xref: /llvm-project/mlir/lib/Conversion/VectorToLLVM/ConvertVectorToLLVM.cpp (revision e8dcf5f87dc20b3f08005ac767ff934e36bf2a5b)
1 //===- VectorToLLVM.cpp - Conversion from Vector to the LLVM dialect ------===//
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 #include "mlir/Conversion/VectorToLLVM/ConvertVectorToLLVM.h"
10 
11 #include "../PassDetail.h"
12 #include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVM.h"
13 #include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVMPass.h"
14 #include "mlir/Dialect/LLVMIR/LLVMDialect.h"
15 #include "mlir/Dialect/StandardOps/IR/Ops.h"
16 #include "mlir/Dialect/Vector/VectorOps.h"
17 #include "mlir/IR/AffineMap.h"
18 #include "mlir/IR/Attributes.h"
19 #include "mlir/IR/Builders.h"
20 #include "mlir/IR/MLIRContext.h"
21 #include "mlir/IR/Module.h"
22 #include "mlir/IR/Operation.h"
23 #include "mlir/IR/PatternMatch.h"
24 #include "mlir/IR/StandardTypes.h"
25 #include "mlir/IR/Types.h"
26 #include "mlir/Target/LLVMIR/TypeTranslation.h"
27 #include "mlir/Transforms/DialectConversion.h"
28 #include "mlir/Transforms/Passes.h"
29 #include "llvm/IR/DerivedTypes.h"
30 #include "llvm/IR/Module.h"
31 #include "llvm/IR/Type.h"
32 #include "llvm/Support/Allocator.h"
33 #include "llvm/Support/ErrorHandling.h"
34 
35 using namespace mlir;
36 using namespace mlir::vector;
37 
38 // Helper to reduce vector type by one rank at front.
39 static VectorType reducedVectorTypeFront(VectorType tp) {
40   assert((tp.getRank() > 1) && "unlowerable vector type");
41   return VectorType::get(tp.getShape().drop_front(), tp.getElementType());
42 }
43 
44 // Helper to reduce vector type by *all* but one rank at back.
45 static VectorType reducedVectorTypeBack(VectorType tp) {
46   assert((tp.getRank() > 1) && "unlowerable vector type");
47   return VectorType::get(tp.getShape().take_back(), tp.getElementType());
48 }
49 
50 // Helper that picks the proper sequence for inserting.
51 static Value insertOne(ConversionPatternRewriter &rewriter,
52                        LLVMTypeConverter &typeConverter, Location loc,
53                        Value val1, Value val2, Type llvmType, int64_t rank,
54                        int64_t pos) {
55   if (rank == 1) {
56     auto idxType = rewriter.getIndexType();
57     auto constant = rewriter.create<LLVM::ConstantOp>(
58         loc, typeConverter.convertType(idxType),
59         rewriter.getIntegerAttr(idxType, pos));
60     return rewriter.create<LLVM::InsertElementOp>(loc, llvmType, val1, val2,
61                                                   constant);
62   }
63   return rewriter.create<LLVM::InsertValueOp>(loc, llvmType, val1, val2,
64                                               rewriter.getI64ArrayAttr(pos));
65 }
66 
67 // Helper that picks the proper sequence for inserting.
68 static Value insertOne(PatternRewriter &rewriter, Location loc, Value from,
69                        Value into, int64_t offset) {
70   auto vectorType = into.getType().cast<VectorType>();
71   if (vectorType.getRank() > 1)
72     return rewriter.create<InsertOp>(loc, from, into, offset);
73   return rewriter.create<vector::InsertElementOp>(
74       loc, vectorType, from, into,
75       rewriter.create<ConstantIndexOp>(loc, offset));
76 }
77 
78 // Helper that picks the proper sequence for extracting.
79 static Value extractOne(ConversionPatternRewriter &rewriter,
80                         LLVMTypeConverter &typeConverter, Location loc,
81                         Value val, Type llvmType, int64_t rank, int64_t pos) {
82   if (rank == 1) {
83     auto idxType = rewriter.getIndexType();
84     auto constant = rewriter.create<LLVM::ConstantOp>(
85         loc, typeConverter.convertType(idxType),
86         rewriter.getIntegerAttr(idxType, pos));
87     return rewriter.create<LLVM::ExtractElementOp>(loc, llvmType, val,
88                                                    constant);
89   }
90   return rewriter.create<LLVM::ExtractValueOp>(loc, llvmType, val,
91                                                rewriter.getI64ArrayAttr(pos));
92 }
93 
94 // Helper that picks the proper sequence for extracting.
95 static Value extractOne(PatternRewriter &rewriter, Location loc, Value vector,
96                         int64_t offset) {
97   auto vectorType = vector.getType().cast<VectorType>();
98   if (vectorType.getRank() > 1)
99     return rewriter.create<ExtractOp>(loc, vector, offset);
100   return rewriter.create<vector::ExtractElementOp>(
101       loc, vectorType.getElementType(), vector,
102       rewriter.create<ConstantIndexOp>(loc, offset));
103 }
104 
105 // Helper that returns a subset of `arrayAttr` as a vector of int64_t.
106 // TODO: Better support for attribute subtype forwarding + slicing.
107 static SmallVector<int64_t, 4> getI64SubArray(ArrayAttr arrayAttr,
108                                               unsigned dropFront = 0,
109                                               unsigned dropBack = 0) {
110   assert(arrayAttr.size() > dropFront + dropBack && "Out of bounds");
111   auto range = arrayAttr.getAsRange<IntegerAttr>();
112   SmallVector<int64_t, 4> res;
113   res.reserve(arrayAttr.size() - dropFront - dropBack);
114   for (auto it = range.begin() + dropFront, eit = range.end() - dropBack;
115        it != eit; ++it)
116     res.push_back((*it).getValue().getSExtValue());
117   return res;
118 }
119 
120 // Helper that returns data layout alignment of an operation with memref.
121 template <typename T>
122 LogicalResult getMemRefAlignment(LLVMTypeConverter &typeConverter, T op,
123                                  unsigned &align) {
124   Type elementTy =
125       typeConverter.convertType(op.getMemRefType().getElementType());
126   if (!elementTy)
127     return failure();
128 
129   auto dataLayout = typeConverter.getDialect()->getLLVMModule().getDataLayout();
130   // TODO: this should be abstracted away to avoid depending on translation.
131   align = dataLayout.getPrefTypeAlignment(LLVM::translateTypeToLLVMIR(
132       elementTy.cast<LLVM::LLVMType>(),
133       typeConverter.getDialect()->getLLVMContext()));
134   return success();
135 }
136 
137 // Helper that returns the base address of a memref.
138 LogicalResult getBase(ConversionPatternRewriter &rewriter, Location loc,
139                       Value memref, MemRefType memRefType, Value &base) {
140   // Inspect stride and offset structure.
141   //
142   // TODO: flat memory only for now, generalize
143   //
144   int64_t offset;
145   SmallVector<int64_t, 4> strides;
146   auto successStrides = getStridesAndOffset(memRefType, strides, offset);
147   if (failed(successStrides) || strides.size() != 1 || strides[0] != 1 ||
148       offset != 0 || memRefType.getMemorySpace() != 0)
149     return failure();
150   base = MemRefDescriptor(memref).alignedPtr(rewriter, loc);
151   return success();
152 }
153 
154 // Helper that returns a pointer given a memref base.
155 LogicalResult getBasePtr(ConversionPatternRewriter &rewriter, Location loc,
156                          Value memref, MemRefType memRefType, Value &ptr) {
157   Value base;
158   if (failed(getBase(rewriter, loc, memref, memRefType, base)))
159     return failure();
160   auto pType = MemRefDescriptor(memref).getElementType();
161   ptr = rewriter.create<LLVM::GEPOp>(loc, pType, base);
162   return success();
163 }
164 
165 // Helper that returns vector of pointers given a memref base and an index
166 // vector.
