1 | //===-- ArrayValueCopy.cpp ------------------------------------------------===// |
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 "flang/Optimizer/Builder/BoxValue.h" |
10 | #include "flang/Optimizer/Builder/FIRBuilder.h" |
11 | #include "flang/Optimizer/Builder/Factory.h" |
12 | #include "flang/Optimizer/Builder/Runtime/Derived.h" |
13 | #include "flang/Optimizer/Builder/Todo.h" |
14 | #include "flang/Optimizer/Dialect/FIRDialect.h" |
15 | #include "flang/Optimizer/Dialect/FIROpsSupport.h" |
16 | #include "flang/Optimizer/Dialect/Support/FIRContext.h" |
17 | #include "flang/Optimizer/Transforms/Passes.h" |
18 | #include "mlir/Dialect/ControlFlow/IR/ControlFlowOps.h" |
19 | #include "mlir/Dialect/SCF/IR/SCF.h" |
20 | #include "mlir/Transforms/DialectConversion.h" |
21 | #include "llvm/Support/Debug.h" |
22 | |
23 | namespace fir { |
24 | #define GEN_PASS_DEF_ARRAYVALUECOPY |
25 | #include "flang/Optimizer/Transforms/Passes.h.inc" |
26 | } // namespace fir |
27 | |
28 | #define DEBUG_TYPE "flang-array-value-copy" |
29 | |
30 | using namespace fir; |
31 | using namespace mlir; |
32 | |
33 | using OperationUseMapT = llvm::DenseMap<mlir::Operation *, mlir::Operation *>; |
34 | |
35 | namespace { |
36 | |
37 | /// Array copy analysis. |
38 | /// Perform an interference analysis between array values. |
39 | /// |
40 | /// Lowering will generate a sequence of the following form. |
41 | /// ```mlir |
42 | /// %a_1 = fir.array_load %array_1(%shape) : ... |
43 | /// ... |
44 | /// %a_j = fir.array_load %array_j(%shape) : ... |
45 | /// ... |
46 | /// %a_n = fir.array_load %array_n(%shape) : ... |
47 | /// ... |
48 | /// %v_i = fir.array_fetch %a_i, ... |
49 | /// %a_j1 = fir.array_update %a_j, ... |
50 | /// ... |
51 | /// fir.array_merge_store %a_j, %a_jn to %array_j : ... |
52 | /// ``` |
53 | /// |
54 | /// The analysis is to determine if there are any conflicts. A conflict is when |
55 | /// one the following cases occurs. |
56 | /// |
57 | /// 1. There is an `array_update` to an array value, a_j, such that a_j was |
58 | /// loaded from the same array memory reference (array_j) but with a different |
59 | /// shape as the other array values a_i, where i != j. [Possible overlapping |
60 | /// arrays.] |
61 | /// |
62 | /// 2. There is either an array_fetch or array_update of a_j with a different |
63 | /// set of index values. [Possible loop-carried dependence.] |
64 | /// |
65 | /// If none of the array values overlap in storage and the accesses are not |
66 | /// loop-carried, then the arrays are conflict-free and no copies are required. |
67 | class ArrayCopyAnalysisBase { |
68 | public: |
69 | using ConflictSetT = llvm::SmallPtrSet<mlir::Operation *, 16>; |
70 | using UseSetT = llvm::SmallPtrSet<mlir::OpOperand *, 8>; |
71 | using LoadMapSetsT = llvm::DenseMap<mlir::Operation *, UseSetT>; |
72 | using AmendAccessSetT = llvm::SmallPtrSet<mlir::Operation *, 4>; |
73 | |
74 | ArrayCopyAnalysisBase(mlir::Operation *op, bool optimized) |
75 | : operation{op}, optimizeConflicts(optimized) { |
76 | construct(op); |
77 | } |
78 | virtual ~ArrayCopyAnalysisBase() = default; |
79 | |
80 | mlir::Operation *getOperation() const { return operation; } |
81 | |
82 | /// Return true iff the `array_merge_store` has potential conflicts. |
83 | bool hasPotentialConflict(mlir::Operation *op) const { |
84 | LLVM_DEBUG(llvm::dbgs() |
85 | << "looking for a conflict on " << *op |
86 | << " and the set has a total of " << conflicts.size() << '\n'); |
87 | return conflicts.contains(op); |
88 | } |
89 | |
90 | /// Return the use map. |
91 | /// The use map maps array access, amend, fetch and update operations back to |
92 | /// the array load that is the original source of the array value. |
93 | /// It maps an array_load to an array_merge_store, if and only if the loaded |
94 | /// array value has pending modifications to be merged. |
95 | const OperationUseMapT &getUseMap() const { return useMap; } |
96 | |
97 | /// Return the set of array_access ops directly associated with array_amend |
98 | /// ops. |
99 | bool inAmendAccessSet(mlir::Operation *op) const { |
100 | return amendAccesses.count(op); |
101 | } |
102 | |
103 | /// For ArrayLoad `load`, return the transitive set of all OpOperands. |
104 | UseSetT getLoadUseSet(mlir::Operation *load) const { |
105 | assert(loadMapSets.count(load) && "analysis missed an array load?" ); |
106 | return loadMapSets.lookup(load); |
107 | } |
108 | |
109 | void arrayMentions(llvm::SmallVectorImpl<mlir::Operation *> &mentions, |
110 | ArrayLoadOp load); |
111 | |
112 | private: |
113 | void construct(mlir::Operation *topLevelOp); |
114 | |
115 | mlir::Operation *operation; // operation that analysis ran upon |
116 | ConflictSetT conflicts; // set of conflicts (loads and merge stores) |
117 | OperationUseMapT useMap; |
118 | LoadMapSetsT loadMapSets; |
119 | // Set of array_access ops associated with array_amend ops. |
120 | AmendAccessSetT amendAccesses; |
121 | bool optimizeConflicts; |
122 | }; |
123 | |
124 | // Optimized array copy analysis that takes into account Fortran |
125 | // variable attributes to prove that no conflict is possible |
126 | // and reduce the number of temporary arrays. |
127 | class ArrayCopyAnalysisOptimized : public ArrayCopyAnalysisBase { |
128 | public: |
129 | MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(ArrayCopyAnalysisOptimized) |
130 | |
131 | ArrayCopyAnalysisOptimized(mlir::Operation *op) |
132 | : ArrayCopyAnalysisBase(op, /*optimized=*/true) {} |
133 | }; |
134 | |
135 | // Unoptimized array copy analysis used at O0. |
136 | class ArrayCopyAnalysis : public ArrayCopyAnalysisBase { |
137 | public: |
138 | MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(ArrayCopyAnalysis) |
139 | |
140 | ArrayCopyAnalysis(mlir::Operation *op) |
141 | : ArrayCopyAnalysisBase(op, /*optimized=*/false) {} |
142 | }; |
143 | } // namespace |
144 | |
145 | namespace { |
146 | /// Helper class to collect all array operations that produced an array value. |
147 | class ReachCollector { |
148 | public: |
149 | ReachCollector(llvm::SmallVectorImpl<mlir::Operation *> &reach, |
150 | mlir::Region *loopRegion) |
151 | : reach{reach}, loopRegion{loopRegion} {} |
152 | |
153 | void collectArrayMentionFrom(mlir::Operation *op, mlir::ValueRange range) { |
154 | if (range.empty()) { |
155 | collectArrayMentionFrom(op, mlir::Value{}); |
156 | return; |
157 | } |
158 | for (mlir::Value v : range) |
159 | collectArrayMentionFrom(v); |
160 | } |
161 | |
162 | // Collect all the array_access ops in `block`. This recursively looks into |
163 | // blocks in ops with regions. |
164 | // FIXME: This is temporarily relying on the array_amend appearing in a |
165 | // do_loop Region. This phase ordering assumption can be eliminated by using |
166 | // dominance information to find the array_access ops or by scanning the |
167 | // transitive closure of the amending array_access's users and the defs that |
168 | // reach them. |
169 | void collectAccesses(llvm::SmallVector<ArrayAccessOp> &result, |
170 | mlir::Block *block) { |
171 | for (auto &op : *block) { |
172 | if (auto access = mlir::dyn_cast<ArrayAccessOp>(op)) { |
173 | LLVM_DEBUG(llvm::dbgs() << "adding access: " << access << '\n'); |
174 | result.push_back(access); |
175 | continue; |
176 | } |
177 | for (auto ®ion : op.getRegions()) |
178 | for (auto &bb : region.getBlocks()) |
179 | collectAccesses(result, &bb); |
180 | } |
181 | } |
182 | |
183 | void collectArrayMentionFrom(mlir::Operation *op, mlir::Value val) { |
184 | // `val` is defined by an Op, process the defining Op. |
185 | // If `val` is defined by a region containing Op, we want to drill down |
186 | // and through that Op's region(s). |
187 | LLVM_DEBUG(llvm::dbgs() << "popset: " << *op << '\n'); |
188 | auto popFn = [&](auto rop) { |
