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Sebastian Popad434992012-10-11 07:32:34 +00001//===-- DependenceAnalysis.cpp - DA Implementation --------------*- C++ -*-===//
2//
3// The LLVM Compiler Infrastructure
4//
5// This file is distributed under the University of Illinois Open Source
6// License. See LICENSE.TXT for details.
7//
8//===----------------------------------------------------------------------===//
9//
10// DependenceAnalysis is an LLVM pass that analyses dependences between memory
11// accesses. Currently, it is an (incomplete) implementation of the approach
12// described in
13//
14// Practical Dependence Testing
15// Goff, Kennedy, Tseng
16// PLDI 1991
17//
18// There's a single entry point that analyzes the dependence between a pair
19// of memory references in a function, returning either NULL, for no dependence,
20// or a more-or-less detailed description of the dependence between them.
21//
22// Currently, the implementation cannot propagate constraints between
23// coupled RDIV subscripts and lacks a multi-subscript MIV test.
24// Both of these are conservative weaknesses;
25// that is, not a source of correctness problems.
26//
27// The implementation depends on the GEP instruction to
28// differentiate subscripts. Since Clang linearizes subscripts
29// for most arrays, we give up some precision (though the existing MIV tests
30// will help). We trust that the GEP instruction will eventually be extended.
31// In the meantime, we should explore Maslov's ideas about delinearization.
32//
33// We should pay some careful attention to the possibility of integer overflow
34// in the implementation of the various tests. This could happen with Add,
35// Subtract, or Multiply, with both APInt's and SCEV's.
36//
37// Some non-linear subscript pairs can be handled by the GCD test
38// (and perhaps other tests).
39// Should explore how often these things occur.
40//
41// Finally, it seems like certain test cases expose weaknesses in the SCEV
42// simplification, especially in the handling of sign and zero extensions.
43// It could be useful to spend time exploring these.
44//
45// Please note that this is work in progress and the interface is subject to
46// change.
47//
48//===----------------------------------------------------------------------===//
49// //
50// In memory of Ken Kennedy, 1945 - 2007 //
51// //
52//===----------------------------------------------------------------------===//
53
54#define DEBUG_TYPE "da"
55
56#include "llvm/Analysis/DependenceAnalysis.h"
57#include "llvm/ADT/Statistic.h"
Sebastian Popad434992012-10-11 07:32:34 +000058#include "llvm/Operator.h"
Benjamin Kramer8e4e0072012-10-25 16:15:22 +000059#include "llvm/Analysis/AliasAnalysis.h"
60#include "llvm/Analysis/LoopInfo.h"
Sebastian Popad434992012-10-11 07:32:34 +000061#include "llvm/Analysis/ValueTracking.h"
Benjamin Kramer8e4e0072012-10-25 16:15:22 +000062#include "llvm/Analysis/ScalarEvolution.h"
63#include "llvm/Analysis/ScalarEvolutionExpressions.h"
Sebastian Popad434992012-10-11 07:32:34 +000064#include "llvm/Support/Debug.h"
65#include "llvm/Support/ErrorHandling.h"
66#include "llvm/Support/InstIterator.h"
Benjamin Kramer8e4e0072012-10-25 16:15:22 +000067#include "llvm/Support/raw_ostream.h"
Sebastian Popad434992012-10-11 07:32:34 +000068
69using namespace llvm;
70
71//===----------------------------------------------------------------------===//
72// statistics
73
74STATISTIC(TotalArrayPairs, "Array pairs tested");
75STATISTIC(SeparableSubscriptPairs, "Separable subscript pairs");
76STATISTIC(CoupledSubscriptPairs, "Coupled subscript pairs");
77STATISTIC(NonlinearSubscriptPairs, "Nonlinear subscript pairs");
78STATISTIC(ZIVapplications, "ZIV applications");
79STATISTIC(ZIVindependence, "ZIV independence");
80STATISTIC(StrongSIVapplications, "Strong SIV applications");
81STATISTIC(StrongSIVsuccesses, "Strong SIV successes");
82STATISTIC(StrongSIVindependence, "Strong SIV independence");
83STATISTIC(WeakCrossingSIVapplications, "Weak-Crossing SIV applications");
84STATISTIC(WeakCrossingSIVsuccesses, "Weak-Crossing SIV successes");
85STATISTIC(WeakCrossingSIVindependence, "Weak-Crossing SIV independence");
86STATISTIC(ExactSIVapplications, "Exact SIV applications");
87STATISTIC(ExactSIVsuccesses, "Exact SIV successes");
88STATISTIC(ExactSIVindependence, "Exact SIV independence");