167 LogicalResult getIndexedPtrs(ConversionPatternRewriter &rewriter, Location loc,
168                              Value memref, Value indices, MemRefType memRefType,
169                              VectorType vType, Type iType, Value &ptrs) {
170   Value base;
171   if (failed(getBase(rewriter, loc, memref, memRefType, base)))
172     return failure();
173   auto pType = MemRefDescriptor(memref).getElementType();
174   auto ptrsType = LLVM::LLVMType::getVectorTy(pType, vType.getDimSize(0));
175   ptrs = rewriter.create<LLVM::GEPOp>(loc, ptrsType, base, indices);
176   return success();
177 }
178 
179 static LogicalResult
180 replaceTransferOpWithLoadOrStore(ConversionPatternRewriter &rewriter,
181                                  LLVMTypeConverter &typeConverter, Location loc,
182                                  TransferReadOp xferOp,
183                                  ArrayRef<Value> operands, Value dataPtr) {
184   unsigned align;
185   if (failed(getMemRefAlignment(typeConverter, xferOp, align)))
186     return failure();
187   rewriter.replaceOpWithNewOp<LLVM::LoadOp>(xferOp, dataPtr, align);
188   return success();
189 }
190 
191 static LogicalResult
192 replaceTransferOpWithMasked(ConversionPatternRewriter &rewriter,
193                             LLVMTypeConverter &typeConverter, Location loc,
194                             TransferReadOp xferOp, ArrayRef<Value> operands,
195                             Value dataPtr, Value mask) {
196   auto toLLVMTy = [&](Type t) { return typeConverter.convertType(t); };
197   VectorType fillType = xferOp.getVectorType();
198   Value fill = rewriter.create<SplatOp>(loc, fillType, xferOp.padding());
199   fill = rewriter.create<LLVM::DialectCastOp>(loc, toLLVMTy(fillType), fill);
200 
201   Type vecTy = typeConverter.convertType(xferOp.getVectorType());
202   if (!vecTy)
203     return failure();
204 
205   unsigned align;
206   if (failed(getMemRefAlignment(typeConverter, xferOp, align)))
207     return failure();
208 
209   rewriter.replaceOpWithNewOp<LLVM::MaskedLoadOp>(
210       xferOp, vecTy, dataPtr, mask, ValueRange{fill},
211       rewriter.getI32IntegerAttr(align));
212   return success();
213 }
214 
215 static LogicalResult
216 replaceTransferOpWithLoadOrStore(ConversionPatternRewriter &rewriter,
217                                  LLVMTypeConverter &typeConverter, Location loc,
218                                  TransferWriteOp xferOp,
219                                  ArrayRef<Value> operands, Value dataPtr) {
220   unsigned align;
221   if (failed(getMemRefAlignment(typeConverter, xferOp, align)))
222     return failure();
223   auto adaptor = TransferWriteOpAdaptor(operands);
224   rewriter.replaceOpWithNewOp<LLVM::StoreOp>(xferOp, adaptor.vector(), dataPtr,
225                                              align);
226   return success();
227 }
228 
229 static LogicalResult
230 replaceTransferOpWithMasked(ConversionPatternRewriter &rewriter,
231                             LLVMTypeConverter &typeConverter, Location loc,
232                             TransferWriteOp xferOp, ArrayRef<Value> operands,
233                             Value dataPtr, Value mask) {
234   unsigned align;
235   if (failed(getMemRefAlignment(typeConverter, xferOp, align)))
236     return failure();
237 
238   auto adaptor = TransferWriteOpAdaptor(operands);
239   rewriter.replaceOpWithNewOp<LLVM::MaskedStoreOp>(
240       xferOp, adaptor.vector(), dataPtr, mask,
241       rewriter.getI32IntegerAttr(align));
242   return success();
243 }
244 
245 static TransferReadOpAdaptor getTransferOpAdapter(TransferReadOp xferOp,
246                                                   ArrayRef<Value> operands) {
247   return TransferReadOpAdaptor(operands);
248 }
249 
250 static TransferWriteOpAdaptor getTransferOpAdapter(TransferWriteOp xferOp,
251                                                    ArrayRef<Value> operands) {
252   return TransferWriteOpAdaptor(operands);
253 }
254 
255 namespace {
256 
257 /// Conversion pattern for a vector.matrix_multiply.
258 /// This is lowered directly to the proper llvm.intr.matrix.multiply.
259 class VectorMatmulOpConversion : public ConvertToLLVMPattern {
260 public:
261   explicit VectorMatmulOpConversion(MLIRContext *context,
262                                     LLVMTypeConverter &typeConverter)
263       : ConvertToLLVMPattern(vector::MatmulOp::getOperationName(), context,
264                              typeConverter) {}
265 
266   LogicalResult
267   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
268                   ConversionPatternRewriter &rewriter) const override {
269     auto matmulOp = cast<vector::MatmulOp>(op);
270     auto adaptor = vector::MatmulOpAdaptor(operands);
271     rewriter.replaceOpWithNewOp<LLVM::MatrixMultiplyOp>(
272         op, typeConverter.convertType(matmulOp.res().getType()), adaptor.lhs(),
273         adaptor.rhs(), matmulOp.lhs_rows(), matmulOp.lhs_columns(),
274         matmulOp.rhs_columns());
275     return success();
276   }
277 };
278 
279 /// Conversion pattern for a vector.flat_transpose.
280 /// This is lowered directly to the proper llvm.intr.matrix.transpose.
281 class VectorFlatTransposeOpConversion : public ConvertToLLVMPattern {
282 public:
283   explicit VectorFlatTransposeOpConversion(MLIRContext *context,
284                                            LLVMTypeConverter &typeConverter)
285       : ConvertToLLVMPattern(vector::FlatTransposeOp::getOperationName(),
286                              context, typeConverter) {}
287 
288   LogicalResult
289   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
290                   ConversionPatternRewriter &rewriter) const override {
291     auto transOp = cast<vector::FlatTransposeOp>(op);
292     auto adaptor = vector::FlatTransposeOpAdaptor(operands);
293     rewriter.replaceOpWithNewOp<LLVM::MatrixTransposeOp>(
294         transOp, typeConverter.convertType(transOp.res().getType()),
295         adaptor.matrix(), transOp.rows(), transOp.columns());
296     return success();
297   }
298 };
299 
300 /// Conversion pattern for a vector.gather.
301 class VectorGatherOpConversion : public ConvertToLLVMPattern {
302 public:
303   explicit VectorGatherOpConversion(MLIRContext *context,
304                                     LLVMTypeConverter &typeConverter)
305       : ConvertToLLVMPattern(vector::GatherOp::getOperationName(), context,
306                              typeConverter) {}
307 
308   LogicalResult
309   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
310                   ConversionPatternRewriter &rewriter) const override {
311     auto loc = op->getLoc();
312     auto gather = cast<vector::GatherOp>(op);
313     auto adaptor = vector::GatherOpAdaptor(operands);
314 
315     // Resolve alignment.
316     unsigned align;
317     if (failed(getMemRefAlignment(typeConverter, gather, align)))
318       return failure();
319 
320     // Get index ptrs.
321     VectorType vType = gather.getResultVectorType();
322     Type iType = gather.getIndicesVectorType().getElementType();
323     Value ptrs;
324     if (failed(getIndexedPtrs(rewriter, loc, adaptor.base(), adaptor.indices(),
325                               gather.getMemRefType(), vType, iType, ptrs)))
326       return failure();
327 
328     // Replace with the gather intrinsic.
329     ValueRange v = (llvm::size(adaptor.pass_thru()) == 0) ? ValueRange({})
330                                                           : adaptor.pass_thru();
331     rewriter.replaceOpWithNewOp<LLVM::masked_gather>(
332         gather, typeConverter.convertType(vType), ptrs, adaptor.mask(), v,
333         rewriter.getI32IntegerAttr(align));
334     return success();
335   }
336 };
337 
338 /// Conversion pattern for a vector.scatter.
339 class VectorScatterOpConversion : public ConvertToLLVMPattern {
340 public:
341   explicit VectorScatterOpConversion(MLIRContext *context,
342                                      LLVMTypeConverter &typeConverter)
343       : ConvertToLLVMPattern(vector::ScatterOp::getOperationName(), context,
344                              typeConverter) {}
345 
346   LogicalResult
347   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
348                   ConversionPatternRewriter &rewriter) const override {
349     auto loc = op->getLoc();
350     auto scatter = cast<vector::ScatterOp>(op);
351     auto adaptor = vector::ScatterOpAdaptor(operands);
352 
353     // Resolve alignment.
