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Vikram TV7e98d692018-09-12 01:59:43 +00001//===- llvm/Analysis/IVDescriptors.cpp - IndVar Descriptors -----*- C++ -*-===//
2//
Chandler Carruth2946cd72019-01-19 08:50:56 +00003// 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
Vikram TV7e98d692018-09-12 01:59:43 +00006//
7//===----------------------------------------------------------------------===//
8//
9// This file "describes" induction and recurrence variables.
10//
11//===----------------------------------------------------------------------===//
12
13#include "llvm/Analysis/IVDescriptors.h"
14#include "llvm/ADT/ScopeExit.h"
15#include "llvm/Analysis/AliasAnalysis.h"
16#include "llvm/Analysis/BasicAliasAnalysis.h"
Richard Trieu5f436fc2019-02-06 02:52:52 +000017#include "llvm/Analysis/DomTreeUpdater.h"
Vikram TV7e98d692018-09-12 01:59:43 +000018#include "llvm/Analysis/GlobalsModRef.h"
19#include "llvm/Analysis/InstructionSimplify.h"
20#include "llvm/Analysis/LoopInfo.h"
21#include "llvm/Analysis/LoopPass.h"
22#include "llvm/Analysis/MustExecute.h"
23#include "llvm/Analysis/ScalarEvolution.h"
24#include "llvm/Analysis/ScalarEvolutionAliasAnalysis.h"
25#include "llvm/Analysis/ScalarEvolutionExpander.h"
26#include "llvm/Analysis/ScalarEvolutionExpressions.h"
27#include "llvm/Analysis/TargetTransformInfo.h"
28#include "llvm/Analysis/ValueTracking.h"
Vikram TV7e98d692018-09-12 01:59:43 +000029#include "llvm/IR/Dominators.h"
30#include "llvm/IR/Instructions.h"
31#include "llvm/IR/Module.h"
32#include "llvm/IR/PatternMatch.h"
33#include "llvm/IR/ValueHandle.h"
34#include "llvm/Pass.h"
35#include "llvm/Support/Debug.h"
36#include "llvm/Support/KnownBits.h"
Vikram TV7e98d692018-09-12 01:59:43 +000037
38using namespace llvm;
39using namespace llvm::PatternMatch;
40
41#define DEBUG_TYPE "iv-descriptors"
42
43bool RecurrenceDescriptor::areAllUsesIn(Instruction *I,
44 SmallPtrSetImpl<Instruction *> &Set) {
45 for (User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use)
46 if (!Set.count(dyn_cast<Instruction>(*Use)))
47 return false;
48 return true;
49}
50
51bool RecurrenceDescriptor::isIntegerRecurrenceKind(RecurrenceKind Kind) {
52 switch (Kind) {
53 default:
54 break;
55 case RK_IntegerAdd:
56 case RK_IntegerMult:
57 case RK_IntegerOr:
58 case RK_IntegerAnd:
59 case RK_IntegerXor:
60 case RK_IntegerMinMax:
61 return true;
62 }
63 return false;
64}
65
66bool RecurrenceDescriptor::isFloatingPointRecurrenceKind(RecurrenceKind Kind) {
67 return (Kind != RK_NoRecurrence) && !isIntegerRecurrenceKind(Kind);
68}
69
70bool RecurrenceDescriptor::isArithmeticRecurrenceKind(RecurrenceKind Kind) {
71 switch (Kind) {
72 default:
73 break;
74 case RK_IntegerAdd:
75 case RK_IntegerMult:
76 case RK_FloatAdd:
77 case RK_FloatMult:
78 return true;
79 }
80 return false;
81}
82
83/// Determines if Phi may have been type-promoted. If Phi has a single user
84/// that ANDs the Phi with a type mask, return the user. RT is updated to
85/// account for the narrower bit width represented by the mask, and the AND
86/// instruction is added to CI.
87static Instruction *lookThroughAnd(PHINode *Phi, Type *&RT,
88 SmallPtrSetImpl<Instruction *> &Visited,
89 SmallPtrSetImpl<Instruction *> &CI) {
90 if (!Phi->hasOneUse())
91 return Phi;
92
93 const APInt *M = nullptr;
94 Instruction *I, *J = cast<Instruction>(Phi->use_begin()->getUser());
95
96 // Matches either I & 2^x-1 or 2^x-1 & I. If we find a match, we update RT
97 // with a new integer type of the corresponding bit width.
98 if (match(J, m_c_And(m_Instruction(I), m_APInt(M)))) {
99 int32_t Bits = (*M + 1).exactLogBase2();
100 if (Bits > 0) {
101 RT = IntegerType::get(Phi->getContext(), Bits);
102 Visited.insert(Phi);
103 CI.insert(J);
104 return J;
105 }
106 }
107 return Phi;
108}
109
110/// Compute the minimal bit width needed to represent a reduction whose exit
111/// instruction is given by Exit.
112static std::pair<Type *, bool> computeRecurrenceType(Instruction *Exit,
113 DemandedBits *DB,
114 AssumptionCache *AC,
115 DominatorTree *DT) {
116 bool IsSigned = false;
117 const DataLayout &DL = Exit->getModule()->getDataLayout();
118 uint64_t MaxBitWidth = DL.getTypeSizeInBits(Exit->getType());
119
120 if (DB) {
121 // Use the demanded bits analysis to determine the bits that are live out
122 // of the exit instruction, rounding up to the nearest power of two. If the
123 // use of demanded bits results in a smaller bit width, we know the value
124 // must be positive (i.e., IsSigned = false), because if this were not the
125 // case, the sign bit would have been demanded.
126 auto Mask = DB->getDemandedBits(Exit);
127 MaxBitWidth = Mask.getBitWidth() - Mask.countLeadingZeros();
128 }
129
130 if (MaxBitWidth == DL.getTypeSizeInBits(Exit->getType()) && AC && DT) {
131 // If demanded bits wasn't able to limit the bit width, we can try to use
132 // value tracking instead. This can be the case, for example, if the value
133 // may be negative.
134 auto NumSignBits = ComputeNumSignBits(Exit, DL, 0, AC, nullptr, DT);
135 auto NumTypeBits = DL.getTypeSizeInBits(Exit->getType());
136 MaxBitWidth = NumTypeBits - NumSignBits;
137 KnownBits Bits = computeKnownBits(Exit, DL);
138 if (!Bits.isNonNegative()) {
139 // If the value is not known to be non-negative, we set IsSigned to true,
140 // meaning that we will use sext instructions instead of zext
141 // instructions to restore the original type.