89STATISTIC(WeakZeroSIVapplications, "Weak-Zero SIV applications");
90STATISTIC(WeakZeroSIVsuccesses, "Weak-Zero SIV successes");
91STATISTIC(WeakZeroSIVindependence, "Weak-Zero SIV independence");
92STATISTIC(ExactRDIVapplications, "Exact RDIV applications");
93STATISTIC(ExactRDIVindependence, "Exact RDIV independence");
94STATISTIC(SymbolicRDIVapplications, "Symbolic RDIV applications");
95STATISTIC(SymbolicRDIVindependence, "Symbolic RDIV independence");
96STATISTIC(DeltaApplications, "Delta applications");
97STATISTIC(DeltaSuccesses, "Delta successes");
98STATISTIC(DeltaIndependence, "Delta independence");
99STATISTIC(DeltaPropagations, "Delta propagations");
100STATISTIC(GCDapplications, "GCD applications");
101STATISTIC(GCDsuccesses, "GCD successes");
102STATISTIC(GCDindependence, "GCD independence");
103STATISTIC(BanerjeeApplications, "Banerjee applications");
104STATISTIC(BanerjeeIndependence, "Banerjee independence");
105STATISTIC(BanerjeeSuccesses, "Banerjee successes");
106
107//===----------------------------------------------------------------------===//
108// basics
109
110INITIALIZE_PASS_BEGIN(DependenceAnalysis, "da",
111 "Dependence Analysis", true, true)
112INITIALIZE_PASS_DEPENDENCY(LoopInfo)
113INITIALIZE_PASS_DEPENDENCY(ScalarEvolution)
114INITIALIZE_AG_DEPENDENCY(AliasAnalysis)
115INITIALIZE_PASS_END(DependenceAnalysis, "da",
116 "Dependence Analysis", true, true)
117
118char DependenceAnalysis::ID = 0;
119
120
121FunctionPass *llvm::createDependenceAnalysisPass() {
122 return new DependenceAnalysis();
123}
124
125
126bool DependenceAnalysis::runOnFunction(Function &F) {
127 this->F = &F;
128 AA = &getAnalysis<AliasAnalysis>();
129 SE = &getAnalysis<ScalarEvolution>();
130 LI = &getAnalysis<LoopInfo>();
131 return false;
132}
133
134
135void DependenceAnalysis::releaseMemory() {
136}
137
138
139void DependenceAnalysis::getAnalysisUsage(AnalysisUsage &AU) const {
140 AU.setPreservesAll();
141 AU.addRequiredTransitive<AliasAnalysis>();
142 AU.addRequiredTransitive<ScalarEvolution>();
143 AU.addRequiredTransitive<LoopInfo>();
144}
145
146
147// Used to test the dependence analyzer.
148// Looks through the function, noting the first store instruction
149// and the first load instruction
150// (which always follows the first load in our tests).
151// Calls depends() and prints out the result.
152// Ignores all other instructions.
153static
154void dumpExampleDependence(raw_ostream &OS, Function *F,
155 DependenceAnalysis *DA) {
156 for (inst_iterator SrcI = inst_begin(F), SrcE = inst_end(F);
157 SrcI != SrcE; ++SrcI) {
158 if (const StoreInst *Src = dyn_cast<StoreInst>(&*SrcI)) {
159 for (inst_iterator DstI = SrcI, DstE = inst_end(F);
160 DstI != DstE; ++DstI) {
161 if (const LoadInst *Dst = dyn_cast<LoadInst>(&*DstI)) {
162 OS << "da analyze - ";
163 if (Dependence *D = DA->depends(Src, Dst, true)) {
164 D->dump(OS);
165 for (unsigned Level = 1; Level <= D->getLevels(); Level++) {
166 if (D->isSplitable(Level)) {
167 OS << "da analyze - split level = " << Level;
168 OS << ", iteration = " << *DA->getSplitIteration(D, Level);
169 OS << "!\n";
170 }
171 }
172 delete D;
173 }
174 else
175 OS << "none!\n";
176 return;
177 }
178 }
179 }
180 }
181}
182
183
184void DependenceAnalysis::print(raw_ostream &OS, const Module*) const {
185 dumpExampleDependence(OS, F, const_cast<DependenceAnalysis *>(this));
186}
187
188//===----------------------------------------------------------------------===//
189// Dependence methods
190
191// Returns true if this is an input dependence.
192bool Dependence::isInput() const {
193 return Src->mayReadFromMemory() && Dst->mayReadFromMemory();
194}
195
196
197// Returns true if this is an output dependence.
198bool Dependence::isOutput() const {
199 return Src->mayWriteToMemory() && Dst->mayWriteToMemory();
200}
201
202
203// Returns true if this is an flow (aka true) dependence.
204bool Dependence::isFlow() const {
205 return Src->mayWriteToMemory() && Dst->mayReadFromMemory();
206}
207
208
209// Returns true if this is an anti dependence.
210bool Dependence::isAnti() const {
211 return Src->mayReadFromMemory() && Dst->mayWriteToMemory();
212}
213
214
215// Returns true if a particular level is scalar; that is,
216// if no subscript in the source or destination mention the induction
217// variable associated with the loop at this level.