354     unsigned align;
355     if (failed(getMemRefAlignment(typeConverter, scatter, align)))
356       return failure();
357 
358     // Get index ptrs.
359     VectorType vType = scatter.getValueVectorType();
360     Type iType = scatter.getIndicesVectorType().getElementType();
361     Value ptrs;
362     if (failed(getIndexedPtrs(rewriter, loc, adaptor.base(), adaptor.indices(),
363                               scatter.getMemRefType(), vType, iType, ptrs)))
364       return failure();
365 
366     // Replace with the scatter intrinsic.
367     rewriter.replaceOpWithNewOp<LLVM::masked_scatter>(
368         scatter, adaptor.value(), ptrs, adaptor.mask(),
369         rewriter.getI32IntegerAttr(align));
370     return success();
371   }
372 };
373 
374 /// Conversion pattern for a vector.expandload.
375 class VectorExpandLoadOpConversion : public ConvertToLLVMPattern {
376 public:
377   explicit VectorExpandLoadOpConversion(MLIRContext *context,
378                                         LLVMTypeConverter &typeConverter)
379       : ConvertToLLVMPattern(vector::ExpandLoadOp::getOperationName(), context,
380                              typeConverter) {}
381 
382   LogicalResult
383   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
384                   ConversionPatternRewriter &rewriter) const override {
385     auto loc = op->getLoc();
386     auto expand = cast<vector::ExpandLoadOp>(op);
387     auto adaptor = vector::ExpandLoadOpAdaptor(operands);
388 
389     Value ptr;
390     if (failed(getBasePtr(rewriter, loc, adaptor.base(), expand.getMemRefType(),
391                           ptr)))
392       return failure();
393 
394     auto vType = expand.getResultVectorType();
395     rewriter.replaceOpWithNewOp<LLVM::masked_expandload>(
396         op, typeConverter.convertType(vType), ptr, adaptor.mask(),
397         adaptor.pass_thru());
398     return success();
399   }
400 };
401 
402 /// Conversion pattern for a vector.compressstore.
403 class VectorCompressStoreOpConversion : public ConvertToLLVMPattern {
404 public:
405   explicit VectorCompressStoreOpConversion(MLIRContext *context,
406                                            LLVMTypeConverter &typeConverter)
407       : ConvertToLLVMPattern(vector::CompressStoreOp::getOperationName(),
408                              context, typeConverter) {}
409 
410   LogicalResult
411   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
412                   ConversionPatternRewriter &rewriter) const override {
413     auto loc = op->getLoc();
414     auto compress = cast<vector::CompressStoreOp>(op);
415     auto adaptor = vector::CompressStoreOpAdaptor(operands);
416 
417     Value ptr;
418     if (failed(getBasePtr(rewriter, loc, adaptor.base(),
419                           compress.getMemRefType(), ptr)))
420       return failure();
421 
422     rewriter.replaceOpWithNewOp<LLVM::masked_compressstore>(
423         op, adaptor.value(), ptr, adaptor.mask());
424     return success();
425   }
426 };
427 
428 /// Conversion pattern for all vector reductions.
429 class VectorReductionOpConversion : public ConvertToLLVMPattern {
430 public:
431   explicit VectorReductionOpConversion(MLIRContext *context,
432                                        LLVMTypeConverter &typeConverter,
433                                        bool reassociateFP)
434       : ConvertToLLVMPattern(vector::ReductionOp::getOperationName(), context,
435                              typeConverter),
436         reassociateFPReductions(reassociateFP) {}
437 
438   LogicalResult
439   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
440                   ConversionPatternRewriter &rewriter) const override {
441     auto reductionOp = cast<vector::ReductionOp>(op);
442     auto kind = reductionOp.kind();
443     Type eltType = reductionOp.dest().getType();
444     Type llvmType = typeConverter.convertType(eltType);
445     if (eltType.isSignlessInteger(32) || eltType.isSignlessInteger(64)) {
446       // Integer reductions: add/mul/min/max/and/or/xor.
447       if (kind == "add")
448         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_add>(
449             op, llvmType, operands[0]);
450       else if (kind == "mul")
451         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_mul>(
452             op, llvmType, operands[0]);
453       else if (kind == "min")
454         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_smin>(
455             op, llvmType, operands[0]);
456       else if (kind == "max")
457         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_smax>(
458             op, llvmType, operands[0]);
459       else if (kind == "and")
460         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_and>(
461             op, llvmType, operands[0]);
462       else if (kind == "or")
463         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_or>(
464             op, llvmType, operands[0]);
465       else if (kind == "xor")
466         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_xor>(
467             op, llvmType, operands[0]);
468       else
469         return failure();
470       return success();
471 
472     } else if (eltType.isF32() || eltType.isF64()) {
473       // Floating-point reductions: add/mul/min/max
474       if (kind == "add") {
475         // Optional accumulator (or zero).
476         Value acc = operands.size() > 1 ? operands[1]
477                                         : rewriter.create<LLVM::ConstantOp>(
478                                               op->getLoc(), llvmType,
479                                               rewriter.getZeroAttr(eltType));
480         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_v2_fadd>(
481             op, llvmType, acc, operands[0],
482             rewriter.getBoolAttr(reassociateFPReductions));
483       } else if (kind == "mul") {
484         // Optional accumulator (or one).
485         Value acc = operands.size() > 1
486                         ? operands[1]
487                         : rewriter.create<LLVM::ConstantOp>(
488                               op->getLoc(), llvmType,
489                               rewriter.getFloatAttr(eltType, 1.0));
490         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_v2_fmul>(
491             op, llvmType, acc, operands[0],
492             rewriter.getBoolAttr(reassociateFPReductions));
493       } else if (kind == "min")
494         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_fmin>(
495             op, llvmType, operands[0]);
496       else if (kind == "max")
497         rewriter.replaceOpWithNewOp<LLVM::experimental_vector_reduce_fmax>(
498             op, llvmType, operands[0]);
499       else
500         return failure();
501       return success();
502     }
503     return failure();
504   }
505 
506 private:
507   const bool reassociateFPReductions;
508 };
509 
510 class VectorShuffleOpConversion : public ConvertToLLVMPattern {
511 public:
512   explicit VectorShuffleOpConversion(MLIRContext *context,
513                                      LLVMTypeConverter &typeConverter)
514       : ConvertToLLVMPattern(vector::ShuffleOp::getOperationName(), context,
515                              typeConverter) {}
516 
517   LogicalResult
518   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
519                   ConversionPatternRewriter &rewriter) const override {
520     auto loc = op->getLoc();
521     auto adaptor = vector::ShuffleOpAdaptor(operands);
522     auto shuffleOp = cast<vector::ShuffleOp>(op);
523     auto v1Type = shuffleOp.getV1VectorType();
524     auto v2Type = shuffleOp.getV2VectorType();
525     auto vectorType = shuffleOp.getVectorType();
526     Type llvmType = typeConverter.convertType(vectorType);
527     auto maskArrayAttr = shuffleOp.mask();
528 
529     // Bail if result type cannot be lowered.
530     if (!llvmType)
531       return failure();
532 
533     // Get rank and dimension sizes.
534     int64_t rank = vectorType.getRank();
535     assert(v1Type.getRank() == rank);
536     assert(v2Type.getRank() == rank);
537     int64_t v1Dim = v1Type.getDimSize(0);
538 
539     // For rank 1, where both operands have *exactly* the same vector type,
540     // there is direct shuffle support in LLVM. Use it!
541     if (rank == 1 && v1Type == v2Type) {
542       Value shuffle = rewriter.create<LLVM::ShuffleVectorOp>(
543           loc, adaptor.v1(), adaptor.v2(), maskArrayAttr);
544       rewriter.replaceOp(op, shuffle);
545       return success();
546     }
547 
548     // For all other cases, insert the individual values individually.