142 IsSigned = true;
143 if (!Bits.isNegative())
144 // If the value is not known to be negative, we don't known what the
145 // upper bit is, and therefore, we don't know what kind of extend we
146 // will need. In this case, just increase the bit width by one bit and
147 // use sext.
148 ++MaxBitWidth;
149 }
150 }
151 if (!isPowerOf2_64(MaxBitWidth))
152 MaxBitWidth = NextPowerOf2(MaxBitWidth);
153
154 return std::make_pair(Type::getIntNTy(Exit->getContext(), MaxBitWidth),
155 IsSigned);
156}
157
158/// Collect cast instructions that can be ignored in the vectorizer's cost
159/// model, given a reduction exit value and the minimal type in which the
160/// reduction can be represented.
161static void collectCastsToIgnore(Loop *TheLoop, Instruction *Exit,
162 Type *RecurrenceType,
163 SmallPtrSetImpl<Instruction *> &Casts) {
164
165 SmallVector<Instruction *, 8> Worklist;
166 SmallPtrSet<Instruction *, 8> Visited;
167 Worklist.push_back(Exit);
168
169 while (!Worklist.empty()) {
170 Instruction *Val = Worklist.pop_back_val();
171 Visited.insert(Val);
172 if (auto *Cast = dyn_cast<CastInst>(Val))
173 if (Cast->getSrcTy() == RecurrenceType) {
174 // If the source type of a cast instruction is equal to the recurrence
175 // type, it will be eliminated, and should be ignored in the vectorizer
176 // cost model.
177 Casts.insert(Cast);
178 continue;
179 }
180
181 // Add all operands to the work list if they are loop-varying values that
182 // we haven't yet visited.
183 for (Value *O : cast<User>(Val)->operands())
184 if (auto *I = dyn_cast<Instruction>(O))
185 if (TheLoop->contains(I) && !Visited.count(I))
186 Worklist.push_back(I);
187 }
188}
189
190bool RecurrenceDescriptor::AddReductionVar(PHINode *Phi, RecurrenceKind Kind,
191 Loop *TheLoop, bool HasFunNoNaNAttr,
192 RecurrenceDescriptor &RedDes,
193 DemandedBits *DB,
194 AssumptionCache *AC,
195 DominatorTree *DT) {
196 if (Phi->getNumIncomingValues() != 2)
197 return false;
198
199 // Reduction variables are only found in the loop header block.
200 if (Phi->getParent() != TheLoop->getHeader())
201 return false;
202
203 // Obtain the reduction start value from the value that comes from the loop
204 // preheader.
205 Value *RdxStart = Phi->getIncomingValueForBlock(TheLoop->getLoopPreheader());
206
207 // ExitInstruction is the single value which is used outside the loop.
208 // We only allow for a single reduction value to be used outside the loop.
209 // This includes users of the reduction, variables (which form a cycle
210 // which ends in the phi node).
211 Instruction *ExitInstruction = nullptr;
212 // Indicates that we found a reduction operation in our scan.
213 bool FoundReduxOp = false;
214
215 // We start with the PHI node and scan for all of the users of this
216 // instruction. All users must be instructions that can be used as reduction
217 // variables (such as ADD). We must have a single out-of-block user. The cycle
218 // must include the original PHI.
219 bool FoundStartPHI = false;
220
221 // To recognize min/max patterns formed by a icmp select sequence, we store
222 // the number of instruction we saw from the recognized min/max pattern,
223 // to make sure we only see exactly the two instructions.
224 unsigned NumCmpSelectPatternInst = 0;
225 InstDesc ReduxDesc(false, nullptr);
226
227 // Data used for determining if the recurrence has been type-promoted.
228 Type *RecurrenceType = Phi->getType();
229 SmallPtrSet<Instruction *, 4> CastInsts;
230 Instruction *Start = Phi;
231 bool IsSigned = false;
232
233 SmallPtrSet<Instruction *, 8> VisitedInsts;
234 SmallVector<Instruction *, 8> Worklist;
235
236 // Return early if the recurrence kind does not match the type of Phi. If the
237 // recurrence kind is arithmetic, we attempt to look through AND operations
238 // resulting from the type promotion performed by InstCombine. Vector
239 // operations are not limited to the legal integer widths, so we may be able
240 // to evaluate the reduction in the narrower width.
241 if (RecurrenceType->isFloatingPointTy()) {
242 if (!isFloatingPointRecurrenceKind(Kind))
243 return false;
244 } else {
245 if (!isIntegerRecurrenceKind(Kind))
246 return false;
247 if (isArithmeticRecurrenceKind(Kind))
248 Start = lookThroughAnd(Phi, RecurrenceType, VisitedInsts, CastInsts);
249 }
250
251 Worklist.push_back(Start);
252 VisitedInsts.insert(Start);
253
Sanjoy Das3f5ce182019-03-12 01:31:44 +0000254 // Start with all flags set because we will intersect this with the reduction
255 // flags from all the reduction operations.
256 FastMathFlags FMF = FastMathFlags::getFast();
257
Vikram TV7e98d692018-09-12 01:59:43 +0000258 // A value in the reduction can be used:
259 // - By the reduction:
260 // - Reduction operation:
261 // - One use of reduction value (safe).
262 // - Multiple use of reduction value (not safe).
263 // - PHI:
264 // - All uses of the PHI must be the reduction (safe).
265 // - Otherwise, not safe.
266 // - By instructions outside of the loop (safe).
267 // * One value may have several outside users, but all outside
268 // uses must be of the same value.
269 // - By an instruction that is not part of the reduction (not safe).
270 // This is either:
271 // * An instruction type other than PHI or the reduction operation.
272 // * A PHI in the header other than the initial PHI.
273 while (!Worklist.empty()) {
274 Instruction *Cur = Worklist.back();
275 Worklist.pop_back();
276
277 // No Users.
278 // If the instruction has no users then this is a broken chain and can't be
279 // a reduction variable.
280 if (Cur->use_empty())
281 return false;
282
283 bool IsAPhi = isa<PHINode>(Cur);
284
285 // A header PHI use other than the original PHI.
286 if (Cur != Phi && IsAPhi && Cur->getParent() == Phi->getParent())
287 return false;
288
289 // Reductions of instructions such as Div, and Sub is only possible if the
290 // LHS is the reduction variable.