189 | assert(val && "op must have a result value" ); |
190 | auto resNum = mlir::cast<mlir::OpResult>(val).getResultNumber(); |
191 | llvm::SmallVector<mlir::Value> results; |
192 | rop.resultToSourceOps(results, resNum); |
193 | for (auto u : results) |
194 | collectArrayMentionFrom(u); |
195 | }; |
196 | if (auto rop = mlir::dyn_cast<DoLoopOp>(op)) { |
197 | popFn(rop); |
198 | return; |
199 | } |
200 | if (auto rop = mlir::dyn_cast<IterWhileOp>(op)) { |
201 | popFn(rop); |
202 | return; |
203 | } |
204 | if (auto rop = mlir::dyn_cast<fir::IfOp>(op)) { |
205 | popFn(rop); |
206 | return; |
207 | } |
208 | if (auto box = mlir::dyn_cast<EmboxOp>(op)) { |
209 | for (auto *user : box.getMemref().getUsers()) |
210 | if (user != op) |
211 | collectArrayMentionFrom(user, user->getResults()); |
212 | return; |
213 | } |
214 | if (auto mergeStore = mlir::dyn_cast<ArrayMergeStoreOp>(op)) { |
215 | if (opIsInsideLoops(mergeStore)) |
216 | collectArrayMentionFrom(mergeStore.getSequence()); |
217 | return; |
218 | } |
219 | |
220 | if (mlir::isa<AllocaOp, AllocMemOp>(op)) { |
221 | // Look for any stores inside the loops, and collect an array operation |
222 | // that produced the value being stored to it. |
223 | for (auto *user : op->getUsers()) |
224 | if (auto store = mlir::dyn_cast<fir::StoreOp>(user)) |
225 | if (opIsInsideLoops(store)) |
226 | collectArrayMentionFrom(store.getValue()); |
227 | return; |
228 | } |
229 | |
230 | // Scan the uses of amend's memref |
231 | if (auto amend = mlir::dyn_cast<ArrayAmendOp>(op)) { |
232 | reach.push_back(op); |
233 | llvm::SmallVector<ArrayAccessOp> accesses; |
234 | collectAccesses(accesses, op->getBlock()); |
235 | for (auto access : accesses) |
236 | collectArrayMentionFrom(access.getResult()); |
237 | } |
238 | |
239 | // Otherwise, Op does not contain a region so just chase its operands. |
240 | if (mlir::isa<ArrayAccessOp, ArrayLoadOp, ArrayUpdateOp, ArrayModifyOp, |
241 | ArrayFetchOp>(op)) { |
242 | LLVM_DEBUG(llvm::dbgs() << "add " << *op << " to reachable set\n" ); |
243 | reach.push_back(op); |
244 | } |
245 | |
246 | // Include all array_access ops using an array_load. |
247 | if (auto arrLd = mlir::dyn_cast<ArrayLoadOp>(op)) |
248 | for (auto *user : arrLd.getResult().getUsers()) |
249 | if (mlir::isa<ArrayAccessOp>(user)) { |
250 | LLVM_DEBUG(llvm::dbgs() << "add " << *user << " to reachable set\n" ); |
251 | reach.push_back(user); |
252 | } |
253 | |
254 | // Array modify assignment is performed on the result. So the analysis must |
255 | // look at the what is done with the result. |
256 | if (mlir::isa<ArrayModifyOp>(op)) |
257 | for (auto *user : op->getResult(0).getUsers()) |
258 | followUsers(user); |
259 | |
260 | if (mlir::isa<fir::CallOp>(op)) { |
261 | LLVM_DEBUG(llvm::dbgs() << "add " << *op << " to reachable set\n" ); |
262 | reach.push_back(op); |
263 | } |
264 | |
265 | for (auto u : op->getOperands()) |
266 | collectArrayMentionFrom(u); |
267 | } |
268 | |
269 | void collectArrayMentionFrom(mlir::BlockArgument ba) { |
270 | auto *parent = ba.getOwner()->getParentOp(); |
271 | // If inside an Op holding a region, the block argument corresponds to an |
272 | // argument passed to the containing Op. |
273 | auto popFn = [&](auto rop) { |
274 | collectArrayMentionFrom(rop.blockArgToSourceOp(ba.getArgNumber())); |
275 | }; |
276 | if (auto rop = mlir::dyn_cast<DoLoopOp>(parent)) { |
277 | popFn(rop); |
278 | return; |
279 | } |
280 | if (auto rop = mlir::dyn_cast<IterWhileOp>(parent)) { |
281 | popFn(rop); |
282 | return; |
283 | } |
284 | // Otherwise, a block argument is provided via the pred blocks. |
285 | for (auto *pred : ba.getOwner()->getPredecessors()) { |
286 | auto u = pred->getTerminator()->getOperand(ba.getArgNumber()); |
287 | collectArrayMentionFrom(u); |
288 | } |
289 | } |
290 | |
291 | // Recursively trace operands to find all array operations relating to the |
292 | // values merged. |
293 | void collectArrayMentionFrom(mlir::Value val) { |
294 | if (!val || visited.contains(val)) |
295 | return; |
296 | visited.insert(val); |
297 | |
298 | // Process a block argument. |
299 | if (auto ba = mlir::dyn_cast<mlir::BlockArgument>(val)) { |
300 | collectArrayMentionFrom(ba); |
301 | return; |
302 | } |
303 | |
304 | // Process an Op. |
305 | if (auto *op = val.getDefiningOp()) { |
306 | collectArrayMentionFrom(op, val); |
307 | return; |
308 | } |
309 | |
310 | emitFatalError(val.getLoc(), "unhandled value" ); |
311 | } |
312 | |
313 | /// Return all ops that produce the array value that is stored into the |
314 | /// `array_merge_store`. |
315 | static void reachingValues(llvm::SmallVectorImpl<mlir::Operation *> &reach, |
316 | mlir::Value seq) { |
317 | reach.clear(); |
318 | mlir::Region *loopRegion = nullptr; |
319 | if (auto doLoop = mlir::dyn_cast_or_null<DoLoopOp>(seq.getDefiningOp())) |
320 | loopRegion = &doLoop->getRegion(0); |
321 | ReachCollector collector(reach, loopRegion); |
322 | collector.collectArrayMentionFrom(seq); |
323 | } |
324 | |
325 | private: |
326 | /// Is \op inside the loop nest region ? |
327 | /// FIXME: replace this structural dependence with graph properties. |
328 | bool opIsInsideLoops(mlir::Operation *op) const { |
329 | auto *region = op->getParentRegion(); |
330 | while (region) { |
331 | if (region == loopRegion) |
332 | return true; |
333 | region = region->getParentRegion(); |
334 | } |
335 | return false; |
336 | } |
337 | |
338 | /// Recursively trace the use of an operation results, calling |
339 | /// collectArrayMentionFrom on the direct and indirect user operands. |
340 | void followUsers(mlir::Operation *op) { |
341 | for (auto userOperand : op->getOperands()) |
342 | collectArrayMentionFrom(userOperand); |
343 | // Go through potential converts/coordinate_op. |
344 | for (auto indirectUser : op->getUsers()) |
345 | followUsers(indirectUser); |
346 | } |
347 | |
348 | llvm::SmallVectorImpl<mlir::Operation *> &reach; |
349 | llvm::SmallPtrSet<mlir::Value, 16> visited; |
350 | /// Region of the loops nest that produced the array value. |
351 | mlir::Region *loopRegion; |
352 | }; |
353 | } // namespace |
354 | |
355 | /// Find all the array operations that access the array value that is loaded by |
356 | /// the array load operation, `load`. |
357 | void ArrayCopyAnalysisBase::arrayMentions( |
358 | llvm::SmallVectorImpl<mlir::Operation *> &mentions, ArrayLoadOp load) { |
359 | mentions.clear(); |
360 | auto lmIter = loadMapSets.find(load); |
361 | if (lmIter != loadMapSets.end()) { |
362 | for (auto *opnd : lmIter->second) { |
363 | auto *owner = opnd->getOwner(); |
364 | if (mlir::isa<ArrayAccessOp, ArrayAmendOp, ArrayFetchOp, ArrayUpdateOp, |
365 | ArrayModifyOp>(owner)) |
366 | mentions.push_back(owner); |
367 | } |
368 | return; |
369 | } |
370 | |
371 | UseSetT visited; |
372 | llvm::SmallVector<mlir::OpOperand *> queue; // uses of ArrayLoad[orig] |
373 | |
374 | auto appendToQueue = [&](mlir::Value val) { |
375 | for (auto &use : val.getUses()) |
376 | if (!visited.count(&use)) { |
377 | visited.insert(&use); |
378 | queue.push_back(&use); |
379 | } |
380 | }; |
381 | |
382 | // Build the set of uses of `original`. |
383 | // let USES = { uses of original fir.load } |
384 | appendToQueue(load); |
385 | |
386 | // Process the worklist until done. |
387 | while (!queue.empty()) { |
388 | mlir::OpOperand *operand = queue.pop_back_val(); |
389 | mlir::Operation *owner = operand->getOwner(); |
390 | if (!owner) |
391 | continue; |
392 | auto structuredLoop = [&](auto ro) { |
393 | if (auto blockArg = ro.iterArgToBlockArg(operand->get())) { |
394 | int64_t arg = blockArg.getArgNumber(); |
395 | mlir::Value output = ro.getResult(ro.getFinalValue() ? arg : arg - 1); |
396 | appendToQueue(output); |
397 | appendToQueue(blockArg); |
398 | } |
399 | }; |