549     Value insert = rewriter.create<LLVM::UndefOp>(loc, llvmType);
550     int64_t insPos = 0;
551     for (auto en : llvm::enumerate(maskArrayAttr)) {
552       int64_t extPos = en.value().cast<IntegerAttr>().getInt();
553       Value value = adaptor.v1();
554       if (extPos >= v1Dim) {
555         extPos -= v1Dim;
556         value = adaptor.v2();
557       }
558       Value extract = extractOne(rewriter, typeConverter, loc, value, llvmType,
559                                  rank, extPos);
560       insert = insertOne(rewriter, typeConverter, loc, insert, extract,
561                          llvmType, rank, insPos++);
562     }
563     rewriter.replaceOp(op, insert);
564     return success();
565   }
566 };
567 
568 class VectorExtractElementOpConversion : public ConvertToLLVMPattern {
569 public:
570   explicit VectorExtractElementOpConversion(MLIRContext *context,
571                                             LLVMTypeConverter &typeConverter)
572       : ConvertToLLVMPattern(vector::ExtractElementOp::getOperationName(),
573                              context, typeConverter) {}
574 
575   LogicalResult
576   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
577                   ConversionPatternRewriter &rewriter) const override {
578     auto adaptor = vector::ExtractElementOpAdaptor(operands);
579     auto extractEltOp = cast<vector::ExtractElementOp>(op);
580     auto vectorType = extractEltOp.getVectorType();
581     auto llvmType = typeConverter.convertType(vectorType.getElementType());
582 
583     // Bail if result type cannot be lowered.
584     if (!llvmType)
585       return failure();
586 
587     rewriter.replaceOpWithNewOp<LLVM::ExtractElementOp>(
588         op, llvmType, adaptor.vector(), adaptor.position());
589     return success();
590   }
591 };
592 
593 class VectorExtractOpConversion : public ConvertToLLVMPattern {
594 public:
595   explicit VectorExtractOpConversion(MLIRContext *context,
596                                      LLVMTypeConverter &typeConverter)
597       : ConvertToLLVMPattern(vector::ExtractOp::getOperationName(), context,
598                              typeConverter) {}
599 
600   LogicalResult
601   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
602                   ConversionPatternRewriter &rewriter) const override {
603     auto loc = op->getLoc();
604     auto adaptor = vector::ExtractOpAdaptor(operands);
605     auto extractOp = cast<vector::ExtractOp>(op);
606     auto vectorType = extractOp.getVectorType();
607     auto resultType = extractOp.getResult().getType();
608     auto llvmResultType = typeConverter.convertType(resultType);
609     auto positionArrayAttr = extractOp.position();
610 
611     // Bail if result type cannot be lowered.
612     if (!llvmResultType)
613       return failure();
614 
615     // One-shot extraction of vector from array (only requires extractvalue).
616     if (resultType.isa<VectorType>()) {
617       Value extracted = rewriter.create<LLVM::ExtractValueOp>(
618           loc, llvmResultType, adaptor.vector(), positionArrayAttr);
619       rewriter.replaceOp(op, extracted);
620       return success();
621     }
622 
623     // Potential extraction of 1-D vector from array.
624     auto *context = op->getContext();
625     Value extracted = adaptor.vector();
626     auto positionAttrs = positionArrayAttr.getValue();
627     if (positionAttrs.size() > 1) {
628       auto oneDVectorType = reducedVectorTypeBack(vectorType);
629       auto nMinusOnePositionAttrs =
630           ArrayAttr::get(positionAttrs.drop_back(), context);
631       extracted = rewriter.create<LLVM::ExtractValueOp>(
632           loc, typeConverter.convertType(oneDVectorType), extracted,
633           nMinusOnePositionAttrs);
634     }
635 
636     // Remaining extraction of element from 1-D LLVM vector
637     auto position = positionAttrs.back().cast<IntegerAttr>();
638     auto i64Type = LLVM::LLVMType::getInt64Ty(typeConverter.getDialect());
639     auto constant = rewriter.create<LLVM::ConstantOp>(loc, i64Type, position);
640     extracted =
641         rewriter.create<LLVM::ExtractElementOp>(loc, extracted, constant);
642     rewriter.replaceOp(op, extracted);
643 
644     return success();
645   }
646 };
647 
648 /// Conversion pattern that turns a vector.fma on a 1-D vector
649 /// into an llvm.intr.fmuladd. This is a trivial 1-1 conversion.
650 /// This does not match vectors of n >= 2 rank.
651 ///
652 /// Example:
653 /// ```
654 ///  vector.fma %a, %a, %a : vector<8xf32>
655 /// ```
656 /// is converted to:
657 /// ```
658 ///  llvm.intr.fmuladd %va, %va, %va:
659 ///    (!llvm<"<8 x float>">, !llvm<"<8 x float>">, !llvm<"<8 x float>">)
660 ///    -> !llvm<"<8 x float>">
661 /// ```
662 class VectorFMAOp1DConversion : public ConvertToLLVMPattern {
663 public:
664   explicit VectorFMAOp1DConversion(MLIRContext *context,
665                                    LLVMTypeConverter &typeConverter)
666       : ConvertToLLVMPattern(vector::FMAOp::getOperationName(), context,
667                              typeConverter) {}
668 
669   LogicalResult
670   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
671                   ConversionPatternRewriter &rewriter) const override {
672     auto adaptor = vector::FMAOpAdaptor(operands);
673     vector::FMAOp fmaOp = cast<vector::FMAOp>(op);
674     VectorType vType = fmaOp.getVectorType();
675     if (vType.getRank() != 1)
676       return failure();
677     rewriter.replaceOpWithNewOp<LLVM::FMulAddOp>(op, adaptor.lhs(),
678                                                  adaptor.rhs(), adaptor.acc());
679     return success();
680   }
681 };
682 
683 class VectorInsertElementOpConversion : public ConvertToLLVMPattern {
684 public:
685   explicit VectorInsertElementOpConversion(MLIRContext *context,
686                                            LLVMTypeConverter &typeConverter)
687       : ConvertToLLVMPattern(vector::InsertElementOp::getOperationName(),
688                              context, typeConverter) {}
689 
690   LogicalResult
691   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
692                   ConversionPatternRewriter &rewriter) const override {
693     auto adaptor = vector::InsertElementOpAdaptor(operands);
694     auto insertEltOp = cast<vector::InsertElementOp>(op);
695     auto vectorType = insertEltOp.getDestVectorType();
696     auto llvmType = typeConverter.convertType(vectorType);
697 
698     // Bail if result type cannot be lowered.
699     if (!llvmType)
700       return failure();
701 
702     rewriter.replaceOpWithNewOp<LLVM::InsertElementOp>(
703         op, llvmType, adaptor.dest(), adaptor.source(), adaptor.position());
704     return success();
705   }
706 };
707 
708 class VectorInsertOpConversion : public ConvertToLLVMPattern {
709 public:
710   explicit VectorInsertOpConversion(MLIRContext *context,
711                                     LLVMTypeConverter &typeConverter)
712       : ConvertToLLVMPattern(vector::InsertOp::getOperationName(), context,
713                              typeConverter) {}
714 
715   LogicalResult
716   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
717                   ConversionPatternRewriter &rewriter) const override {
718     auto loc = op->getLoc();
719     auto adaptor = vector::InsertOpAdaptor(operands);
720     auto insertOp = cast<vector::InsertOp>(op);
721     auto sourceType = insertOp.getSourceType();
722     auto destVectorType = insertOp.getDestVectorType();
723     auto llvmResultType = typeConverter.convertType(destVectorType);
724     auto positionArrayAttr = insertOp.position();
725 
726     // Bail if result type cannot be lowered.
727     if (!llvmResultType)
728       return failure();
729 
730     // One-shot insertion of a vector into an array (only requires insertvalue).
731     if (sourceType.isa<VectorType>()) {
732       Value inserted = rewriter.create<LLVM::InsertValueOp>(
733           loc, llvmResultType, adaptor.dest(), adaptor.source(),
734           positionArrayAttr);
735       rewriter.replaceOp(op, inserted);
736       return success();
737     }
738 
739     // Potential extraction of 1-D vector from array.
740     auto *context = op->getContext();
741     Value extracted = adaptor.dest();
742     auto positionAttrs = positionArrayAttr.getValue();
743     auto position = positionAttrs.back().cast<IntegerAttr>();
744     auto oneDVectorType = destVectorType;
745     if (positionAttrs.size() > 1) {
746       oneDVectorType = reducedVectorTypeBack(destVectorType);
747       auto nMinusOnePositionAttrs =
748           ArrayAttr::get(positionAttrs.drop_back(), context);
749       extracted = rewriter.create<LLVM::ExtractValueOp>(
750           loc, typeConverter.convertType(oneDVectorType), extracted,
751           nMinusOnePositionAttrs);
752     }
753 
754     // Insertion of an element into a 1-D LLVM vector.