291 if (!Cur->isCommutative() && !IsAPhi && !isa<SelectInst>(Cur) &&
292 !isa<ICmpInst>(Cur) && !isa<FCmpInst>(Cur) &&
293 !VisitedInsts.count(dyn_cast<Instruction>(Cur->getOperand(0))))
294 return false;
295
296 // Any reduction instruction must be of one of the allowed kinds. We ignore
297 // the starting value (the Phi or an AND instruction if the Phi has been
298 // type-promoted).
299 if (Cur != Start) {
300 ReduxDesc = isRecurrenceInstr(Cur, Kind, ReduxDesc, HasFunNoNaNAttr);
301 if (!ReduxDesc.isRecurrence())
302 return false;
Sanjay Patel6d4ea222019-09-25 14:35:02 +0000303 // FIXME: FMF is allowed on phi, but propagation is not handled correctly.
304 if (isa<FPMathOperator>(ReduxDesc.getPatternInst()) && !IsAPhi)
Sanjoy Das3f5ce182019-03-12 01:31:44 +0000305 FMF &= ReduxDesc.getPatternInst()->getFastMathFlags();
Vikram TV7e98d692018-09-12 01:59:43 +0000306 }
307
Renato Golin135e72e2018-11-30 13:40:10 +0000308 bool IsASelect = isa<SelectInst>(Cur);
309
310 // A conditional reduction operation must only have 2 or less uses in
311 // VisitedInsts.
312 if (IsASelect && (Kind == RK_FloatAdd || Kind == RK_FloatMult) &&
313 hasMultipleUsesOf(Cur, VisitedInsts, 2))
314 return false;
315
Vikram TV7e98d692018-09-12 01:59:43 +0000316 // A reduction operation must only have one use of the reduction value.
Renato Golin135e72e2018-11-30 13:40:10 +0000317 if (!IsAPhi && !IsASelect && Kind != RK_IntegerMinMax &&
318 Kind != RK_FloatMinMax && hasMultipleUsesOf(Cur, VisitedInsts, 1))
Vikram TV7e98d692018-09-12 01:59:43 +0000319 return false;
320
321 // All inputs to a PHI node must be a reduction value.
322 if (IsAPhi && Cur != Phi && !areAllUsesIn(Cur, VisitedInsts))
323 return false;
324
325 if (Kind == RK_IntegerMinMax &&
326 (isa<ICmpInst>(Cur) || isa<SelectInst>(Cur)))
327 ++NumCmpSelectPatternInst;
328 if (Kind == RK_FloatMinMax && (isa<FCmpInst>(Cur) || isa<SelectInst>(Cur)))
329 ++NumCmpSelectPatternInst;
330
331 // Check whether we found a reduction operator.
332 FoundReduxOp |= !IsAPhi && Cur != Start;
333
334 // Process users of current instruction. Push non-PHI nodes after PHI nodes
335 // onto the stack. This way we are going to have seen all inputs to PHI
336 // nodes once we get to them.
337 SmallVector<Instruction *, 8> NonPHIs;
338 SmallVector<Instruction *, 8> PHIs;
339 for (User *U : Cur->users()) {
340 Instruction *UI = cast<Instruction>(U);
341
342 // Check if we found the exit user.
343 BasicBlock *Parent = UI->getParent();
344 if (!TheLoop->contains(Parent)) {
345 // If we already know this instruction is used externally, move on to
346 // the next user.
347 if (ExitInstruction == Cur)
348 continue;
349
350 // Exit if you find multiple values used outside or if the header phi
351 // node is being used. In this case the user uses the value of the
352 // previous iteration, in which case we would loose "VF-1" iterations of
353 // the reduction operation if we vectorize.
354 if (ExitInstruction != nullptr || Cur == Phi)
355 return false;
356
357 // The instruction used by an outside user must be the last instruction
358 // before we feed back to the reduction phi. Otherwise, we loose VF-1
359 // operations on the value.
360 if (!is_contained(Phi->operands(), Cur))
361 return false;
362
363 ExitInstruction = Cur;
364 continue;
365 }
366
367 // Process instructions only once (termination). Each reduction cycle
368 // value must only be used once, except by phi nodes and min/max
369 // reductions which are represented as a cmp followed by a select.
370 InstDesc IgnoredVal(false, nullptr);
371 if (VisitedInsts.insert(UI).second) {
372 if (isa<PHINode>(UI))
373 PHIs.push_back(UI);
374 else
375 NonPHIs.push_back(UI);
376 } else if (!isa<PHINode>(UI) &&
377 ((!isa<FCmpInst>(UI) && !isa<ICmpInst>(UI) &&
378 !isa<SelectInst>(UI)) ||
Renato Golin135e72e2018-11-30 13:40:10 +0000379 (!isConditionalRdxPattern(Kind, UI).isRecurrence() &&
380 !isMinMaxSelectCmpPattern(UI, IgnoredVal).isRecurrence())))
Vikram TV7e98d692018-09-12 01:59:43 +0000381 return false;
382
383 // Remember that we completed the cycle.
384 if (UI == Phi)
385 FoundStartPHI = true;
386 }
387 Worklist.append(PHIs.begin(), PHIs.end());
388 Worklist.append(NonPHIs.begin(), NonPHIs.end());
389 }
390
391 // This means we have seen one but not the other instruction of the
392 // pattern or more than just a select and cmp.
393 if ((Kind == RK_IntegerMinMax || Kind == RK_FloatMinMax) &&
394 NumCmpSelectPatternInst != 2)
395 return false;
396
397 if (!FoundStartPHI || !FoundReduxOp || !ExitInstruction)
398 return false;
399
400 if (Start != Phi) {
401 // If the starting value is not the same as the phi node, we speculatively
402 // looked through an 'and' instruction when evaluating a potential
403 // arithmetic reduction to determine if it may have been type-promoted.
404 //
405 // We now compute the minimal bit width that is required to represent the
406 // reduction. If this is the same width that was indicated by the 'and', we
407 // can represent the reduction in the smaller type. The 'and' instruction
408 // will be eliminated since it will essentially be a cast instruction that
409 // can be ignore in the cost model. If we compute a different type than we
410 // did when evaluating the 'and', the 'and' will not be eliminated, and we
411 // will end up with different kinds of operations in the recurrence
412 // expression (e.g., RK_IntegerAND, RK_IntegerADD). We give up if this is
413 // the case.
414 //
415 // The vectorizer relies on InstCombine to perform the actual
416 // type-shrinking. It does this by inserting instructions to truncate the
417 // exit value of the reduction to the width indicated by RecurrenceType and
418 // then extend this value back to the original width. If IsSigned is false,
419 // a 'zext' instruction will be generated; otherwise, a 'sext' will be
420 // used.