400 | // TODO: this need to be updated to use the control-flow interface. |
401 | auto branchOp = [&](mlir::Block *dest, OperandRange operands) { |
402 | if (operands.empty()) |
403 | return; |
404 | |
405 | // Check if this operand is within the range. |
406 | unsigned operandIndex = operand->getOperandNumber(); |
407 | unsigned operandsStart = operands.getBeginOperandIndex(); |
408 | if (operandIndex < operandsStart || |
409 | operandIndex >= (operandsStart + operands.size())) |
410 | return; |
411 | |
412 | // Index the successor. |
413 | unsigned argIndex = operandIndex - operandsStart; |
414 | appendToQueue(dest->getArgument(argIndex)); |
415 | }; |
416 | // Thread uses into structured loop bodies and return value uses. |
417 | if (auto ro = mlir::dyn_cast<DoLoopOp>(owner)) { |
418 | structuredLoop(ro); |
419 | } else if (auto ro = mlir::dyn_cast<IterWhileOp>(owner)) { |
420 | structuredLoop(ro); |
421 | } else if (auto rs = mlir::dyn_cast<ResultOp>(owner)) { |
422 | // Thread any uses of fir.if that return the marked array value. |
423 | mlir::Operation *parent = rs->getParentRegion()->getParentOp(); |
424 | if (auto ifOp = mlir::dyn_cast<fir::IfOp>(parent)) |
425 | appendToQueue(ifOp.getResult(operand->getOperandNumber())); |
426 | } else if (mlir::isa<ArrayFetchOp>(owner)) { |
427 | // Keep track of array value fetches. |
428 | LLVM_DEBUG(llvm::dbgs() |
429 | << "add fetch {" << *owner << "} to array value set\n" ); |
430 | mentions.push_back(owner); |
431 | } else if (auto update = mlir::dyn_cast<ArrayUpdateOp>(owner)) { |
432 | // Keep track of array value updates and thread the return value uses. |
433 | LLVM_DEBUG(llvm::dbgs() |
434 | << "add update {" << *owner << "} to array value set\n" ); |
435 | mentions.push_back(owner); |
436 | appendToQueue(update.getResult()); |
437 | } else if (auto update = mlir::dyn_cast<ArrayModifyOp>(owner)) { |
438 | // Keep track of array value modification and thread the return value |
439 | // uses. |
440 | LLVM_DEBUG(llvm::dbgs() |
441 | << "add modify {" << *owner << "} to array value set\n" ); |
442 | mentions.push_back(owner); |
443 | appendToQueue(update.getResult(1)); |
444 | } else if (auto mention = mlir::dyn_cast<ArrayAccessOp>(owner)) { |
445 | mentions.push_back(owner); |
446 | } else if (auto amend = mlir::dyn_cast<ArrayAmendOp>(owner)) { |
447 | mentions.push_back(owner); |
448 | appendToQueue(amend.getResult()); |
449 | } else if (auto br = mlir::dyn_cast<mlir::cf::BranchOp>(owner)) { |
450 | branchOp(br.getDest(), br.getDestOperands()); |
451 | } else if (auto br = mlir::dyn_cast<mlir::cf::CondBranchOp>(owner)) { |
452 | branchOp(br.getTrueDest(), br.getTrueOperands()); |
453 | branchOp(br.getFalseDest(), br.getFalseOperands()); |
454 | } else if (mlir::isa<ArrayMergeStoreOp>(owner)) { |
455 | // do nothing |
456 | } else { |
457 | llvm::report_fatal_error("array value reached unexpected op" ); |
458 | } |
459 | } |
460 | loadMapSets.insert({load, visited}); |
461 | } |
462 | |
463 | static bool hasPointerType(mlir::Type type) { |
464 | if (auto boxTy = type.dyn_cast<BoxType>()) |
465 | type = boxTy.getEleTy(); |
466 | return type.isa<fir::PointerType>(); |
467 | } |
468 | |
469 | // This is a NF performance hack. It makes a simple test that the slices of the |
470 | // load, \p ld, and the merge store, \p st, are trivially mutually exclusive. |
471 | static bool mutuallyExclusiveSliceRange(ArrayLoadOp ld, ArrayMergeStoreOp st) { |
472 | // If the same array_load, then no further testing is warranted. |
473 | if (ld.getResult() == st.getOriginal()) |
474 | return false; |
475 | |
476 | auto getSliceOp = [](mlir::Value val) -> SliceOp { |
477 | if (!val) |
478 | return {}; |
479 | auto sliceOp = mlir::dyn_cast_or_null<SliceOp>(val.getDefiningOp()); |
480 | if (!sliceOp) |
481 | return {}; |
482 | return sliceOp; |
483 | }; |
484 | |
485 | auto ldSlice = getSliceOp(ld.getSlice()); |
486 | auto stSlice = getSliceOp(st.getSlice()); |
487 | if (!ldSlice || !stSlice) |
488 | return false; |
489 | |
490 | // Resign on subobject slices. |
491 | if (!ldSlice.getFields().empty() || !stSlice.getFields().empty() || |
492 | !ldSlice.getSubstr().empty() || !stSlice.getSubstr().empty()) |
493 | return false; |
494 | |
495 | // Crudely test that the two slices do not overlap by looking for the |
496 | // following general condition. If the slices look like (i:j) and (j+1:k) then |
497 | // these ranges do not overlap. The addend must be a constant. |
498 | auto ldTriples = ldSlice.getTriples(); |
499 | auto stTriples = stSlice.getTriples(); |
500 | const auto size = ldTriples.size(); |
501 | if (size != stTriples.size()) |
502 | return false; |
503 | |
504 | auto displacedByConstant = [](mlir::Value v1, mlir::Value v2) { |
505 | auto removeConvert = [](mlir::Value v) -> mlir::Operation * { |
506 | auto *op = v.getDefiningOp(); |
507 | while (auto conv = mlir::dyn_cast_or_null<ConvertOp>(op)) |
508 | op = conv.getValue().getDefiningOp(); |
509 | return op; |
510 | }; |
511 | |
512 | auto isPositiveConstant = [](mlir::Value v) -> bool { |
513 | if (auto conOp = |
514 | mlir::dyn_cast<mlir::arith::ConstantOp>(v.getDefiningOp())) |
515 | if (auto iattr = conOp.getValue().dyn_cast<mlir::IntegerAttr>()) |
516 | return iattr.getInt() > 0; |
517 | return false; |
518 | }; |
519 | |
520 | auto *op1 = removeConvert(v1); |
521 | auto *op2 = removeConvert(v2); |
522 | if (!op1 || !op2) |
523 | return false; |
524 | if (auto addi = mlir::dyn_cast<mlir::arith::AddIOp>(op2)) |
525 | if ((addi.getLhs().getDefiningOp() == op1 && |
526 | isPositiveConstant(addi.getRhs())) || |
527 | (addi.getRhs().getDefiningOp() == op1 && |
528 | isPositiveConstant(addi.getLhs()))) |
529 | return true; |
530 | if (auto subi = mlir::dyn_cast<mlir::arith::SubIOp>(op1)) |
531 | if (subi.getLhs().getDefiningOp() == op2 && |
532 | isPositiveConstant(subi.getRhs())) |
533 | return true; |
534 | return false; |
535 | }; |
536 | |
537 | for (std::remove_const_t<decltype(size)> i = 0; i < size; i += 3) { |
538 | // If both are loop invariant, skip to the next triple. |
539 | if (mlir::isa_and_nonnull<fir::UndefOp>(ldTriples[i + 1].getDefiningOp()) && |
540 | mlir::isa_and_nonnull<fir::UndefOp>(stTriples[i + 1].getDefiningOp())) { |
541 | // Unless either is a vector index, then be conservative. |
542 | if (mlir::isa_and_nonnull<fir::UndefOp>(ldTriples[i].getDefiningOp()) || |
543 | mlir::isa_and_nonnull<fir::UndefOp>(stTriples[i].getDefiningOp())) |
544 | return false; |
545 | continue; |
546 | } |
547 | // If identical, skip to the next triple. |
548 | if (ldTriples[i] == stTriples[i] && ldTriples[i + 1] == stTriples[i + 1] && |
549 | ldTriples[i + 2] == stTriples[i + 2]) |
550 | continue; |
551 | // If ubound and lbound are the same with a constant offset, skip to the |
552 | // next triple. |
553 | if (displacedByConstant(ldTriples[i + 1], stTriples[i]) || |
554 | displacedByConstant(stTriples[i + 1], ldTriples[i])) |
555 | continue; |
556 | return false; |
557 | } |
558 | LLVM_DEBUG(llvm::dbgs() << "detected non-overlapping slice ranges on " << ld |
559 | << " and " << st << ", which is not a conflict\n" ); |
560 | return true; |
561 | } |
562 | |
563 | /// Is there a conflict between the array value that was updated and to be |
564 | /// stored to `st` and the set of arrays loaded (`reach`) and used to compute |
565 | /// the updated value? |
566 | /// If `optimize` is true, use the variable attributes to prove that |
567 | /// there is no conflict. |
568 | static bool conflictOnLoad(llvm::ArrayRef<mlir::Operation *> reach, |
569 | ArrayMergeStoreOp st, bool optimize) { |
570 | mlir::Value load; |
571 | mlir::Value addr = st.getMemref(); |
572 | const bool storeHasPointerType = hasPointerType(addr.getType()); |
573 | for (auto *op : reach) |
574 | if (auto ld = mlir::dyn_cast<ArrayLoadOp>(op)) { |