755     auto i64Type = LLVM::LLVMType::getInt64Ty(typeConverter.getDialect());
756     auto constant = rewriter.create<LLVM::ConstantOp>(loc, i64Type, position);
757     Value inserted = rewriter.create<LLVM::InsertElementOp>(
758         loc, typeConverter.convertType(oneDVectorType), extracted,
759         adaptor.source(), constant);
760 
761     // Potential insertion of resulting 1-D vector into array.
762     if (positionAttrs.size() > 1) {
763       auto nMinusOnePositionAttrs =
764           ArrayAttr::get(positionAttrs.drop_back(), context);
765       inserted = rewriter.create<LLVM::InsertValueOp>(loc, llvmResultType,
766                                                       adaptor.dest(), inserted,
767                                                       nMinusOnePositionAttrs);
768     }
769 
770     rewriter.replaceOp(op, inserted);
771     return success();
772   }
773 };
774 
775 /// Rank reducing rewrite for n-D FMA into (n-1)-D FMA where n > 1.
776 ///
777 /// Example:
778 /// ```
779 ///   %d = vector.fma %a, %b, %c : vector<2x4xf32>
780 /// ```
781 /// is rewritten into:
782 /// ```
783 ///  %r = splat %f0: vector<2x4xf32>
784 ///  %va = vector.extractvalue %a[0] : vector<2x4xf32>
785 ///  %vb = vector.extractvalue %b[0] : vector<2x4xf32>
786 ///  %vc = vector.extractvalue %c[0] : vector<2x4xf32>
787 ///  %vd = vector.fma %va, %vb, %vc : vector<4xf32>
788 ///  %r2 = vector.insertvalue %vd, %r[0] : vector<4xf32> into vector<2x4xf32>
789 ///  %va2 = vector.extractvalue %a2[1] : vector<2x4xf32>
790 ///  %vb2 = vector.extractvalue %b2[1] : vector<2x4xf32>
791 ///  %vc2 = vector.extractvalue %c2[1] : vector<2x4xf32>
792 ///  %vd2 = vector.fma %va2, %vb2, %vc2 : vector<4xf32>
793 ///  %r3 = vector.insertvalue %vd2, %r2[1] : vector<4xf32> into vector<2x4xf32>
794 ///  // %r3 holds the final value.
795 /// ```
796 class VectorFMAOpNDRewritePattern : public OpRewritePattern<FMAOp> {
797 public:
798   using OpRewritePattern<FMAOp>::OpRewritePattern;
799 
800   LogicalResult matchAndRewrite(FMAOp op,
801                                 PatternRewriter &rewriter) const override {
802     auto vType = op.getVectorType();
803     if (vType.getRank() < 2)
804       return failure();
805 
806     auto loc = op.getLoc();
807     auto elemType = vType.getElementType();
808     Value zero = rewriter.create<ConstantOp>(loc, elemType,
809                                              rewriter.getZeroAttr(elemType));
810     Value desc = rewriter.create<SplatOp>(loc, vType, zero);
811     for (int64_t i = 0, e = vType.getShape().front(); i != e; ++i) {
812       Value extrLHS = rewriter.create<ExtractOp>(loc, op.lhs(), i);
813       Value extrRHS = rewriter.create<ExtractOp>(loc, op.rhs(), i);
814       Value extrACC = rewriter.create<ExtractOp>(loc, op.acc(), i);
815       Value fma = rewriter.create<FMAOp>(loc, extrLHS, extrRHS, extrACC);
816       desc = rewriter.create<InsertOp>(loc, fma, desc, i);
817     }
818     rewriter.replaceOp(op, desc);
819     return success();
820   }
821 };
822 
823 // When ranks are different, InsertStridedSlice needs to extract a properly
824 // ranked vector from the destination vector into which to insert. This pattern
825 // only takes care of this part and forwards the rest of the conversion to
826 // another pattern that converts InsertStridedSlice for operands of the same
827 // rank.
828 //
829 // RewritePattern for InsertStridedSliceOp where source and destination vectors
830 // have different ranks. In this case:
831 //   1. the proper subvector is extracted from the destination vector
832 //   2. a new InsertStridedSlice op is created to insert the source in the
833 //   destination subvector
834 //   3. the destination subvector is inserted back in the proper place
835 //   4. the op is replaced by the result of step 3.
836 // The new InsertStridedSlice from step 2. will be picked up by a
837 // `VectorInsertStridedSliceOpSameRankRewritePattern`.
838 class VectorInsertStridedSliceOpDifferentRankRewritePattern
839     : public OpRewritePattern<InsertStridedSliceOp> {
840 public:
841   using OpRewritePattern<InsertStridedSliceOp>::OpRewritePattern;
842 
843   LogicalResult matchAndRewrite(InsertStridedSliceOp op,
844                                 PatternRewriter &rewriter) const override {
845     auto srcType = op.getSourceVectorType();
846     auto dstType = op.getDestVectorType();
847 
848     if (op.offsets().getValue().empty())
849       return failure();
850 
851     auto loc = op.getLoc();
852     int64_t rankDiff = dstType.getRank() - srcType.getRank();
853     assert(rankDiff >= 0);
854     if (rankDiff == 0)
855       return failure();
856 
857     int64_t rankRest = dstType.getRank() - rankDiff;
858     // Extract / insert the subvector of matching rank and InsertStridedSlice
859     // on it.
860     Value extracted =
861         rewriter.create<ExtractOp>(loc, op.dest(),
862                                    getI64SubArray(op.offsets(), /*dropFront=*/0,
863                                                   /*dropFront=*/rankRest));
864     // A different pattern will kick in for InsertStridedSlice with matching
865     // ranks.
866     auto stridedSliceInnerOp = rewriter.create<InsertStridedSliceOp>(
867         loc, op.source(), extracted,
868         getI64SubArray(op.offsets(), /*dropFront=*/rankDiff),
869         getI64SubArray(op.strides(), /*dropFront=*/0));
870     rewriter.replaceOpWithNewOp<InsertOp>(
871         op, stridedSliceInnerOp.getResult(), op.dest(),
872         getI64SubArray(op.offsets(), /*dropFront=*/0,
873                        /*dropFront=*/rankRest));
874     return success();
875   }
876 };
877 
878 // RewritePattern for InsertStridedSliceOp where source and destination vectors
879 // have the same rank. In this case, we reduce
880 //   1. the proper subvector is extracted from the destination vector
881 //   2. a new InsertStridedSlice op is created to insert the source in the
882 //   destination subvector
883 //   3. the destination subvector is inserted back in the proper place
884 //   4. the op is replaced by the result of step 3.
885 // The new InsertStridedSlice from step 2. will be picked up by a
886 // `VectorInsertStridedSliceOpSameRankRewritePattern`.
887 class VectorInsertStridedSliceOpSameRankRewritePattern
888     : public OpRewritePattern<InsertStridedSliceOp> {
889 public:
890   using OpRewritePattern<InsertStridedSliceOp>::OpRewritePattern;
891 
892   LogicalResult matchAndRewrite(InsertStridedSliceOp op,
893                                 PatternRewriter &rewriter) const override {
894     auto srcType = op.getSourceVectorType();
895     auto dstType = op.getDestVectorType();
896 
897     if (op.offsets().getValue().empty())
898       return failure();
899 
900     int64_t rankDiff = dstType.getRank() - srcType.getRank();
901     assert(rankDiff >= 0);
902     if (rankDiff != 0)
903       return failure();
904 
905     if (srcType == dstType) {
906       rewriter.replaceOp(op, op.source());
907       return success();
908     }
909 
910     int64_t offset =
911         op.offsets().getValue().front().cast<IntegerAttr>().getInt();
912     int64_t size = srcType.getShape().front();
913     int64_t stride =
914         op.strides().getValue().front().cast<IntegerAttr>().getInt();
915 
916     auto loc = op.getLoc();
917     Value res = op.dest();
918     // For each slice of the source vector along the most major dimension.