421 //
422 // TODO: We should not rely on InstCombine to rewrite the reduction in the
423 // smaller type. We should just generate a correctly typed expression
424 // to begin with.
425 Type *ComputedType;
426 std::tie(ComputedType, IsSigned) =
427 computeRecurrenceType(ExitInstruction, DB, AC, DT);
428 if (ComputedType != RecurrenceType)
429 return false;
430
431 // The recurrence expression will be represented in a narrower type. If
432 // there are any cast instructions that will be unnecessary, collect them
433 // in CastInsts. Note that the 'and' instruction was already included in
434 // this list.
435 //
436 // TODO: A better way to represent this may be to tag in some way all the
437 // instructions that are a part of the reduction. The vectorizer cost
438 // model could then apply the recurrence type to these instructions,
439 // without needing a white list of instructions to ignore.
440 collectCastsToIgnore(TheLoop, ExitInstruction, RecurrenceType, CastInsts);
441 }
442
443 // We found a reduction var if we have reached the original phi node and we
444 // only have a single instruction with out-of-loop users.
445
446 // The ExitInstruction(Instruction which is allowed to have out-of-loop users)
447 // is saved as part of the RecurrenceDescriptor.
448
449 // Save the description of this reduction variable.
450 RecurrenceDescriptor RD(
Sanjoy Das3f5ce182019-03-12 01:31:44 +0000451 RdxStart, ExitInstruction, Kind, FMF, ReduxDesc.getMinMaxKind(),
Vikram TV7e98d692018-09-12 01:59:43 +0000452 ReduxDesc.getUnsafeAlgebraInst(), RecurrenceType, IsSigned, CastInsts);
453 RedDes = RD;
454
455 return true;
456}
457
458/// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction
459/// pattern corresponding to a min(X, Y) or max(X, Y).
460RecurrenceDescriptor::InstDesc
461RecurrenceDescriptor::isMinMaxSelectCmpPattern(Instruction *I, InstDesc &Prev) {
462
463 assert((isa<ICmpInst>(I) || isa<FCmpInst>(I) || isa<SelectInst>(I)) &&
464 "Expect a select instruction");
465 Instruction *Cmp = nullptr;
466 SelectInst *Select = nullptr;
467
468 // We must handle the select(cmp()) as a single instruction. Advance to the
469 // select.
470 if ((Cmp = dyn_cast<ICmpInst>(I)) || (Cmp = dyn_cast<FCmpInst>(I))) {
471 if (!Cmp->hasOneUse() || !(Select = dyn_cast<SelectInst>(*I->user_begin())))
472 return InstDesc(false, I);
473 return InstDesc(Select, Prev.getMinMaxKind());
474 }
475
476 // Only handle single use cases for now.
477 if (!(Select = dyn_cast<SelectInst>(I)))
478 return InstDesc(false, I);
479 if (!(Cmp = dyn_cast<ICmpInst>(I->getOperand(0))) &&
480 !(Cmp = dyn_cast<FCmpInst>(I->getOperand(0))))
481 return InstDesc(false, I);
482 if (!Cmp->hasOneUse())
483 return InstDesc(false, I);
484
485 Value *CmpLeft;
486 Value *CmpRight;
487
488 // Look for a min/max pattern.
489 if (m_UMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
490 return InstDesc(Select, MRK_UIntMin);
491 else if (m_UMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
492 return InstDesc(Select, MRK_UIntMax);
493 else if (m_SMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
494 return InstDesc(Select, MRK_SIntMax);
495 else if (m_SMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
496 return InstDesc(Select, MRK_SIntMin);
497 else if (m_OrdFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
498 return InstDesc(Select, MRK_FloatMin);
499 else if (m_OrdFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
500 return InstDesc(Select, MRK_FloatMax);
501 else if (m_UnordFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
502 return InstDesc(Select, MRK_FloatMin);
503 else if (m_UnordFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
504 return InstDesc(Select, MRK_FloatMax);
505
506 return InstDesc(false, I);
507}
508
Renato Golin135e72e2018-11-30 13:40:10 +0000509/// Returns true if the select instruction has users in the compare-and-add
510/// reduction pattern below. The select instruction argument is the last one
511/// in the sequence.
512///
513/// %sum.1 = phi ...
514/// ...
515/// %cmp = fcmp pred %0, %CFP
516/// %add = fadd %0, %sum.1
517/// %sum.2 = select %cmp, %add, %sum.1
518RecurrenceDescriptor::InstDesc
519RecurrenceDescriptor::isConditionalRdxPattern(
520 RecurrenceKind Kind, Instruction *I) {
521 SelectInst *SI = dyn_cast<SelectInst>(I);
522 if (!SI)
523 return InstDesc(false, I);
524
525 CmpInst *CI = dyn_cast<CmpInst>(SI->getCondition());
526 // Only handle single use cases for now.
527 if (!CI || !CI->hasOneUse())
528 return InstDesc(false, I);
529
530 Value *TrueVal = SI->getTrueValue();
531 Value *FalseVal = SI->getFalseValue();
532 // Handle only when either of operands of select instruction is a PHI
533 // node for now.
534 if ((isa<PHINode>(*TrueVal) && isa<PHINode>(*FalseVal)) ||
535 (!isa<PHINode>(*TrueVal) && !isa<PHINode>(*FalseVal)))
536 return InstDesc(false, I);
537
538 Instruction *I1 =
539 isa<PHINode>(*TrueVal) ? dyn_cast<Instruction>(FalseVal)
540 : dyn_cast<Instruction>(TrueVal);
541 if (!I1 || !I1->isBinaryOp())
542 return InstDesc(false, I);
543
544 Value *Op1, *Op2;
Renato Golinde4b88e2018-11-30 13:54:36 +0000545 if ((m_FAdd(m_Value(Op1), m_Value(Op2)).match(I1) ||
546 m_FSub(m_Value(Op1), m_Value(Op2)).match(I1)) &&
547 I1->isFast())
Renato Golin135e72e2018-11-30 13:40:10 +0000548 return InstDesc(Kind == RK_FloatAdd, SI);
549
550 if (m_FMul(m_Value(Op1), m_Value(Op2)).match(I1) && (I1->isFast()))
551 return InstDesc(Kind == RK_FloatMult, SI);
552
553 return InstDesc(false, I);
554}
555
Vikram TV7e98d692018-09-12 01:59:43 +0000556RecurrenceDescriptor::InstDesc
557RecurrenceDescriptor::isRecurrenceInstr(Instruction *I, RecurrenceKind Kind,
558 InstDesc &Prev, bool HasFunNoNaNAttr) {
Vikram TV7e98d692018-09-12 01:59:43 +0000559 Instruction *UAI = Prev.getUnsafeAlgebraInst();
Sanjoy Das3f5ce182019-03-12 01:31:44 +0000560 if (!UAI && isa<FPMathOperator>(I) && !I->hasAllowReassoc())
Vikram TV7e98d692018-09-12 01:59:43 +0000561 UAI = I; // Found an unsafe (unvectorizable) algebra instruction.