575 | mlir::Type ldTy = ld.getMemref().getType(); |
576 | auto globalOpName = mlir::OperationName(fir::GlobalOp::getOperationName(), |
577 | ld.getContext()); |
578 | if (ld.getMemref() == addr) { |
579 | if (mutuallyExclusiveSliceRange(ld, st)) |
580 | continue; |
581 | if (ld.getResult() != st.getOriginal()) |
582 | return true; |
583 | if (load) { |
584 | // TODO: extend this to allow checking if the first `load` and this |
585 | // `ld` are mutually exclusive accesses but not identical. |
586 | return true; |
587 | } |
588 | load = ld; |
589 | } else if (storeHasPointerType) { |
590 | if (optimize && !hasPointerType(ldTy) && |
591 | !valueMayHaveFirAttributes( |
592 | ld.getMemref(), |
593 | {getTargetAttrName(), |
594 | fir::GlobalOp::getTargetAttrName(globalOpName).strref()})) |
595 | continue; |
596 | |
597 | return true; |
598 | } else if (hasPointerType(ldTy)) { |
599 | if (optimize && !storeHasPointerType && |
600 | !valueMayHaveFirAttributes( |
601 | addr, |
602 | {getTargetAttrName(), |
603 | fir::GlobalOp::getTargetAttrName(globalOpName).strref()})) |
604 | continue; |
605 | |
606 | return true; |
607 | } |
608 | // TODO: Check if types can also allow ruling out some cases. For now, |
609 | // the fact that equivalences is using pointer attribute to enforce |
610 | // aliasing is preventing any attempt to do so, and in general, it may |
611 | // be wrong to use this if any of the types is a complex or a derived |
612 | // for which it is possible to create a pointer to a part with a |
613 | // different type than the whole, although this deserve some more |
614 | // investigation because existing compiler behavior seem to diverge |
615 | // here. |
616 | } |
617 | return false; |
618 | } |
619 | |
620 | /// Is there an access vector conflict on the array being merged into? If the |
621 | /// access vectors diverge, then assume that there are potentially overlapping |
622 | /// loop-carried references. |
623 | static bool conflictOnMerge(llvm::ArrayRef<mlir::Operation *> mentions) { |
624 | if (mentions.size() < 2) |
625 | return false; |
626 | llvm::SmallVector<mlir::Value> indices; |
627 | LLVM_DEBUG(llvm::dbgs() << "check merge conflict on with " << mentions.size() |
628 | << " mentions on the list\n" ); |
629 | bool valSeen = false; |
630 | bool refSeen = false; |
631 | for (auto *op : mentions) { |
632 | llvm::SmallVector<mlir::Value> compareVector; |
633 | if (auto u = mlir::dyn_cast<ArrayUpdateOp>(op)) { |
634 | valSeen = true; |
635 | if (indices.empty()) { |
636 | indices = u.getIndices(); |
637 | continue; |
638 | } |
639 | compareVector = u.getIndices(); |
640 | } else if (auto f = mlir::dyn_cast<ArrayModifyOp>(op)) { |
641 | valSeen = true; |
642 | if (indices.empty()) { |
643 | indices = f.getIndices(); |
644 | continue; |
645 | } |
646 | compareVector = f.getIndices(); |
647 | } else if (auto f = mlir::dyn_cast<ArrayFetchOp>(op)) { |
648 | valSeen = true; |
649 | if (indices.empty()) { |
650 | indices = f.getIndices(); |
651 | continue; |
652 | } |
653 | compareVector = f.getIndices(); |
654 | } else if (auto f = mlir::dyn_cast<ArrayAccessOp>(op)) { |
655 | refSeen = true; |
656 | if (indices.empty()) { |
657 | indices = f.getIndices(); |
658 | continue; |
659 | } |
660 | compareVector = f.getIndices(); |
661 | } else if (mlir::isa<ArrayAmendOp>(op)) { |
662 | refSeen = true; |
663 | continue; |
664 | } else { |
665 | mlir::emitError(op->getLoc(), "unexpected operation in analysis" ); |
666 | } |
667 | if (compareVector.size() != indices.size() || |
668 | llvm::any_of(llvm::zip(compareVector, indices), [&](auto pair) { |
669 | return std::get<0>(pair) != std::get<1>(pair); |
670 | })) |
671 | return true; |
672 | LLVM_DEBUG(llvm::dbgs() << "vectors compare equal\n" ); |
673 | } |
674 | return valSeen && refSeen; |
675 | } |
676 | |
677 | /// With element-by-reference semantics, an amended array with more than once |
678 | /// access to the same loaded array are conservatively considered a conflict. |
679 | /// Note: the array copy can still be eliminated in subsequent optimizations. |
680 | static bool conflictOnReference(llvm::ArrayRef<mlir::Operation *> mentions) { |
681 | LLVM_DEBUG(llvm::dbgs() << "checking reference semantics " << mentions.size() |
682 | << '\n'); |
683 | if (mentions.size() < 3) |
684 | return false; |
685 | unsigned amendCount = 0; |
686 | unsigned accessCount = 0; |
687 | for (auto *op : mentions) { |
688 | if (mlir::isa<ArrayAmendOp>(op) && ++amendCount > 1) { |
689 | LLVM_DEBUG(llvm::dbgs() << "conflict: multiple amends of array value\n" ); |
690 | return true; |
691 | } |
692 | if (mlir::isa<ArrayAccessOp>(op) && ++accessCount > 1) { |
693 | LLVM_DEBUG(llvm::dbgs() |
694 | << "conflict: multiple accesses of array value\n" ); |
695 | return true; |
696 | } |
697 | if (mlir::isa<ArrayFetchOp, ArrayUpdateOp, ArrayModifyOp>(op)) { |
698 | LLVM_DEBUG(llvm::dbgs() |
699 | << "conflict: array value has both uses by-value and uses " |
700 | "by-reference. conservative assumption.\n" ); |
701 | return true; |
702 | } |
703 | } |
704 | return false; |
705 | } |
706 | |
707 | static mlir::Operation * |
708 | amendingAccess(llvm::ArrayRef<mlir::Operation *> mentions) { |
709 | for (auto *op : mentions) |
710 | if (auto amend = mlir::dyn_cast<ArrayAmendOp>(op)) |
711 | return amend.getMemref().getDefiningOp(); |
712 | return {}; |
713 | } |
714 | |
715 | // Are any conflicts present? The conflicts detected here are described above. |
716 | static bool conflictDetected(llvm::ArrayRef<mlir::Operation *> reach, |
717 | llvm::ArrayRef<mlir::Operation *> mentions, |
718 | ArrayMergeStoreOp st, bool optimize) { |
719 | return conflictOnLoad(reach, st, optimize) || conflictOnMerge(mentions); |
720 | } |
721 | |
722 | // Assume that any call to a function that uses host-associations will be |
723 | // modifying the output array. |
724 | static bool |
725 | conservativeCallConflict(llvm::ArrayRef<mlir::Operation *> reaches) { |
726 | return llvm::any_of(reaches, [](mlir::Operation *op) { |
727 | if (auto call = mlir::dyn_cast<fir::CallOp>(op)) |
728 | if (auto callee = |
729 | call.getCallableForCallee().dyn_cast<mlir::SymbolRefAttr>()) { |
730 | auto module = op->getParentOfType<mlir::ModuleOp>(); |
731 | return isInternalProcedure( |
732 | module.lookupSymbol<mlir::func::FuncOp>(callee)); |
733 | } |
734 | return false; |
735 | }); |
736 | } |
737 | |
738 | /// Constructor of the array copy analysis. |
739 | /// This performs the analysis and saves the intermediate results. |
740 | void ArrayCopyAnalysisBase::construct(mlir::Operation *topLevelOp) { |
741 | topLevelOp->walk([&](Operation *op) { |
742 | if (auto st = mlir::dyn_cast<fir::ArrayMergeStoreOp>(op)) { |
743 | llvm::SmallVector<mlir::Operation *> values; |
744 | ReachCollector::reachingValues(values, st.getSequence()); |
745 | bool callConflict = conservativeCallConflict(values); |
746 | llvm::SmallVector<mlir::Operation *> mentions; |
747 | arrayMentions(mentions, |
748 | mlir::cast<ArrayLoadOp>(st.getOriginal().getDefiningOp())); |
749 | bool conflict = conflictDetected(values, mentions, st, optimizeConflicts); |
750 | bool refConflict = conflictOnReference(mentions); |
751 | if (callConflict || conflict || refConflict) { |
752 | LLVM_DEBUG(llvm::dbgs() |
753 | << "CONFLICT: copies required for " << st << '\n' |
754 | << " adding conflicts on: " << *op << " and " |
755 | << st.getOriginal() << '\n'); |
756 | conflicts.insert(op); |
757 | conflicts.insert(st.getOriginal().getDefiningOp()); |
758 | if (auto *access = amendingAccess(mentions)) |
759 | amendAccesses.insert(access); |
760 | } |
761 | auto *ld = st.getOriginal().getDefiningOp(); |
762 | LLVM_DEBUG(llvm::dbgs() |
763 | << "map: adding {" << *ld << " -> " << st << "}\n" ); |
764 | useMap.insert({ld, op}); |