919     for (int64_t off = offset, e = offset + size * stride, idx = 0; off < e;
920          off += stride, ++idx) {
921       // 1. extract the proper subvector (or element) from source
922       Value extractedSource = extractOne(rewriter, loc, op.source(), idx);
923       if (extractedSource.getType().isa<VectorType>()) {
924         // 2. If we have a vector, extract the proper subvector from destination
925         // Otherwise we are at the element level and no need to recurse.
926         Value extractedDest = extractOne(rewriter, loc, op.dest(), off);
927         // 3. Reduce the problem to lowering a new InsertStridedSlice op with
928         // smaller rank.
929         extractedSource = rewriter.create<InsertStridedSliceOp>(
930             loc, extractedSource, extractedDest,
931             getI64SubArray(op.offsets(), /* dropFront=*/1),
932             getI64SubArray(op.strides(), /* dropFront=*/1));
933       }
934       // 4. Insert the extractedSource into the res vector.
935       res = insertOne(rewriter, loc, extractedSource, res, off);
936     }
937 
938     rewriter.replaceOp(op, res);
939     return success();
940   }
941   /// This pattern creates recursive InsertStridedSliceOp, but the recursion is
942   /// bounded as the rank is strictly decreasing.
943   bool hasBoundedRewriteRecursion() const final { return true; }
944 };
945 
946 class VectorTypeCastOpConversion : public ConvertToLLVMPattern {
947 public:
948   explicit VectorTypeCastOpConversion(MLIRContext *context,
949                                       LLVMTypeConverter &typeConverter)
950       : ConvertToLLVMPattern(vector::TypeCastOp::getOperationName(), context,
951                              typeConverter) {}
952 
953   LogicalResult
954   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
955                   ConversionPatternRewriter &rewriter) const override {
956     auto loc = op->getLoc();
957     vector::TypeCastOp castOp = cast<vector::TypeCastOp>(op);
958     MemRefType sourceMemRefType =
959         castOp.getOperand().getType().cast<MemRefType>();
960     MemRefType targetMemRefType =
961         castOp.getResult().getType().cast<MemRefType>();
962 
963     // Only static shape casts supported atm.
964     if (!sourceMemRefType.hasStaticShape() ||
965         !targetMemRefType.hasStaticShape())
966       return failure();
967 
968     auto llvmSourceDescriptorTy =
969         operands[0].getType().dyn_cast<LLVM::LLVMType>();
970     if (!llvmSourceDescriptorTy || !llvmSourceDescriptorTy.isStructTy())
971       return failure();
972     MemRefDescriptor sourceMemRef(operands[0]);
973 
974     auto llvmTargetDescriptorTy = typeConverter.convertType(targetMemRefType)
975                                       .dyn_cast_or_null<LLVM::LLVMType>();
976     if (!llvmTargetDescriptorTy || !llvmTargetDescriptorTy.isStructTy())
977       return failure();
978 
979     int64_t offset;
980     SmallVector<int64_t, 4> strides;
981     auto successStrides =
982         getStridesAndOffset(sourceMemRefType, strides, offset);
983     bool isContiguous = (strides.back() == 1);
984     if (isContiguous) {
985       auto sizes = sourceMemRefType.getShape();
986       for (int index = 0, e = strides.size() - 2; index < e; ++index) {
987         if (strides[index] != strides[index + 1] * sizes[index + 1]) {
988           isContiguous = false;
989           break;
990         }
991       }
992     }
993     // Only contiguous source tensors supported atm.
994     if (failed(successStrides) || !isContiguous)
995       return failure();
996 
997     auto int64Ty = LLVM::LLVMType::getInt64Ty(typeConverter.getDialect());
998 
999     // Create descriptor.
1000     auto desc = MemRefDescriptor::undef(rewriter, loc, llvmTargetDescriptorTy);
1001     Type llvmTargetElementTy = desc.getElementType();
1002     // Set allocated ptr.
1003     Value allocated = sourceMemRef.allocatedPtr(rewriter, loc);
1004     allocated =
1005         rewriter.create<LLVM::BitcastOp>(loc, llvmTargetElementTy, allocated);
1006     desc.setAllocatedPtr(rewriter, loc, allocated);
1007     // Set aligned ptr.
1008     Value ptr = sourceMemRef.alignedPtr(rewriter, loc);
1009     ptr = rewriter.create<LLVM::BitcastOp>(loc, llvmTargetElementTy, ptr);
1010     desc.setAlignedPtr(rewriter, loc, ptr);
1011     // Fill offset 0.
1012     auto attr = rewriter.getIntegerAttr(rewriter.getIndexType(), 0);
1013     auto zero = rewriter.create<LLVM::ConstantOp>(loc, int64Ty, attr);
1014     desc.setOffset(rewriter, loc, zero);
1015 
1016     // Fill size and stride descriptors in memref.
1017     for (auto indexedSize : llvm::enumerate(targetMemRefType.getShape())) {
1018       int64_t index = indexedSize.index();
1019       auto sizeAttr =
1020           rewriter.getIntegerAttr(rewriter.getIndexType(), indexedSize.value());
1021       auto size = rewriter.create<LLVM::ConstantOp>(loc, int64Ty, sizeAttr);
1022       desc.setSize(rewriter, loc, index, size);
1023       auto strideAttr =
1024           rewriter.getIntegerAttr(rewriter.getIndexType(), strides[index]);
1025       auto stride = rewriter.create<LLVM::ConstantOp>(loc, int64Ty, strideAttr);
1026       desc.setStride(rewriter, loc, index, stride);
1027     }
1028 
1029     rewriter.replaceOp(op, {desc});
1030     return success();
1031   }
1032 };
1033 
1034 /// Conversion pattern that converts a 1-D vector transfer read/write op in a
1035 /// sequence of:
1036 /// 1. Bitcast or addrspacecast to vector form.
1037 /// 2. Create an offsetVector = [ offset + 0 .. offset + vector_length - 1 ].
1038 /// 3. Create a mask where offsetVector is compared against memref upper bound.
1039 /// 4. Rewrite op as a masked read or write.
1040 template <typename ConcreteOp>
1041 class VectorTransferConversion : public ConvertToLLVMPattern {
1042 public:
1043   explicit VectorTransferConversion(MLIRContext *context,
1044                                     LLVMTypeConverter &typeConv)
1045       : ConvertToLLVMPattern(ConcreteOp::getOperationName(), context,
1046                              typeConv) {}
1047 
1048   LogicalResult
1049   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
1050                   ConversionPatternRewriter &rewriter) const override {
1051     auto xferOp = cast<ConcreteOp>(op);
1052     auto adaptor = getTransferOpAdapter(xferOp, operands);
1053 
1054     if (xferOp.getVectorType().getRank() > 1 ||
1055         llvm::size(xferOp.indices()) == 0)
1056       return failure();
1057     if (xferOp.permutation_map() !=
1058         AffineMap::getMinorIdentityMap(xferOp.permutation_map().getNumInputs(),
1059                                        xferOp.getVectorType().getRank(),
1060                                        op->getContext()))
1061       return failure();
1062 
1063     auto toLLVMTy = [&](Type t) { return typeConverter.convertType(t); };
1064 
1065     Location loc = op->getLoc();
1066     Type i64Type = rewriter.getIntegerType(64);
1067     MemRefType memRefType = xferOp.getMemRefType();
1068 
1069     // 1. Get the source/dst address as an LLVM vector pointer.
1070     //    The vector pointer would always be on address space 0, therefore
1071     //    addrspacecast shall be used when source/dst memrefs are not on
1072     //    address space 0.
1073     // TODO: support alignment when possible.
1074     Value dataPtr = getDataPtr(loc, memRefType, adaptor.memref(),
1075                                adaptor.indices(), rewriter, getModule());
1076     auto vecTy =
1077         toLLVMTy(xferOp.getVectorType()).template cast<LLVM::LLVMType>();
1078     Value vectorDataPtr;
1079     if (memRefType.getMemorySpace() == 0)
1080       vectorDataPtr =
1081           rewriter.create<LLVM::BitcastOp>(loc, vecTy.getPointerTo(), dataPtr);
1082     else
1083       vectorDataPtr = rewriter.create<LLVM::AddrSpaceCastOp>(
1084           loc, vecTy.getPointerTo(), dataPtr);
1085 
1086     if (!xferOp.isMaskedDim(0))
1087       return replaceTransferOpWithLoadOrStore(rewriter, typeConverter, loc,
1088                                               xferOp, operands, vectorDataPtr);
1089 
1090     // 2. Create a vector with linear indices [ 0 .. vector_length - 1 ].