562
563 switch (I->getOpcode()) {
564 default:
565 return InstDesc(false, I);
566 case Instruction::PHI:
567 return InstDesc(I, Prev.getMinMaxKind(), Prev.getUnsafeAlgebraInst());
568 case Instruction::Sub:
569 case Instruction::Add:
570 return InstDesc(Kind == RK_IntegerAdd, I);
571 case Instruction::Mul:
572 return InstDesc(Kind == RK_IntegerMult, I);
573 case Instruction::And:
574 return InstDesc(Kind == RK_IntegerAnd, I);
575 case Instruction::Or:
576 return InstDesc(Kind == RK_IntegerOr, I);
577 case Instruction::Xor:
578 return InstDesc(Kind == RK_IntegerXor, I);
579 case Instruction::FMul:
580 return InstDesc(Kind == RK_FloatMult, I, UAI);
581 case Instruction::FSub:
582 case Instruction::FAdd:
583 return InstDesc(Kind == RK_FloatAdd, I, UAI);
Renato Golin135e72e2018-11-30 13:40:10 +0000584 case Instruction::Select:
585 if (Kind == RK_FloatAdd || Kind == RK_FloatMult)
586 return isConditionalRdxPattern(Kind, I);
587 LLVM_FALLTHROUGH;
Vikram TV7e98d692018-09-12 01:59:43 +0000588 case Instruction::FCmp:
589 case Instruction::ICmp:
Vikram TV7e98d692018-09-12 01:59:43 +0000590 if (Kind != RK_IntegerMinMax &&
591 (!HasFunNoNaNAttr || Kind != RK_FloatMinMax))
592 return InstDesc(false, I);
593 return isMinMaxSelectCmpPattern(I, Prev);
594 }
595}
596
597bool RecurrenceDescriptor::hasMultipleUsesOf(
Renato Golin135e72e2018-11-30 13:40:10 +0000598 Instruction *I, SmallPtrSetImpl<Instruction *> &Insts,
599 unsigned MaxNumUses) {
Vikram TV7e98d692018-09-12 01:59:43 +0000600 unsigned NumUses = 0;
601 for (User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E;
602 ++Use) {
603 if (Insts.count(dyn_cast<Instruction>(*Use)))
604 ++NumUses;
Renato Golin135e72e2018-11-30 13:40:10 +0000605 if (NumUses > MaxNumUses)
Vikram TV7e98d692018-09-12 01:59:43 +0000606 return true;
607 }
608
609 return false;
610}
611bool RecurrenceDescriptor::isReductionPHI(PHINode *Phi, Loop *TheLoop,
612 RecurrenceDescriptor &RedDes,
613 DemandedBits *DB, AssumptionCache *AC,
614 DominatorTree *DT) {
615
616 BasicBlock *Header = TheLoop->getHeader();
617 Function &F = *Header->getParent();
618 bool HasFunNoNaNAttr =
619 F.getFnAttribute("no-nans-fp-math").getValueAsString() == "true";
620
621 if (AddReductionVar(Phi, RK_IntegerAdd, TheLoop, HasFunNoNaNAttr, RedDes, DB,
622 AC, DT)) {
623 LLVM_DEBUG(dbgs() << "Found an ADD reduction PHI." << *Phi << "\n");
624 return true;
625 }
626 if (AddReductionVar(Phi, RK_IntegerMult, TheLoop, HasFunNoNaNAttr, RedDes, DB,
627 AC, DT)) {
628 LLVM_DEBUG(dbgs() << "Found a MUL reduction PHI." << *Phi << "\n");
629 return true;
630 }
631 if (AddReductionVar(Phi, RK_IntegerOr, TheLoop, HasFunNoNaNAttr, RedDes, DB,
632 AC, DT)) {
633 LLVM_DEBUG(dbgs() << "Found an OR reduction PHI." << *Phi << "\n");
634 return true;
635 }
636 if (AddReductionVar(Phi, RK_IntegerAnd, TheLoop, HasFunNoNaNAttr, RedDes, DB,
637 AC, DT)) {
638 LLVM_DEBUG(dbgs() << "Found an AND reduction PHI." << *Phi << "\n");
639 return true;
640 }
641 if (AddReductionVar(Phi, RK_IntegerXor, TheLoop, HasFunNoNaNAttr, RedDes, DB,
642 AC, DT)) {
643 LLVM_DEBUG(dbgs() << "Found a XOR reduction PHI." << *Phi << "\n");
644 return true;
645 }
646 if (AddReductionVar(Phi, RK_IntegerMinMax, TheLoop, HasFunNoNaNAttr, RedDes,
647 DB, AC, DT)) {
648 LLVM_DEBUG(dbgs() << "Found a MINMAX reduction PHI." << *Phi << "\n");
649 return true;
650 }
651 if (AddReductionVar(Phi, RK_FloatMult, TheLoop, HasFunNoNaNAttr, RedDes, DB,
652 AC, DT)) {
653 LLVM_DEBUG(dbgs() << "Found an FMult reduction PHI." << *Phi << "\n");
654 return true;
655 }
656 if (AddReductionVar(Phi, RK_FloatAdd, TheLoop, HasFunNoNaNAttr, RedDes, DB,
657 AC, DT)) {
658 LLVM_DEBUG(dbgs() << "Found an FAdd reduction PHI." << *Phi << "\n");
659 return true;
660 }
661 if (AddReductionVar(Phi, RK_FloatMinMax, TheLoop, HasFunNoNaNAttr, RedDes, DB,
662 AC, DT)) {
663 LLVM_DEBUG(dbgs() << "Found an float MINMAX reduction PHI." << *Phi
664 << "\n");
665 return true;
666 }
667 // Not a reduction of known type.