765 | } else if (auto load = mlir::dyn_cast<ArrayLoadOp>(op)) { |
766 | llvm::SmallVector<mlir::Operation *> mentions; |
767 | arrayMentions(mentions, load); |
768 | LLVM_DEBUG(llvm::dbgs() << "process load: " << load |
769 | << ", mentions: " << mentions.size() << '\n'); |
770 | for (auto *acc : mentions) { |
771 | LLVM_DEBUG(llvm::dbgs() << " mention: " << *acc << '\n'); |
772 | if (mlir::isa<ArrayAccessOp, ArrayAmendOp, ArrayFetchOp, ArrayUpdateOp, |
773 | ArrayModifyOp>(acc)) { |
774 | if (useMap.count(acc)) { |
775 | mlir::emitError( |
776 | load.getLoc(), |
777 | "The parallel semantics of multiple array_merge_stores per " |
778 | "array_load are not supported." ); |
779 | continue; |
780 | } |
781 | LLVM_DEBUG(llvm::dbgs() |
782 | << "map: adding {" << *acc << "} -> {" << load << "}\n" ); |
783 | useMap.insert({acc, op}); |
784 | } |
785 | } |
786 | } |
787 | }); |
788 | } |
789 | |
790 | //===----------------------------------------------------------------------===// |
791 | // Conversions for converting out of array value form. |
792 | //===----------------------------------------------------------------------===// |
793 | |
794 | namespace { |
795 | class ArrayLoadConversion : public mlir::OpRewritePattern<ArrayLoadOp> { |
796 | public: |
797 | using OpRewritePattern::OpRewritePattern; |
798 | |
799 | mlir::LogicalResult |
800 | matchAndRewrite(ArrayLoadOp load, |
801 | mlir::PatternRewriter &rewriter) const override { |
802 | LLVM_DEBUG(llvm::dbgs() << "replace load " << load << " with undef.\n" ); |
803 | rewriter.replaceOpWithNewOp<UndefOp>(load, load.getType()); |
804 | return mlir::success(); |
805 | } |
806 | }; |
807 | |
808 | class ArrayMergeStoreConversion |
809 | : public mlir::OpRewritePattern<ArrayMergeStoreOp> { |
810 | public: |
811 | using OpRewritePattern::OpRewritePattern; |
812 | |
813 | mlir::LogicalResult |
814 | matchAndRewrite(ArrayMergeStoreOp store, |
815 | mlir::PatternRewriter &rewriter) const override { |
816 | LLVM_DEBUG(llvm::dbgs() << "marking store " << store << " as dead.\n" ); |
817 | rewriter.eraseOp(store); |
818 | return mlir::success(); |
819 | } |
820 | }; |
821 | } // namespace |
822 | |
823 | static mlir::Type getEleTy(mlir::Type ty) { |
824 | auto eleTy = unwrapSequenceType(unwrapPassByRefType(ty)); |
825 | // FIXME: keep ptr/heap/ref information. |
826 | return ReferenceType::get(eleTy); |
827 | } |
828 | |
829 | // This is an unsafe way to deduce this (won't be true in internal |
830 | // procedure or inside select-rank for assumed-size). Only here to satisfy |
831 | // legacy code until removed. |
832 | static bool isAssumedSize(llvm::SmallVectorImpl<mlir::Value> &extents) { |
833 | if (extents.empty()) |
834 | return false; |
835 | auto cstLen = fir::getIntIfConstant(extents.back()); |
836 | return cstLen.has_value() && *cstLen == -1; |
837 | } |
838 | |
839 | // Extract extents from the ShapeOp/ShapeShiftOp into the result vector. |
840 | static bool getAdjustedExtents(mlir::Location loc, |
841 | mlir::PatternRewriter &rewriter, |
842 | ArrayLoadOp arrLoad, |
843 | llvm::SmallVectorImpl<mlir::Value> &result, |
844 | mlir::Value shape) { |
845 | bool copyUsingSlice = false; |
846 | auto *shapeOp = shape.getDefiningOp(); |
847 | if (auto s = mlir::dyn_cast_or_null<ShapeOp>(shapeOp)) { |
848 | auto e = s.getExtents(); |
849 | result.insert(result.end(), e.begin(), e.end()); |
850 | } else if (auto s = mlir::dyn_cast_or_null<ShapeShiftOp>(shapeOp)) { |
851 | auto e = s.getExtents(); |
852 | result.insert(result.end(), e.begin(), e.end()); |
853 | } else { |
854 | emitFatalError(loc, "not a fir.shape/fir.shape_shift op" ); |
855 | } |
856 | auto idxTy = rewriter.getIndexType(); |
857 | if (isAssumedSize(result)) { |
858 | // Use slice information to compute the extent of the column. |
859 | auto one = rewriter.create<mlir::arith::ConstantIndexOp>(loc, 1); |
860 | mlir::Value size = one; |
861 | if (mlir::Value sliceArg = arrLoad.getSlice()) { |
862 | if (auto sliceOp = |
863 | mlir::dyn_cast_or_null<SliceOp>(sliceArg.getDefiningOp())) { |
864 | auto triples = sliceOp.getTriples(); |
865 | const std::size_t tripleSize = triples.size(); |
866 | auto module = arrLoad->getParentOfType<mlir::ModuleOp>(); |
867 | FirOpBuilder builder(rewriter, module); |
868 | size = builder.genExtentFromTriplet(loc, triples[tripleSize - 3], |
869 | triples[tripleSize - 2], |
870 | triples[tripleSize - 1], idxTy); |
871 | copyUsingSlice = true; |
872 | } |
873 | } |
874 | result[result.size() - 1] = size; |
875 | } |
876 | return copyUsingSlice; |
877 | } |
878 | |
879 | /// Place the extents of the array load, \p arrLoad, into \p result and |
880 | /// return a ShapeOp or ShapeShiftOp with the same extents. If \p arrLoad is |
881 | /// loading a `!fir.box`, code will be generated to read the extents from the |
882 | /// boxed value, and the retunred shape Op will be built with the extents read |
883 | /// from the box. Otherwise, the extents will be extracted from the ShapeOp (or |
884 | /// ShapeShiftOp) argument of \p arrLoad. \p copyUsingSlice will be set to true |
885 | /// if slicing of the output array is to be done in the copy-in/copy-out rather |
886 | /// than in the elemental computation step. |
887 | static mlir::Value getOrReadExtentsAndShapeOp( |
888 | mlir::Location loc, mlir::PatternRewriter &rewriter, ArrayLoadOp arrLoad, |
889 | llvm::SmallVectorImpl<mlir::Value> &result, bool ©UsingSlice) { |
890 | assert(result.empty()); |
891 | if (arrLoad->hasAttr(fir::getOptionalAttrName())) |
892 | fir::emitFatalError( |
893 | loc, "shapes from array load of OPTIONAL arrays must not be used" ); |
894 | if (auto boxTy = arrLoad.getMemref().getType().dyn_cast<BoxType>()) { |
895 | auto rank = |
896 | dyn_cast_ptrOrBoxEleTy(boxTy).cast<SequenceType>().getDimension(); |
897 | auto idxTy = rewriter.getIndexType(); |
898 | for (decltype(rank) dim = 0; dim < rank; ++dim) { |
899 | auto dimVal = rewriter.create<mlir::arith::ConstantIndexOp>(loc, dim); |
900 | auto dimInfo = rewriter.create<BoxDimsOp>(loc, idxTy, idxTy, idxTy, |
901 | arrLoad.getMemref(), dimVal); |
902 | result.emplace_back(dimInfo.getResult(1)); |
903 | } |
904 | if (!arrLoad.getShape()) { |
905 | auto shapeType = ShapeType::get(rewriter.getContext(), rank); |
906 | return rewriter.create<ShapeOp>(loc, shapeType, result); |
907 | } |
908 | auto shiftOp = arrLoad.getShape().getDefiningOp<ShiftOp>(); |
909 | auto shapeShiftType = ShapeShiftType::get(rewriter.getContext(), rank); |
910 | llvm::SmallVector<mlir::Value> shapeShiftOperands; |
911 | for (auto [lb, extent] : llvm::zip(shiftOp.getOrigins(), result)) { |
912 | shapeShiftOperands.push_back(lb); |
913 | shapeShiftOperands.push_back(extent); |
914 | } |
915 | return rewriter.create<ShapeShiftOp>(loc, shapeShiftType, |
916 | shapeShiftOperands); |
917 | } |
918 | copyUsingSlice = |
919 | getAdjustedExtents(loc, rewriter, arrLoad, result, arrLoad.getShape()); |
920 | return arrLoad.getShape(); |
921 | } |
922 | |
923 | static mlir::Type toRefType(mlir::Type ty) { |
924 | if (fir::isa_ref_type(ty)) |
925 | return ty; |
926 | return fir::ReferenceType::get(ty); |
927 | } |
928 | |
929 | static llvm::SmallVector<mlir::Value> |
930 | getTypeParamsIfRawData(mlir::Location loc, FirOpBuilder &builder, |
931 | ArrayLoadOp arrLoad, mlir::Type ty) { |
932 | if (ty.isa<BoxType>()) |
933 | return {}; |
934 | return fir::factory::getTypeParams(loc, builder, arrLoad); |
935 | } |
936 | |
937 | static mlir::Value genCoorOp(mlir::PatternRewriter &rewriter, |
938 | mlir::Location loc, mlir::Type eleTy, |
939 | mlir::Type resTy, mlir::Value alloc, |
940 | mlir::Value shape, mlir::Value slice, |
941 | mlir::ValueRange indices, ArrayLoadOp load, |
942 | bool skipOrig = false) { |
943 | llvm::SmallVector<mlir::Value> originated; |
944 | if (skipOrig) |