1091     unsigned vecWidth = vecTy.getVectorNumElements();
1092     VectorType vectorCmpType = VectorType::get(vecWidth, i64Type);
1093     SmallVector<int64_t, 8> indices;
1094     indices.reserve(vecWidth);
1095     for (unsigned i = 0; i < vecWidth; ++i)
1096       indices.push_back(i);
1097     Value linearIndices = rewriter.create<ConstantOp>(
1098         loc, vectorCmpType,
1099         DenseElementsAttr::get(vectorCmpType, ArrayRef<int64_t>(indices)));
1100     linearIndices = rewriter.create<LLVM::DialectCastOp>(
1101         loc, toLLVMTy(vectorCmpType), linearIndices);
1102 
1103     // 3. Create offsetVector = [ offset + 0 .. offset + vector_length - 1 ].
1104     // TODO: when the leaf transfer rank is k > 1 we need the last
1105     // `k` dimensions here.
1106     unsigned lastIndex = llvm::size(xferOp.indices()) - 1;
1107     Value offsetIndex = *(xferOp.indices().begin() + lastIndex);
1108     offsetIndex = rewriter.create<IndexCastOp>(loc, i64Type, offsetIndex);
1109     Value base = rewriter.create<SplatOp>(loc, vectorCmpType, offsetIndex);
1110     Value offsetVector = rewriter.create<AddIOp>(loc, base, linearIndices);
1111 
1112     // 4. Let dim the memref dimension, compute the vector comparison mask:
1113     //   [ offset + 0 .. offset + vector_length - 1 ] < [ dim .. dim ]
1114     Value dim = rewriter.create<DimOp>(loc, xferOp.memref(), lastIndex);
1115     dim = rewriter.create<IndexCastOp>(loc, i64Type, dim);
1116     dim = rewriter.create<SplatOp>(loc, vectorCmpType, dim);
1117     Value mask =
1118         rewriter.create<CmpIOp>(loc, CmpIPredicate::slt, offsetVector, dim);
1119     mask = rewriter.create<LLVM::DialectCastOp>(loc, toLLVMTy(mask.getType()),
1120                                                 mask);
1121 
1122     // 5. Rewrite as a masked read / write.
1123     return replaceTransferOpWithMasked(rewriter, typeConverter, loc, xferOp,
1124                                        operands, vectorDataPtr, mask);
1125   }
1126 };
1127 
1128 class VectorPrintOpConversion : public ConvertToLLVMPattern {
1129 public:
1130   explicit VectorPrintOpConversion(MLIRContext *context,
1131                                    LLVMTypeConverter &typeConverter)
1132       : ConvertToLLVMPattern(vector::PrintOp::getOperationName(), context,
1133                              typeConverter) {}
1134 
1135   // Proof-of-concept lowering implementation that relies on a small
1136   // runtime support library, which only needs to provide a few
1137   // printing methods (single value for all data types, opening/closing
1138   // bracket, comma, newline). The lowering fully unrolls a vector
1139   // in terms of these elementary printing operations. The advantage
1140   // of this approach is that the library can remain unaware of all
1141   // low-level implementation details of vectors while still supporting
1142   // output of any shaped and dimensioned vector. Due to full unrolling,
1143   // this approach is less suited for very large vectors though.
1144   //
1145   // TODO: rely solely on libc in future? something else?
1146   //
1147   LogicalResult
1148   matchAndRewrite(Operation *op, ArrayRef<Value> operands,
1149                   ConversionPatternRewriter &rewriter) const override {
1150     auto printOp = cast<vector::PrintOp>(op);
1151     auto adaptor = vector::PrintOpAdaptor(operands);
1152     Type printType = printOp.getPrintType();
1153 
1154     if (typeConverter.convertType(printType) == nullptr)
1155       return failure();
1156 
1157     // Make sure element type has runtime support (currently just Float/Double).
1158     VectorType vectorType = printType.dyn_cast<VectorType>();
1159     Type eltType = vectorType ? vectorType.getElementType() : printType;
1160     int64_t rank = vectorType ? vectorType.getRank() : 0;
1161     Operation *printer;
1162     if (eltType.isSignlessInteger(1) || eltType.isSignlessInteger(32))
1163       printer = getPrintI32(op);
1164     else if (eltType.isSignlessInteger(64))
1165       printer = getPrintI64(op);
1166     else if (eltType.isF32())
1167       printer = getPrintFloat(op);
1168     else if (eltType.isF64())
1169       printer = getPrintDouble(op);
1170     else
1171       return failure();
1172 
1173     // Unroll vector into elementary print calls.
1174     emitRanks(rewriter, op, adaptor.source(), vectorType, printer, rank);
1175     emitCall(rewriter, op->getLoc(), getPrintNewline(op));
1176     rewriter.eraseOp(op);
1177     return success();
1178   }
1179 
1180 private:
1181   void emitRanks(ConversionPatternRewriter &rewriter, Operation *op,
1182                  Value value, VectorType vectorType, Operation *printer,
1183                  int64_t rank) const {
1184     Location loc = op->getLoc();
1185     if (rank == 0) {
1186       if (value.getType() ==
1187           LLVM::LLVMType::getInt1Ty(typeConverter.getDialect())) {
1188         // Convert i1 (bool) to i32 so we can use the print_i32 method.
1189         // This avoids the need for a print_i1 method with an unclear ABI.
1190         auto i32Type = LLVM::LLVMType::getInt32Ty(typeConverter.getDialect());
1191         auto trueVal = rewriter.create<ConstantOp>(
1192             loc, i32Type, rewriter.getI32IntegerAttr(1));
1193         auto falseVal = rewriter.create<ConstantOp>(
1194             loc, i32Type, rewriter.getI32IntegerAttr(0));
1195         value = rewriter.create<SelectOp>(loc, value, trueVal, falseVal);
1196       }
1197       emitCall(rewriter, loc, printer, value);
1198       return;
1199     }
1200 
1201     emitCall(rewriter, loc, getPrintOpen(op));
1202     Operation *printComma = getPrintComma(op);
1203     int64_t dim = vectorType.getDimSize(0);
1204     for (int64_t d = 0; d < dim; ++d) {
1205       auto reducedType =
1206           rank > 1 ? reducedVectorTypeFront(vectorType) : nullptr;
1207       auto llvmType = typeConverter.convertType(
1208           rank > 1 ? reducedType : vectorType.getElementType());
1209       Value nestedVal =
1210           extractOne(rewriter, typeConverter, loc, value, llvmType, rank, d);
1211       emitRanks(rewriter, op, nestedVal, reducedType, printer, rank - 1);
1212       if (d != dim - 1)
1213         emitCall(rewriter, loc, printComma);
1214     }
1215     emitCall(rewriter, loc, getPrintClose(op));
1216   }
1217 
1218   // Helper to emit a call.
1219   static void emitCall(ConversionPatternRewriter &rewriter, Location loc,
1220                        Operation *ref, ValueRange params = ValueRange()) {
1221     rewriter.create<LLVM::CallOp>(loc, ArrayRef<Type>{},
1222                                   rewriter.getSymbolRefAttr(ref), params);
1223   }
1224 
1225   // Helper for printer method declaration (first hit) and lookup.
1226   static Operation *getPrint(Operation *op, LLVM::LLVMDialect *dialect,
1227                              StringRef name, ArrayRef<LLVM::LLVMType> params) {
1228     auto module = op->getParentOfType<ModuleOp>();
1229     auto func = module.lookupSymbol<LLVM::LLVMFuncOp>(name);
1230     if (func)
1231       return func;
1232     OpBuilder moduleBuilder(module.getBodyRegion());
1233     return moduleBuilder.create<LLVM::LLVMFuncOp>(
1234         op->getLoc(), name,
1235         LLVM::LLVMType::getFunctionTy(LLVM::LLVMType::getVoidTy(dialect),
1236                                       params, /*isVarArg=*/false));
1237   }
1238 
1239   // Helpers for method names.