668 return false;
669}
670
671bool RecurrenceDescriptor::isFirstOrderRecurrence(
672 PHINode *Phi, Loop *TheLoop,
673 DenseMap<Instruction *, Instruction *> &SinkAfter, DominatorTree *DT) {
674
675 // Ensure the phi node is in the loop header and has two incoming values.
676 if (Phi->getParent() != TheLoop->getHeader() ||
677 Phi->getNumIncomingValues() != 2)
678 return false;
679
680 // Ensure the loop has a preheader and a single latch block. The loop
681 // vectorizer will need the latch to set up the next iteration of the loop.
682 auto *Preheader = TheLoop->getLoopPreheader();
683 auto *Latch = TheLoop->getLoopLatch();
684 if (!Preheader || !Latch)
685 return false;
686
687 // Ensure the phi node's incoming blocks are the loop preheader and latch.
688 if (Phi->getBasicBlockIndex(Preheader) < 0 ||
689 Phi->getBasicBlockIndex(Latch) < 0)
690 return false;
691
692 // Get the previous value. The previous value comes from the latch edge while
693 // the initial value comes form the preheader edge.
694 auto *Previous = dyn_cast<Instruction>(Phi->getIncomingValueForBlock(Latch));
695 if (!Previous || !TheLoop->contains(Previous) || isa<PHINode>(Previous) ||
696 SinkAfter.count(Previous)) // Cannot rely on dominance due to motion.
697 return false;
698
699 // Ensure every user of the phi node is dominated by the previous value.
700 // The dominance requirement ensures the loop vectorizer will not need to
701 // vectorize the initial value prior to the first iteration of the loop.
Hans Wennborgeaff3002019-11-07 11:00:02 +0100702 // TODO: Consider extending this sinking to handle other kinds of instructions
703 // and expressions, beyond sinking a single cast past Previous.
Vikram TV7e98d692018-09-12 01:59:43 +0000704 if (Phi->hasOneUse()) {
Hans Wennborgeaff3002019-11-07 11:00:02 +0100705 auto *I = Phi->user_back();
706 if (I->isCast() && (I->getParent() == Phi->getParent()) && I->hasOneUse() &&
707 DT->dominates(Previous, I->user_back())) {
708 if (!DT->dominates(Previous, I)) // Otherwise we're good w/o sinking.
709 SinkAfter[I] = Previous;
Vikram TV7e98d692018-09-12 01:59:43 +0000710 return true;
711 }
712 }
713
Hans Wennborgeaff3002019-11-07 11:00:02 +0100714 for (User *U : Phi->users())
715 if (auto *I = dyn_cast<Instruction>(U)) {
716 if (!DT->dominates(Previous, I))
717 return false;
718 }
719
720 return true;
Vikram TV7e98d692018-09-12 01:59:43 +0000721}
722
723/// This function returns the identity element (or neutral element) for
724/// the operation K.
725Constant *RecurrenceDescriptor::getRecurrenceIdentity(RecurrenceKind K,
726 Type *Tp) {
727 switch (K) {
728 case RK_IntegerXor:
729 case RK_IntegerAdd:
730 case RK_IntegerOr:
731 // Adding, Xoring, Oring zero to a number does not change it.
732 return ConstantInt::get(Tp, 0);
733 case RK_IntegerMult:
734 // Multiplying a number by 1 does not change it.
735 return ConstantInt::get(Tp, 1);
736 case RK_IntegerAnd:
737 // AND-ing a number with an all-1 value does not change it.
738 return ConstantInt::get(Tp, -1, true);
739 case RK_FloatMult:
740 // Multiplying a number by 1 does not change it.
741 return ConstantFP::get(Tp, 1.0L);
742 case RK_FloatAdd:
743 // Adding zero to a number does not change it.
744 return ConstantFP::get(Tp, 0.0L);
745 default:
746 llvm_unreachable("Unknown recurrence kind");
747 }
748}
749
750/// This function translates the recurrence kind to an LLVM binary operator.
751unsigned RecurrenceDescriptor::getRecurrenceBinOp(RecurrenceKind Kind) {
752 switch (Kind) {
753 case RK_IntegerAdd:
754 return Instruction::Add;
755 case RK_IntegerMult:
756 return Instruction::Mul;
757 case RK_IntegerOr:
758 return Instruction::Or;
759 case RK_IntegerAnd:
760 return Instruction::And;
761 case RK_IntegerXor:
762 return Instruction::Xor;
763 case RK_FloatMult:
764 return Instruction::FMul;
765 case RK_FloatAdd:
766 return Instruction::FAdd;
767 case RK_IntegerMinMax:
768 return Instruction::ICmp;
769 case RK_FloatMinMax:
770 return Instruction::FCmp;
771 default:
772 llvm_unreachable("Unknown recurrence operation");
773 }
774}
775
776InductionDescriptor::InductionDescriptor(Value *Start, InductionKind K,
777 const SCEV *Step, BinaryOperator *BOp,
778 SmallVectorImpl<Instruction *> *Casts)
779 : StartValue(Start), IK(K), Step(Step), InductionBinOp(BOp) {
780 assert(IK != IK_NoInduction && "Not an induction");
781
782 // Start value type should match the induction kind and the value
783 // itself should not be null.
784 assert(StartValue && "StartValue is null");
785 assert((IK != IK_PtrInduction || StartValue->getType()->isPointerTy()) &&
786 "StartValue is not a pointer for pointer induction");
787 assert((IK != IK_IntInduction || StartValue->getType()->isIntegerTy()) &&
788 "StartValue is not an integer for integer induction");
789
790 // Check the Step Value. It should be non-zero integer value.
791 assert((!getConstIntStepValue() || !getConstIntStepValue()->isZero()) &&
792 "Step value is zero");
793
794 assert((IK != IK_PtrInduction || getConstIntStepValue()) &&
795 "Step value should be constant for pointer induction");
796 assert((IK == IK_FpInduction || Step->getType()->isIntegerTy()) &&
797 "StepValue is not an integer");
798
799 assert((IK != IK_FpInduction || Step->getType()->isFloatingPointTy()) &&
800 "StepValue is not FP for FpInduction");
801 assert((IK != IK_FpInduction ||
802 (InductionBinOp &&
803 (InductionBinOp->getOpcode() == Instruction::FAdd ||
804 InductionBinOp->getOpcode() == Instruction::FSub))) &&
805 "Binary opcode should be specified for FP induction");
806
807 if (Casts) {
808 for (auto &Inst : *Casts) {
809 RedundantCasts.push_back(Inst);
810 }
811 }
812}
813
814int InductionDescriptor::getConsecutiveDirection() const {
815 ConstantInt *ConstStep = getConstIntStepValue();
816 if (ConstStep && (ConstStep->isOne() || ConstStep->isMinusOne()))
817 return ConstStep->getSExtValue();
818 return 0;
819}
820
821ConstantInt *InductionDescriptor::getConstIntStepValue() const {
822 if (isa<SCEVConstant>(Step))
823 return dyn_cast<ConstantInt>(cast<SCEVConstant>(Step)->getValue());
824 return nullptr;
825}
826
827bool InductionDescriptor::isFPInductionPHI(PHINode *Phi, const Loop *TheLoop,
828 ScalarEvolution *SE,
829 InductionDescriptor &D) {
830
831 // Here we only handle FP induction variables.