945 | originated.assign(indices.begin(), indices.end()); |
946 | else |
947 | originated = factory::originateIndices(loc, rewriter, alloc.getType(), |
948 | shape, indices); |
949 | auto seqTy = dyn_cast_ptrOrBoxEleTy(alloc.getType()); |
950 | assert(seqTy && seqTy.isa<SequenceType>()); |
951 | const auto dimension = seqTy.cast<SequenceType>().getDimension(); |
952 | auto module = load->getParentOfType<mlir::ModuleOp>(); |
953 | FirOpBuilder builder(rewriter, module); |
954 | auto typeparams = getTypeParamsIfRawData(loc, builder, load, alloc.getType()); |
955 | mlir::Value result = rewriter.create<ArrayCoorOp>( |
956 | loc, eleTy, alloc, shape, slice, |
957 | llvm::ArrayRef<mlir::Value>{originated}.take_front(dimension), |
958 | typeparams); |
959 | if (dimension < originated.size()) |
960 | result = rewriter.create<fir::CoordinateOp>( |
961 | loc, resTy, result, |
962 | llvm::ArrayRef<mlir::Value>{originated}.drop_front(dimension)); |
963 | return result; |
964 | } |
965 | |
966 | static mlir::Value getCharacterLen(mlir::Location loc, FirOpBuilder &builder, |
967 | ArrayLoadOp load, CharacterType charTy) { |
968 | auto charLenTy = builder.getCharacterLengthType(); |
969 | if (charTy.hasDynamicLen()) { |
970 | if (load.getMemref().getType().isa<BoxType>()) { |
971 | // The loaded array is an emboxed value. Get the CHARACTER length from |
972 | // the box value. |
973 | auto eleSzInBytes = |
974 | builder.create<BoxEleSizeOp>(loc, charLenTy, load.getMemref()); |
975 | auto kindSize = |
976 | builder.getKindMap().getCharacterBitsize(charTy.getFKind()); |
977 | auto kindByteSize = |
978 | builder.createIntegerConstant(loc, charLenTy, kindSize / 8); |
979 | return builder.create<mlir::arith::DivSIOp>(loc, eleSzInBytes, |
980 | kindByteSize); |
981 | } |
982 | // The loaded array is a (set of) unboxed values. If the CHARACTER's |
983 | // length is not a constant, it must be provided as a type parameter to |
984 | // the array_load. |
985 | auto typeparams = load.getTypeparams(); |
986 | assert(typeparams.size() > 0 && "expected type parameters on array_load" ); |
987 | return typeparams.back(); |
988 | } |
989 | // The typical case: the length of the CHARACTER is a compile-time |
990 | // constant that is encoded in the type information. |
991 | return builder.createIntegerConstant(loc, charLenTy, charTy.getLen()); |
992 | } |
993 | /// Generate a shallow array copy. This is used for both copy-in and copy-out. |
994 | template <bool CopyIn> |
995 | void genArrayCopy(mlir::Location loc, mlir::PatternRewriter &rewriter, |
996 | mlir::Value dst, mlir::Value src, mlir::Value shapeOp, |
997 | mlir::Value sliceOp, ArrayLoadOp arrLoad) { |
998 | auto insPt = rewriter.saveInsertionPoint(); |
999 | llvm::SmallVector<mlir::Value> indices; |
1000 | llvm::SmallVector<mlir::Value> extents; |
1001 | bool copyUsingSlice = |
1002 | getAdjustedExtents(loc, rewriter, arrLoad, extents, shapeOp); |
1003 | auto idxTy = rewriter.getIndexType(); |
1004 | // Build loop nest from column to row. |
1005 | for (auto sh : llvm::reverse(extents)) { |
1006 | auto ubi = rewriter.create<ConvertOp>(loc, idxTy, sh); |
1007 | auto zero = rewriter.create<mlir::arith::ConstantIndexOp>(loc, 0); |
1008 | auto one = rewriter.create<mlir::arith::ConstantIndexOp>(loc, 1); |
1009 | auto ub = rewriter.create<mlir::arith::SubIOp>(loc, idxTy, ubi, one); |
1010 | auto loop = rewriter.create<DoLoopOp>(loc, zero, ub, one); |
1011 | rewriter.setInsertionPointToStart(loop.getBody()); |
1012 | indices.push_back(loop.getInductionVar()); |
1013 | } |
1014 | // Reverse the indices so they are in column-major order. |
1015 | std::reverse(indices.begin(), indices.end()); |
1016 | auto module = arrLoad->getParentOfType<mlir::ModuleOp>(); |
1017 | FirOpBuilder builder(rewriter, module); |
1018 | auto fromAddr = rewriter.create<ArrayCoorOp>( |
1019 | loc, getEleTy(src.getType()), src, shapeOp, |
1020 | CopyIn && copyUsingSlice ? sliceOp : mlir::Value{}, |
1021 | factory::originateIndices(loc, rewriter, src.getType(), shapeOp, indices), |
1022 | getTypeParamsIfRawData(loc, builder, arrLoad, src.getType())); |
1023 | auto toAddr = rewriter.create<ArrayCoorOp>( |
1024 | loc, getEleTy(dst.getType()), dst, shapeOp, |
1025 | !CopyIn && copyUsingSlice ? sliceOp : mlir::Value{}, |
1026 | factory::originateIndices(loc, rewriter, dst.getType(), shapeOp, indices), |
1027 | getTypeParamsIfRawData(loc, builder, arrLoad, dst.getType())); |
1028 | auto eleTy = unwrapSequenceType(unwrapPassByRefType(dst.getType())); |
1029 | // Copy from (to) object to (from) temp copy of same object. |
1030 | if (auto charTy = eleTy.dyn_cast<CharacterType>()) { |
1031 | auto len = getCharacterLen(loc, builder, arrLoad, charTy); |
1032 | CharBoxValue toChar(toAddr, len); |
1033 | CharBoxValue fromChar(fromAddr, len); |
1034 | factory::genScalarAssignment(builder, loc, toChar, fromChar); |
1035 | } else { |
1036 | if (hasDynamicSize(eleTy)) |
1037 | TODO(loc, "copy element of dynamic size" ); |
1038 | factory::genScalarAssignment(builder, loc, toAddr, fromAddr); |
1039 | } |
1040 | rewriter.restoreInsertionPoint(insPt); |
1041 | } |
1042 | |
1043 | /// The array load may be either a boxed or unboxed value. If the value is |
1044 | /// boxed, we read the type parameters from the boxed value. |
1045 | static llvm::SmallVector<mlir::Value> |
1046 | genArrayLoadTypeParameters(mlir::Location loc, mlir::PatternRewriter &rewriter, |
1047 | ArrayLoadOp load) { |
1048 | if (load.getTypeparams().empty()) { |
1049 | auto eleTy = |
1050 | unwrapSequenceType(unwrapPassByRefType(load.getMemref().getType())); |
1051 | if (hasDynamicSize(eleTy)) { |
1052 | if (auto charTy = eleTy.dyn_cast<CharacterType>()) { |
1053 | assert(load.getMemref().getType().isa<BoxType>()); |
1054 | auto module = load->getParentOfType<mlir::ModuleOp>(); |
1055 | FirOpBuilder builder(rewriter, module); |
1056 | return {getCharacterLen(loc, builder, load, charTy)}; |
1057 | } |
1058 | TODO(loc, "unhandled dynamic type parameters" ); |
1059 | } |
1060 | return {}; |
1061 | } |
1062 | return load.getTypeparams(); |
1063 | } |
1064 | |
1065 | static llvm::SmallVector<mlir::Value> |
1066 | findNonconstantExtents(mlir::Type memrefTy, |
1067 | llvm::ArrayRef<mlir::Value> extents) { |
1068 | llvm::SmallVector<mlir::Value> nce; |
1069 | auto arrTy = unwrapPassByRefType(memrefTy); |
1070 | auto seqTy = arrTy.cast<SequenceType>(); |
1071 | for (auto [s, x] : llvm::zip(seqTy.getShape(), extents)) |
1072 | if (s == SequenceType::getUnknownExtent()) |
1073 | nce.emplace_back(x); |
1074 | if (extents.size() > seqTy.getShape().size()) |
1075 | for (auto x : extents.drop_front(seqTy.getShape().size())) |
1076 | nce.emplace_back(x); |
1077 | return nce; |
1078 | } |
1079 | |
1080 | /// Allocate temporary storage for an ArrayLoadOp \load and initialize any |
1081 | /// allocatable direct components of the array elements with an unallocated |
1082 | /// status. Returns the temporary address as well as a callback to generate the |
1083 | /// temporary clean-up once it has been used. The clean-up will take care of |
1084 | /// deallocating all the element allocatable components that may have been |
1085 | /// allocated while using the temporary. |
1086 | static std::pair<mlir::Value, |
1087 | std::function<void(mlir::PatternRewriter &rewriter)>> |
1088 | allocateArrayTemp(mlir::Location loc, mlir::PatternRewriter &rewriter, |
1089 | ArrayLoadOp load, llvm::ArrayRef<mlir::Value> extents, |
1090 | mlir::Value shape) { |
1091 | mlir::Type baseType = load.getMemref().getType(); |
1092 | llvm::SmallVector<mlir::Value> nonconstantExtents = |
1093 | findNonconstantExtents(baseType, extents); |
1094 | llvm::SmallVector<mlir::Value> typeParams = |
1095 | genArrayLoadTypeParameters(loc, rewriter, load); |
1096 | mlir::Value allocmem = rewriter.create<AllocMemOp>( |