1240   Operation *getPrintI32(Operation *op) const {
1241     LLVM::LLVMDialect *dialect = typeConverter.getDialect();
1242     return getPrint(op, dialect, "print_i32",
1243                     LLVM::LLVMType::getInt32Ty(dialect));
1244   }
1245   Operation *getPrintI64(Operation *op) const {
1246     LLVM::LLVMDialect *dialect = typeConverter.getDialect();
1247     return getPrint(op, dialect, "print_i64",
1248                     LLVM::LLVMType::getInt64Ty(dialect));
1249   }
1250   Operation *getPrintFloat(Operation *op) const {
1251     LLVM::LLVMDialect *dialect = typeConverter.getDialect();
1252     return getPrint(op, dialect, "print_f32",
1253                     LLVM::LLVMType::getFloatTy(dialect));
1254   }
1255   Operation *getPrintDouble(Operation *op) const {
1256     LLVM::LLVMDialect *dialect = typeConverter.getDialect();
1257     return getPrint(op, dialect, "print_f64",
1258                     LLVM::LLVMType::getDoubleTy(dialect));
1259   }
1260   Operation *getPrintOpen(Operation *op) const {
1261     return getPrint(op, typeConverter.getDialect(), "print_open", {});
1262   }
1263   Operation *getPrintClose(Operation *op) const {
1264     return getPrint(op, typeConverter.getDialect(), "print_close", {});
1265   }
1266   Operation *getPrintComma(Operation *op) const {
1267     return getPrint(op, typeConverter.getDialect(), "print_comma", {});
1268   }
1269   Operation *getPrintNewline(Operation *op) const {
1270     return getPrint(op, typeConverter.getDialect(), "print_newline", {});
1271   }
1272 };
1273 
1274 /// Progressive lowering of ExtractStridedSliceOp to either:
1275 ///   1. extractelement + insertelement for the 1-D case
1276 ///   2. extract + optional strided_slice + insert for the n-D case.
1277 class VectorStridedSliceOpConversion
1278     : public OpRewritePattern<ExtractStridedSliceOp> {
1279 public:
1280   using OpRewritePattern<ExtractStridedSliceOp>::OpRewritePattern;
1281 
1282   LogicalResult matchAndRewrite(ExtractStridedSliceOp op,
1283                                 PatternRewriter &rewriter) const override {
1284     auto dstType = op.getResult().getType().cast<VectorType>();
1285 
1286     assert(!op.offsets().getValue().empty() && "Unexpected empty offsets");
1287 
1288     int64_t offset =
1289         op.offsets().getValue().front().cast<IntegerAttr>().getInt();
1290     int64_t size = op.sizes().getValue().front().cast<IntegerAttr>().getInt();
1291     int64_t stride =
1292         op.strides().getValue().front().cast<IntegerAttr>().getInt();
1293 
1294     auto loc = op.getLoc();
1295     auto elemType = dstType.getElementType();
1296     assert(elemType.isSignlessIntOrIndexOrFloat());
1297     Value zero = rewriter.create<ConstantOp>(loc, elemType,
1298                                              rewriter.getZeroAttr(elemType));
1299     Value res = rewriter.create<SplatOp>(loc, dstType, zero);
1300     for (int64_t off = offset, e = offset + size * stride, idx = 0; off < e;
1301          off += stride, ++idx) {
1302       Value extracted = extractOne(rewriter, loc, op.vector(), off);
1303       if (op.offsets().getValue().size() > 1) {
1304         extracted = rewriter.create<ExtractStridedSliceOp>(
1305             loc, extracted, getI64SubArray(op.offsets(), /* dropFront=*/1),
1306             getI64SubArray(op.sizes(), /* dropFront=*/1),
1307             getI64SubArray(op.strides(), /* dropFront=*/1));
1308       }
1309       res = insertOne(rewriter, loc, extracted, res, idx);
1310     }
1311     rewriter.replaceOp(op, {res});
1312     return success();
1313   }
1314   /// This pattern creates recursive ExtractStridedSliceOp, but the recursion is
1315   /// bounded as the rank is strictly decreasing.
1316   bool hasBoundedRewriteRecursion() const final { return true; }
1317 };
1318 
1319 } // namespace
1320 
1321 /// Populate the given list with patterns that convert from Vector to LLVM.
1322 void mlir::populateVectorToLLVMConversionPatterns(
1323     LLVMTypeConverter &converter, OwningRewritePatternList &patterns,
1324     bool reassociateFPReductions) {
1325   MLIRContext *ctx = converter.getDialect()->getContext();
1326   // clang-format off
1327   patterns.insert<VectorFMAOpNDRewritePattern,
1328                   VectorInsertStridedSliceOpDifferentRankRewritePattern,
1329                   VectorInsertStridedSliceOpSameRankRewritePattern,
1330                   VectorStridedSliceOpConversion>(ctx);
1331   patterns.insert<VectorReductionOpConversion>(
1332       ctx, converter, reassociateFPReductions);
1333   patterns
1334       .insert<VectorShuffleOpConversion,
1335               VectorExtractElementOpConversion,
1336               VectorExtractOpConversion,
1337               VectorFMAOp1DConversion,
1338               VectorInsertElementOpConversion,
1339               VectorInsertOpConversion,
1340               VectorPrintOpConversion,
1341               VectorTransferConversion<TransferReadOp>,
1342               VectorTransferConversion<TransferWriteOp>,
1343               VectorTypeCastOpConversion,
1344               VectorGatherOpConversion,
1345               VectorScatterOpConversion,
1346               VectorExpandLoadOpConversion,
1347               VectorCompressStoreOpConversion>(ctx, converter);
1348   // clang-format on
1349 }
1350 
1351 void mlir::populateVectorToLLVMMatrixConversionPatterns(
1352     LLVMTypeConverter &converter, OwningRewritePatternList &patterns) {
1353   MLIRContext *ctx = converter.getDialect()->getContext();
1354   patterns.insert<VectorMatmulOpConversion>(ctx, converter);
1355   patterns.insert<VectorFlatTransposeOpConversion>(ctx, converter);
1356 }
1357 
1358 namespace {
1359 struct LowerVectorToLLVMPass
1360     : public ConvertVectorToLLVMBase<LowerVectorToLLVMPass> {
1361   LowerVectorToLLVMPass(const LowerVectorToLLVMOptions &options) {
1362     this->reassociateFPReductions = options.reassociateFPReductions;
1363   }
1364   void runOnOperation() override;
1365 };
1366 } // namespace
1367 
1368 void LowerVectorToLLVMPass::runOnOperation() {
1369   // Perform progressive lowering of operations on slices and
1370   // all contraction operations. Also applies folding and DCE.
1371   {
1372     OwningRewritePatternList patterns;
1373     populateVectorToVectorCanonicalizationPatterns(patterns, &getContext());
1374     populateVectorSlicesLoweringPatterns(patterns, &getContext());
1375     populateVectorContractLoweringPatterns(patterns, &getContext());
1376     applyPatternsAndFoldGreedily(getOperation(), patterns);
1377   }
1378 
1379   // Convert to the LLVM IR dialect.
1380   LLVMTypeConverter converter(&getContext());
1381   OwningRewritePatternList patterns;
1382   populateVectorToLLVMMatrixConversionPatterns(converter, patterns);
1383   populateVectorToLLVMConversionPatterns(converter, patterns,
1384                                          reassociateFPReductions);
1385   populateVectorToLLVMMatrixConversionPatterns(converter, patterns);
1386   populateStdToLLVMConversionPatterns(converter, patterns);
1387 
1388   LLVMConversionTarget target(getContext());
1389   if (failed(applyPartialConversion(getOperation(), target, patterns))) {
1390     signalPassFailure();
1391   }
1392 }
1393 
1394 std::unique_ptr<OperationPass<ModuleOp>>
1395 mlir::createConvertVectorToLLVMPass(const LowerVectorToLLVMOptions &options) {
1396   return std::make_unique<LowerVectorToLLVMPass>(options);
1397 }
1398