832 assert(Phi->getType()->isFloatingPointTy() && "Unexpected Phi type");
833
834 if (TheLoop->getHeader() != Phi->getParent())
835 return false;
836
837 // The loop may have multiple entrances or multiple exits; we can analyze
838 // this phi if it has a unique entry value and a unique backedge value.
839 if (Phi->getNumIncomingValues() != 2)
840 return false;
841 Value *BEValue = nullptr, *StartValue = nullptr;
842 if (TheLoop->contains(Phi->getIncomingBlock(0))) {
843 BEValue = Phi->getIncomingValue(0);
844 StartValue = Phi->getIncomingValue(1);
845 } else {
846 assert(TheLoop->contains(Phi->getIncomingBlock(1)) &&
847 "Unexpected Phi node in the loop");
848 BEValue = Phi->getIncomingValue(1);
849 StartValue = Phi->getIncomingValue(0);
850 }
851
852 BinaryOperator *BOp = dyn_cast<BinaryOperator>(BEValue);
853 if (!BOp)
854 return false;
855
856 Value *Addend = nullptr;
857 if (BOp->getOpcode() == Instruction::FAdd) {
858 if (BOp->getOperand(0) == Phi)
859 Addend = BOp->getOperand(1);
860 else if (BOp->getOperand(1) == Phi)
861 Addend = BOp->getOperand(0);
862 } else if (BOp->getOpcode() == Instruction::FSub)
863 if (BOp->getOperand(0) == Phi)
864 Addend = BOp->getOperand(1);
865
866 if (!Addend)
867 return false;
868
869 // The addend should be loop invariant
870 if (auto *I = dyn_cast<Instruction>(Addend))
871 if (TheLoop->contains(I))
872 return false;
873
874 // FP Step has unknown SCEV
875 const SCEV *Step = SE->getUnknown(Addend);
876 D = InductionDescriptor(StartValue, IK_FpInduction, Step, BOp);
877 return true;
878}
879
880/// This function is called when we suspect that the update-chain of a phi node
881/// (whose symbolic SCEV expression sin \p PhiScev) contains redundant casts,
882/// that can be ignored. (This can happen when the PSCEV rewriter adds a runtime
883/// predicate P under which the SCEV expression for the phi can be the
884/// AddRecurrence \p AR; See createAddRecFromPHIWithCast). We want to find the
885/// cast instructions that are involved in the update-chain of this induction.
886/// A caller that adds the required runtime predicate can be free to drop these
887/// cast instructions, and compute the phi using \p AR (instead of some scev
888/// expression with casts).
889///
890/// For example, without a predicate the scev expression can take the following
891/// form:
892/// (Ext ix (Trunc iy ( Start + i*Step ) to ix) to iy)
893///
894/// It corresponds to the following IR sequence:
895/// %for.body:
896/// %x = phi i64 [ 0, %ph ], [ %add, %for.body ]
897/// %casted_phi = "ExtTrunc i64 %x"
898/// %add = add i64 %casted_phi, %step
899///
900/// where %x is given in \p PN,
901/// PSE.getSCEV(%x) is equal to PSE.getSCEV(%casted_phi) under a predicate,
902/// and the IR sequence that "ExtTrunc i64 %x" represents can take one of
903/// several forms, for example, such as:
904/// ExtTrunc1: %casted_phi = and %x, 2^n-1
905/// or:
906/// ExtTrunc2: %t = shl %x, m
907/// %casted_phi = ashr %t, m
908///
909/// If we are able to find such sequence, we return the instructions
910/// we found, namely %casted_phi and the instructions on its use-def chain up
911/// to the phi (not including the phi).
912static bool getCastsForInductionPHI(PredicatedScalarEvolution &PSE,
913 const SCEVUnknown *PhiScev,
914 const SCEVAddRecExpr *AR,
915 SmallVectorImpl<Instruction *> &CastInsts) {
916
917 assert(CastInsts.empty() && "CastInsts is expected to be empty.");
918 auto *PN = cast<PHINode>(PhiScev->getValue());
919 assert(PSE.getSCEV(PN) == AR && "Unexpected phi node SCEV expression");
920 const Loop *L = AR->getLoop();
921
922 // Find any cast instructions that participate in the def-use chain of
923 // PhiScev in the loop.
924 // FORNOW/TODO: We currently expect the def-use chain to include only
925 // two-operand instructions, where one of the operands is an invariant.
926 // createAddRecFromPHIWithCasts() currently does not support anything more
927 // involved than that, so we keep the search simple. This can be
928 // extended/generalized as needed.
929
930 auto getDef = [&](const Value *Val) -> Value * {
931 const BinaryOperator *BinOp = dyn_cast<BinaryOperator>(Val);
932 if (!BinOp)
933 return nullptr;
934 Value *Op0 = BinOp->getOperand(0);
935 Value *Op1 = BinOp->getOperand(1);
936 Value *Def = nullptr;
937 if (L->isLoopInvariant(Op0))
938 Def = Op1;
939 else if (L->isLoopInvariant(Op1))
940 Def = Op0;
941 return Def;
942 };
943
944 // Look for the instruction that defines the induction via the
945 // loop backedge.
946 BasicBlock *Latch = L->getLoopLatch();
947 if (!Latch)
948 return false;
949 Value *Val = PN->getIncomingValueForBlock(Latch);
950 if (!Val)
951 return false;
952
953 // Follow the def-use chain until the induction phi is reached.
954 // If on the way we encounter a Value that has the same SCEV Expr as the
955 // phi node, we can consider the instructions we visit from that point
956 // as part of the cast-sequence that can be ignored.
957 bool InCastSequence = false;
958 auto *Inst = dyn_cast<Instruction>(Val);
959 while (Val != PN) {
960 // If we encountered a phi node other than PN, or if we left the loop,
961 // we bail out.