1097 | loc, dyn_cast_ptrOrBoxEleTy(baseType), typeParams, nonconstantExtents); |
1098 | mlir::Type eleType = |
1099 | fir::unwrapSequenceType(fir::unwrapPassByRefType(baseType)); |
1100 | if (fir::isRecordWithAllocatableMember(eleType)) { |
1101 | // The allocatable component descriptors need to be set to a clean |
1102 | // deallocated status before anything is done with them. |
1103 | mlir::Value box = rewriter.create<fir::EmboxOp>( |
1104 | loc, fir::BoxType::get(allocmem.getType()), allocmem, shape, |
1105 | /*slice=*/mlir::Value{}, typeParams); |
1106 | auto module = load->getParentOfType<mlir::ModuleOp>(); |
1107 | FirOpBuilder builder(rewriter, module); |
1108 | runtime::genDerivedTypeInitialize(builder, loc, box); |
1109 | // Any allocatable component that may have been allocated must be |
1110 | // deallocated during the clean-up. |
1111 | auto cleanup = [=](mlir::PatternRewriter &r) { |
1112 | FirOpBuilder builder(r, module); |
1113 | runtime::genDerivedTypeDestroy(builder, loc, box); |
1114 | r.create<FreeMemOp>(loc, allocmem); |
1115 | }; |
1116 | return {allocmem, cleanup}; |
1117 | } |
1118 | auto cleanup = [=](mlir::PatternRewriter &r) { |
1119 | r.create<FreeMemOp>(loc, allocmem); |
1120 | }; |
1121 | return {allocmem, cleanup}; |
1122 | } |
1123 | |
1124 | namespace { |
1125 | /// Conversion of fir.array_update and fir.array_modify Ops. |
1126 | /// If there is a conflict for the update, then we need to perform a |
1127 | /// copy-in/copy-out to preserve the original values of the array. If there is |
1128 | /// no conflict, then it is save to eschew making any copies. |
1129 | template <typename ArrayOp> |
1130 | class ArrayUpdateConversionBase : public mlir::OpRewritePattern<ArrayOp> { |
1131 | public: |
1132 | // TODO: Implement copy/swap semantics? |
1133 | explicit ArrayUpdateConversionBase(mlir::MLIRContext *ctx, |
1134 | const ArrayCopyAnalysisBase &a, |
1135 | const OperationUseMapT &m) |
1136 | : mlir::OpRewritePattern<ArrayOp>{ctx}, analysis{a}, useMap{m} {} |
1137 | |
1138 | /// The array_access, \p access, is to be to a cloned copy due to a potential |
1139 | /// conflict. Uses copy-in/copy-out semantics and not copy/swap. |
1140 | mlir::Value referenceToClone(mlir::Location loc, |
1141 | mlir::PatternRewriter &rewriter, |
1142 | ArrayOp access) const { |
1143 | LLVM_DEBUG(llvm::dbgs() |
1144 | << "generating copy-in/copy-out loops for " << access << '\n'); |
1145 | auto *op = access.getOperation(); |
1146 | auto *loadOp = useMap.lookup(op); |
1147 | auto load = mlir::cast<ArrayLoadOp>(loadOp); |
1148 | auto eleTy = access.getType(); |
1149 | rewriter.setInsertionPoint(loadOp); |
1150 | // Copy in. |
1151 | llvm::SmallVector<mlir::Value> extents; |
1152 | bool copyUsingSlice = false; |
1153 | auto shapeOp = getOrReadExtentsAndShapeOp(loc, rewriter, load, extents, |
1154 | copyUsingSlice); |
1155 | auto [allocmem, genTempCleanUp] = |
1156 | allocateArrayTemp(loc, rewriter, load, extents, shapeOp); |
1157 | genArrayCopy</*copyIn=*/true>(load.getLoc(), rewriter, allocmem, |
1158 | load.getMemref(), shapeOp, load.getSlice(), |
1159 | load); |
1160 | // Generate the reference for the access. |
1161 | rewriter.setInsertionPoint(op); |
1162 | auto coor = genCoorOp( |
1163 | rewriter, loc, getEleTy(load.getType()), eleTy, allocmem, shapeOp, |
1164 | copyUsingSlice ? mlir::Value{} : load.getSlice(), access.getIndices(), |
1165 | load, access->hasAttr(factory::attrFortranArrayOffsets())); |
1166 | // Copy out. |
1167 | auto *storeOp = useMap.lookup(loadOp); |
1168 | auto store = mlir::cast<ArrayMergeStoreOp>(storeOp); |
1169 | rewriter.setInsertionPoint(storeOp); |
1170 | // Copy out. |
1171 | genArrayCopy</*copyIn=*/false>(store.getLoc(), rewriter, store.getMemref(), |
1172 | allocmem, shapeOp, store.getSlice(), load); |
1173 | genTempCleanUp(rewriter); |
1174 | return coor; |
1175 | } |
1176 | |
1177 | /// Copy the RHS element into the LHS and insert copy-in/copy-out between a |
1178 | /// temp and the LHS if the analysis found potential overlaps between the RHS |
1179 | /// and LHS arrays. The element copy generator must be provided in \p |
1180 | /// assignElement. \p update must be the ArrayUpdateOp or the ArrayModifyOp. |
1181 | /// Returns the address of the LHS element inside the loop and the LHS |
1182 | /// ArrayLoad result. |
1183 | std::pair<mlir::Value, mlir::Value> |
1184 | materializeAssignment(mlir::Location loc, mlir::PatternRewriter &rewriter, |
1185 | ArrayOp update, |
1186 | const std::function<void(mlir::Value)> &assignElement, |
1187 | mlir::Type lhsEltRefType) const { |
1188 | auto *op = update.getOperation(); |
1189 | auto *loadOp = useMap.lookup(op); |
1190 | auto load = mlir::cast<ArrayLoadOp>(loadOp); |
1191 | LLVM_DEBUG(llvm::outs() << "does " << load << " have a conflict?\n" ); |
1192 | if (analysis.hasPotentialConflict(loadOp)) { |
1193 | // If there is a conflict between the arrays, then we copy the lhs array |
1194 | // to a temporary, update the temporary, and copy the temporary back to |
1195 | // the lhs array. This yields Fortran's copy-in copy-out array semantics. |
1196 | LLVM_DEBUG(llvm::outs() << "Yes, conflict was found\n" ); |
1197 | rewriter.setInsertionPoint(loadOp); |
1198 | // Copy in. |
1199 | llvm::SmallVector<mlir::Value> extents; |
1200 | bool copyUsingSlice = false; |
1201 | auto shapeOp = getOrReadExtentsAndShapeOp(loc, rewriter, load, extents, |
1202 | copyUsingSlice); |
1203 | auto [allocmem, genTempCleanUp] = |
1204 | allocateArrayTemp(loc, rewriter, load, extents, shapeOp); |
1205 | |
1206 | genArrayCopy</*copyIn=*/true>(load.getLoc(), rewriter, allocmem, |
1207 | load.getMemref(), shapeOp, load.getSlice(), |
1208 | load); |
1209 | rewriter.setInsertionPoint(op); |
1210 | auto coor = genCoorOp( |
1211 | rewriter, loc, getEleTy(load.getType()), lhsEltRefType, allocmem, |
1212 | shapeOp, copyUsingSlice ? mlir::Value{} : load.getSlice(), |
1213 | update.getIndices(), load, |
1214 | update->hasAttr(factory::attrFortranArrayOffsets())); |
1215 | assignElement(coor); |
1216 | auto *storeOp = useMap.lookup(loadOp); |
1217 | auto store = mlir::cast<ArrayMergeStoreOp>(storeOp); |
1218 | rewriter.setInsertionPoint(storeOp); |
1219 | // Copy out. |
1220 | genArrayCopy</*copyIn=*/false>(store.getLoc(), rewriter, |
1221 | store.getMemref(), allocmem, shapeOp, |
1222 | store.getSlice(), load); |
1223 | genTempCleanUp(rewriter); |
1224 | return {coor, load.getResult()}; |
1225 | } |
1226 | // Otherwise, when there is no conflict (a possible loop-carried |
1227 | // dependence), the lhs array can be updated in place. |
1228 | LLVM_DEBUG(llvm::outs() << "No, conflict wasn't found\n" ); |
1229 | rewriter.setInsertionPoint(op); |
1230 | auto coorTy = getEleTy(load.getType()); |
1231 | auto coor = |
1232 | genCoorOp(rewriter, loc, coorTy, lhsEltRefType, load.getMemref(), |
1233 | load.getShape(), load.getSlice(), update.getIndices(), load, |
1234 | update->hasAttr(factory::attrFortranArrayOffsets())); |
1235 | assignElement(coor); |
1236 | return {coor, load.getResult()}; |
1237 | } |
1238 | |
1239 | protected: |
1240 | const ArrayCopyAnalysisBase &analysis; |
1241 | const OperationUseMapT &useMap; |
1242 | }; |
1243 | |
1244 | class ArrayUpdateConversion : public ArrayUpdateConversionBase<ArrayUpdateOp> { |
1245 | public: |
1246 | explicit ArrayUpdateConversion(mlir::MLIRContext *ctx, |
1247 | const ArrayCopyAnalysisBase &a, |
1248 | const OperationUseMapT &m) |
1249 | : ArrayUpdateConversionBase{ctx, a, m} {} |
1250 | |
1251 | mlir::LogicalResult |
1252 | matchAndRewrite(ArrayUpdateOp update, |
1253 | mlir::PatternRewriter &rewriter) const override { |
1254 | auto loc = update.getLoc(); |
1255 | auto assignElement = [&](mlir::Value coor) { |
1256 | auto input = update.getMerge(); |
1257 | if (auto inEleTy = dyn_cast_ptrEleTy(input.getType())) { |
