternSet patterns(context);
929 converter.addConversion(callback: [](Type type) { return type; });
930 converter.addConversion(
931 callback: [](VectorType vectorType,
932 SmallVectorImpl<Type> &types) -> std::optional<LogicalResult> {
933 if (!isMultipleOfSMETileVectorType(vectorType))
934 return std::nullopt;
935 auto smeTileCount = getNumberOfSMETilesForVectorType(vectorType);
936 auto smeTileType =
937 getSMETileTypeForElement(vectorType.getElementType());
938 types = SmallVector<Type>(smeTileCount, smeTileType);
939 return success();
940 });
941
942 // Apply preprocessing patterns.
943 RewritePatternSet rewritePatterns(context);
944 rewritePatterns.add<FoldExtractFromVectorOfSMELikeCreateMasks,
945 LiftIllegalVectorTransposeToMemory,
946 ConvertIllegalShapeCastOpsToTransposes,
947 LowerIllegalTransposeStoreViaZA>(context);
948 if (failed(
949 applyPatternsGreedily(getOperation(), std::move(rewritePatterns))))
950 return signalPassFailure();
951
952 // Note: These two patterns are added with a high benefit to ensure:
953 // - Masked outer products are handled before unmasked ones
954 // - Multi-tile writes are lowered as a store loop (if possible)
955 patterns.add<LegalizeMaskedVectorOuterProductOpsByDecomposition,
956 LegalizeMultiTileTransferWriteAsStoreLoop>(converter, context,
957 /*benefit=*/1024);
958 patterns.add<LegalizeArithConstantOpsByDecomposition,
959 LegalizeVectorOuterProductOpsByDecomposition,
960 LegalizeTransferReadOpsByDecomposition,
961 LegalizeTransferWriteOpsByDecomposition>(converter, context);
962 populateFunctionOpInterfaceTypeConversionPattern<func::FuncOp>(patterns,
963 converter);
964 populateCallOpTypeConversionPattern(patterns, converter);
965 populateReturnOpTypeConversionPattern(patterns, converter);
966 scf::populateSCFStructuralTypeConversions(typeConverter: converter, patterns);
967
968 ConversionTarget target(getContext());
969 target.markUnknownOpDynamicallyLegal(
970 fn: [&](Operation *op) { return converter.isLegal(op); });
971 target.addDynamicallyLegalOp<func::FuncOp>([&](func::FuncOp op) {
972 return converter.isSignatureLegal(op.getFunctionType());
973 });
974 if (failed(applyPartialConversion(getOperation(), target,
975 std::move(patterns))))
976 return signalPassFailure();
977 }
978};
979
980} // namespace
981
982std::unique_ptr<Pass> mlir::arm_sme::createVectorLegalizationPass() {
983 return std::make_unique<VectorLegalizationPass>();
984}
985

source code of mlir/lib/Dialect/ArmSME/Transforms/VectorLegalization.cpp