962 if (!Inst || !L->contains(Inst)) {
963 return false;
964 }
965 auto *AddRec = dyn_cast<SCEVAddRecExpr>(PSE.getSCEV(Val));
966 if (AddRec && PSE.areAddRecsEqualWithPreds(AddRec, AR))
967 InCastSequence = true;
968 if (InCastSequence) {
969 // Only the last instruction in the cast sequence is expected to have
970 // uses outside the induction def-use chain.
971 if (!CastInsts.empty())
972 if (!Inst->hasOneUse())
973 return false;
974 CastInsts.push_back(Inst);
975 }
976 Val = getDef(Val);
977 if (!Val)
978 return false;
979 Inst = dyn_cast<Instruction>(Val);
980 }
981
982 return InCastSequence;
983}
984
985bool InductionDescriptor::isInductionPHI(PHINode *Phi, const Loop *TheLoop,
986 PredicatedScalarEvolution &PSE,
987 InductionDescriptor &D, bool Assume) {
988 Type *PhiTy = Phi->getType();
989
990 // Handle integer and pointer inductions variables.
991 // Now we handle also FP induction but not trying to make a
992 // recurrent expression from the PHI node in-place.
993
994 if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy() && !PhiTy->isFloatTy() &&
995 !PhiTy->isDoubleTy() && !PhiTy->isHalfTy())
996 return false;
997
998 if (PhiTy->isFloatingPointTy())
999 return isFPInductionPHI(Phi, TheLoop, PSE.getSE(), D);
1000
1001 const SCEV *PhiScev = PSE.getSCEV(Phi);
1002 const auto *AR = dyn_cast<SCEVAddRecExpr>(PhiScev);
1003
1004 // We need this expression to be an AddRecExpr.
1005 if (Assume && !AR)
1006 AR = PSE.getAsAddRec(Phi);
1007
1008 if (!AR) {
1009 LLVM_DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n");
1010 return false;
1011 }
1012
1013 // Record any Cast instructions that participate in the induction update
1014 const auto *SymbolicPhi = dyn_cast<SCEVUnknown>(PhiScev);
1015 // If we started from an UnknownSCEV, and managed to build an addRecurrence
1016 // only after enabling Assume with PSCEV, this means we may have encountered
1017 // cast instructions that required adding a runtime check in order to
Hiroshi Inoue02a2bb22019-02-05 08:30:48 +00001018 // guarantee the correctness of the AddRecurrence respresentation of the
Vikram TV7e98d692018-09-12 01:59:43 +00001019 // induction.
1020 if (PhiScev != AR && SymbolicPhi) {
1021 SmallVector<Instruction *, 2> Casts;
1022 if (getCastsForInductionPHI(PSE, SymbolicPhi, AR, Casts))
1023 return isInductionPHI(Phi, TheLoop, PSE.getSE(), D, AR, &Casts);
1024 }
1025
1026 return isInductionPHI(Phi, TheLoop, PSE.getSE(), D, AR);
1027}
1028
1029bool InductionDescriptor::isInductionPHI(
1030 PHINode *Phi, const Loop *TheLoop, ScalarEvolution *SE,
1031 InductionDescriptor &D, const SCEV *Expr,
1032 SmallVectorImpl<Instruction *> *CastsToIgnore) {
1033 Type *PhiTy = Phi->getType();
1034 // We only handle integer and pointer inductions variables.
1035 if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy())
1036 return false;
1037
1038 // Check that the PHI is consecutive.
1039 const SCEV *PhiScev = Expr ? Expr : SE->getSCEV(Phi);
1040 const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev);
1041
1042 if (!AR) {
1043 LLVM_DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n");
1044 return false;
1045 }
1046
1047 if (AR->getLoop() != TheLoop) {
1048 // FIXME: We should treat this as a uniform. Unfortunately, we
1049 // don't currently know how to handled uniform PHIs.
1050 LLVM_DEBUG(
1051 dbgs() << "LV: PHI is a recurrence with respect to an outer loop.\n");
1052 return false;
1053 }
1054
1055 Value *StartValue =
1056 Phi->getIncomingValueForBlock(AR->getLoop()->getLoopPreheader());
Kit Barton37b79222019-05-14 13:26:36 +00001057
1058 BasicBlock *Latch = AR->getLoop()->getLoopLatch();
1059 if (!Latch)
1060 return false;
1061 BinaryOperator *BOp =
1062 dyn_cast<BinaryOperator>(Phi->getIncomingValueForBlock(Latch));
1063
Vikram TV7e98d692018-09-12 01:59:43 +00001064 const SCEV *Step = AR->getStepRecurrence(*SE);
1065 // Calculate the pointer stride and check if it is consecutive.
1066 // The stride may be a constant or a loop invariant integer value.
1067 const SCEVConstant *ConstStep = dyn_cast<SCEVConstant>(Step);
1068 if (!ConstStep && !SE->isLoopInvariant(Step, TheLoop))
1069 return false;
1070
1071 if (PhiTy->isIntegerTy()) {
Kit Barton37b79222019-05-14 13:26:36 +00001072 D = InductionDescriptor(StartValue, IK_IntInduction, Step, BOp,
Vikram TV7e98d692018-09-12 01:59:43 +00001073 CastsToIgnore);
1074 return true;
1075 }
1076
1077 assert(PhiTy->isPointerTy() && "The PHI must be a pointer");
1078 // Pointer induction should be a constant.
1079 if (!ConstStep)
1080 return false;
1081
1082 ConstantInt *CV = ConstStep->getValue();
1083 Type *PointerElementType = PhiTy->getPointerElementType();
1084 // The pointer stride cannot be determined if the pointer element type is not
1085 // sized.
1086 if (!PointerElementType->isSized())
1087 return false;
1088
1089 const DataLayout &DL = Phi->getModule()->getDataLayout();
1090 int64_t Size = static_cast<int64_t>(DL.getTypeAllocSize(PointerElementType));
1091 if (!Size)
1092 return false;
1093
1094 int64_t CVSize = CV->getSExtValue();
1095 if (CVSize % Size)
1096 return false;
1097 auto *StepValue =
1098 SE->getConstant(CV->getType(), CVSize / Size, true /* signed */);
Kit Barton37b79222019-05-14 13:26:36 +00001099 D = InductionDescriptor(StartValue, IK_PtrInduction, StepValue, BOp);
Vikram TV7e98d692018-09-12 01:59:43 +00001100 return true;
1101}