1258 | emitFatalError(loc, "array_update on references not supported" ); |
1259 | } else { |
1260 | rewriter.create<fir::StoreOp>(loc, input, coor); |
1261 | } |
1262 | }; |
1263 | auto lhsEltRefType = toRefType(update.getMerge().getType()); |
1264 | auto [_, lhsLoadResult] = materializeAssignment( |
1265 | loc, rewriter, update, assignElement, lhsEltRefType); |
1266 | update.replaceAllUsesWith(lhsLoadResult); |
1267 | rewriter.replaceOp(update, lhsLoadResult); |
1268 | return mlir::success(); |
1269 | } |
1270 | }; |
1271 | |
1272 | class ArrayModifyConversion : public ArrayUpdateConversionBase<ArrayModifyOp> { |
1273 | public: |
1274 | explicit ArrayModifyConversion(mlir::MLIRContext *ctx, |
1275 | const ArrayCopyAnalysisBase &a, |
1276 | const OperationUseMapT &m) |
1277 | : ArrayUpdateConversionBase{ctx, a, m} {} |
1278 | |
1279 | mlir::LogicalResult |
1280 | matchAndRewrite(ArrayModifyOp modify, |
1281 | mlir::PatternRewriter &rewriter) const override { |
1282 | auto loc = modify.getLoc(); |
1283 | auto assignElement = [](mlir::Value) { |
1284 | // Assignment already materialized by lowering using lhs element address. |
1285 | }; |
1286 | auto lhsEltRefType = modify.getResult(0).getType(); |
1287 | auto [lhsEltCoor, lhsLoadResult] = materializeAssignment( |
1288 | loc, rewriter, modify, assignElement, lhsEltRefType); |
1289 | modify.replaceAllUsesWith(mlir::ValueRange{lhsEltCoor, lhsLoadResult}); |
1290 | rewriter.replaceOp(modify, mlir::ValueRange{lhsEltCoor, lhsLoadResult}); |
1291 | return mlir::success(); |
1292 | } |
1293 | }; |
1294 | |
1295 | class ArrayFetchConversion : public mlir::OpRewritePattern<ArrayFetchOp> { |
1296 | public: |
1297 | explicit ArrayFetchConversion(mlir::MLIRContext *ctx, |
1298 | const OperationUseMapT &m) |
1299 | : OpRewritePattern{ctx}, useMap{m} {} |
1300 | |
1301 | mlir::LogicalResult |
1302 | matchAndRewrite(ArrayFetchOp fetch, |
1303 | mlir::PatternRewriter &rewriter) const override { |
1304 | auto *op = fetch.getOperation(); |
1305 | rewriter.setInsertionPoint(op); |
1306 | auto load = mlir::cast<ArrayLoadOp>(useMap.lookup(op)); |
1307 | auto loc = fetch.getLoc(); |
1308 | auto coor = genCoorOp( |
1309 | rewriter, loc, getEleTy(load.getType()), toRefType(fetch.getType()), |
1310 | load.getMemref(), load.getShape(), load.getSlice(), fetch.getIndices(), |
1311 | load, fetch->hasAttr(factory::attrFortranArrayOffsets())); |
1312 | if (isa_ref_type(fetch.getType())) |
1313 | rewriter.replaceOp(fetch, coor); |
1314 | else |
1315 | rewriter.replaceOpWithNewOp<fir::LoadOp>(fetch, coor); |
1316 | return mlir::success(); |
1317 | } |
1318 | |
1319 | private: |
1320 | const OperationUseMapT &useMap; |
1321 | }; |
1322 | |
1323 | /// As array_access op is like an array_fetch op, except that it does not imply |
1324 | /// a load op. (It operates in the reference domain.) |
1325 | class ArrayAccessConversion : public ArrayUpdateConversionBase<ArrayAccessOp> { |
1326 | public: |
1327 | explicit ArrayAccessConversion(mlir::MLIRContext *ctx, |
1328 | const ArrayCopyAnalysisBase &a, |
1329 | const OperationUseMapT &m) |
1330 | : ArrayUpdateConversionBase{ctx, a, m} {} |
1331 | |
1332 | mlir::LogicalResult |
1333 | matchAndRewrite(ArrayAccessOp access, |
1334 | mlir::PatternRewriter &rewriter) const override { |
1335 | auto *op = access.getOperation(); |
1336 | auto loc = access.getLoc(); |
1337 | if (analysis.inAmendAccessSet(op)) { |
1338 | // This array_access is associated with an array_amend and there is a |
1339 | // conflict. Make a copy to store into. |
1340 | auto result = referenceToClone(loc, rewriter, access); |
1341 | access.replaceAllUsesWith(result); |
1342 | rewriter.replaceOp(access, result); |
1343 | return mlir::success(); |
1344 | } |
1345 | rewriter.setInsertionPoint(op); |
1346 | auto load = mlir::cast<ArrayLoadOp>(useMap.lookup(op)); |
1347 | auto coor = genCoorOp( |
1348 | rewriter, loc, getEleTy(load.getType()), toRefType(access.getType()), |
1349 | load.getMemref(), load.getShape(), load.getSlice(), access.getIndices(), |
1350 | load, access->hasAttr(factory::attrFortranArrayOffsets())); |
1351 | rewriter.replaceOp(access, coor); |
1352 | return mlir::success(); |
1353 | } |
1354 | }; |
1355 | |
1356 | /// An array_amend op is a marker to record which array access is being used to |
1357 | /// update an array value. After this pass runs, an array_amend has no |
1358 | /// semantics. We rewrite these to undefined values here to remove them while |
1359 | /// preserving SSA form. |
1360 | class ArrayAmendConversion : public mlir::OpRewritePattern<ArrayAmendOp> { |
1361 | public: |
1362 | explicit ArrayAmendConversion(mlir::MLIRContext *ctx) |
1363 | : OpRewritePattern{ctx} {} |
1364 | |
1365 | mlir::LogicalResult |
1366 | matchAndRewrite(ArrayAmendOp amend, |
1367 | mlir::PatternRewriter &rewriter) const override { |
1368 | auto *op = amend.getOperation(); |
1369 | rewriter.setInsertionPoint(op); |
1370 | auto loc = amend.getLoc(); |
1371 | auto undef = rewriter.create<UndefOp>(loc, amend.getType()); |
1372 | rewriter.replaceOp(amend, undef.getResult()); |
1373 | return mlir::success(); |
1374 | } |
1375 | }; |
1376 | |
1377 | class ArrayValueCopyConverter |
1378 | : public fir::impl::ArrayValueCopyBase<ArrayValueCopyConverter> { |
1379 | public: |
1380 | ArrayValueCopyConverter() = default; |
1381 | ArrayValueCopyConverter(const fir::ArrayValueCopyOptions &options) |
1382 | : Base(options) {} |
1383 | |
1384 | void runOnOperation() override { |
1385 | auto func = getOperation(); |
1386 | LLVM_DEBUG(llvm::dbgs() << "\n\narray-value-copy pass on function '" |
1387 | << func.getName() << "'\n" ); |
1388 | auto *context = &getContext(); |
1389 | |
1390 | // Perform the conflict analysis. |
1391 | const ArrayCopyAnalysisBase *analysis; |
1392 | if (optimizeConflicts) |
1393 | analysis = &getAnalysis<ArrayCopyAnalysisOptimized>(); |
1394 | else |
1395 | analysis = &getAnalysis<ArrayCopyAnalysis>(); |
1396 | |
1397 | const auto &useMap = analysis->getUseMap(); |
1398 | |
1399 | mlir::RewritePatternSet patterns1(context); |
1400 | patterns1.insert<ArrayFetchConversion>(context, useMap); |
1401 | patterns1.insert<ArrayUpdateConversion>(context, *analysis, useMap); |
1402 | patterns1.insert<ArrayModifyConversion>(context, *analysis, useMap); |
1403 | patterns1.insert<ArrayAccessConversion>(context, *analysis, useMap); |
1404 | patterns1.insert<ArrayAmendConversion>(context); |
1405 | mlir::ConversionTarget target(*context); |
1406 | target |
1407 | .addLegalDialect<FIROpsDialect, mlir::scf::SCFDialect, |
1408 | mlir::arith::ArithDialect, mlir::func::FuncDialect>(); |
1409 | target.addIllegalOp<ArrayAccessOp, ArrayAmendOp, ArrayFetchOp, |
1410 | ArrayUpdateOp, ArrayModifyOp>(); |
1411 | // Rewrite the array fetch and array update ops. |
1412 | if (mlir::failed( |
1413 | mlir::applyPartialConversion(func, target, std::move(patterns1)))) { |
1414 | mlir::emitError(mlir::UnknownLoc::get(context), |
1415 | "failure in array-value-copy pass, phase 1" ); |
1416 | signalPassFailure(); |
1417 | } |
1418 | |
1419 | mlir::RewritePatternSet patterns2(context); |
1420 | patterns2.insert<ArrayLoadConversion>(context); |
1421 | patterns2.insert<ArrayMergeStoreConversion>(context); |
1422 | target.addIllegalOp<ArrayLoadOp, ArrayMergeStoreOp>(); |
1423 | if (mlir::failed( |
1424 | mlir::applyPartialConversion(func, target, std::move(patterns2)))) { |
1425 | mlir::emitError(mlir::UnknownLoc::get(context), |
1426 | "failure in array-value-copy pass, phase 2" ); |
1427 | signalPassFailure(); |
1428 | } |
1429 | } |
1430 | }; |
1431 | } // namespace |
1432 | |
1433 | std::unique_ptr<mlir::Pass> |
1434 | fir::createArrayValueCopyPass(fir::ArrayValueCopyOptions options) { |
1435 | return std::make_unique<ArrayValueCopyConverter>(options); |
1436 | } |
1437 | |