218// Leave this out of line, so it will serve as a virtual method anchor
219bool Dependence::isScalar(unsigned level) const {
220 return false;
221}
222
223
224//===----------------------------------------------------------------------===//
225// FullDependence methods
226
227FullDependence::FullDependence(const Instruction *Source,
228 const Instruction *Destination,
229 bool PossiblyLoopIndependent,
230 unsigned CommonLevels) :
231 Dependence(Source, Destination),
232 Levels(CommonLevels),
233 LoopIndependent(PossiblyLoopIndependent) {
234 Consistent = true;
235 DV = CommonLevels ? new DVEntry[CommonLevels] : NULL;
236}
237
238// The rest are simple getters that hide the implementation.
239
240// getDirection - Returns the direction associated with a particular level.
241unsigned FullDependence::getDirection(unsigned Level) const {
242 assert(0 < Level && Level <= Levels && "Level out of range");
243 return DV[Level - 1].Direction;
244}
245
246
247// Returns the distance (or NULL) associated with a particular level.
248const SCEV *FullDependence::getDistance(unsigned Level) const {
249 assert(0 < Level && Level <= Levels && "Level out of range");
250 return DV[Level - 1].Distance;
251}
252
253
254// Returns true if a particular level is scalar; that is,
255// if no subscript in the source or destination mention the induction
256// variable associated with the loop at this level.
257bool FullDependence::isScalar(unsigned Level) const {
258 assert(0 < Level && Level <= Levels && "Level out of range");
259 return DV[Level - 1].Scalar;
260}
261
262
263// Returns true if peeling the first iteration from this loop
264// will break this dependence.
265bool FullDependence::isPeelFirst(unsigned Level) const {
266 assert(0 < Level && Level <= Levels && "Level out of range");
267 return DV[Level - 1].PeelFirst;
268}
269
270
271// Returns true if peeling the last iteration from this loop
272// will break this dependence.
273bool FullDependence::isPeelLast(unsigned Level) const {
274 assert(0 < Level && Level <= Levels && "Level out of range");
275 return DV[Level - 1].PeelLast;
276}
277
278
279// Returns true if splitting this loop will break the dependence.
280bool FullDependence::isSplitable(unsigned Level) const {
281 assert(0 < Level && Level <= Levels && "Level out of range");
282 return DV[Level - 1].Splitable;
283}
284
285
286//===----------------------------------------------------------------------===//
287// DependenceAnalysis::Constraint methods
288
289// If constraint is a point <X, Y>, returns X.
290// Otherwise assert.
291const SCEV *DependenceAnalysis::Constraint::getX() const {
292 assert(Kind == Point && "Kind should be Point");
293 return A;
294}
295
296
297// If constraint is a point <X, Y>, returns Y.
298// Otherwise assert.
299const SCEV *DependenceAnalysis::Constraint::getY() const {
300 assert(Kind == Point && "Kind should be Point");
301 return B;
302}
303
304
305// If constraint is a line AX + BY = C, returns A.
306// Otherwise assert.
307const SCEV *DependenceAnalysis::Constraint::getA() const {
308 assert((Kind == Line || Kind == Distance) &&
309 "Kind should be Line (or Distance)");
310 return A;
311}
312
313
314// If constraint is a line AX + BY = C, returns B.
315// Otherwise assert.
316const SCEV *DependenceAnalysis::Constraint::getB() const {
317 assert((Kind == Line || Kind == Distance) &&
318 "Kind should be Line (or Distance)");
319 return B;
320}
321
322
323// If constraint is a line AX + BY = C, returns C.
324// Otherwise assert.
325const SCEV *DependenceAnalysis::Constraint::getC() const {
326 assert((Kind == Line || Kind == Distance) &&
327 "Kind should be Line (or Distance)");
328 return C;
329}
330
331
332// If constraint is a distance, returns D.
333// Otherwise assert.
334const SCEV *DependenceAnalysis::Constraint::getD() const {
335 assert(Kind == Distance && "Kind should be Distance");
336 return SE->getNegativeSCEV(C);
337}
338
339
340// Returns the loop associated with this constraint.
341const Loop *DependenceAnalysis::Constraint::getAssociatedLoop() const {
342 assert((Kind == Distance || Kind == Line || Kind == Point) &&
343 "Kind should be Distance, Line, or Point");
344 return AssociatedLoop;
345}
346
347
348void DependenceAnalysis::Constraint::setPoint(const SCEV *X,
349 const SCEV *Y,
350 const Loop *CurLoop) {
351 Kind = Point;
352 A = X;
353 B = Y;
354 AssociatedLoop = CurLoop;
355}
356
357
358void DependenceAnalysis::Constraint::setLine(const SCEV *AA,
359 const SCEV *BB,
360 const SCEV *CC,
361 const Loop *CurLoop) {
362 Kind = Line;
363 A = AA;
364 B = BB;
365 C = CC;
366 AssociatedLoop = CurLoop;
367}
368
369
370void DependenceAnalysis::Constraint::setDistance(const SCEV *D,
371 const Loop *CurLoop) {
372 Kind = Distance;
373 A = SE->getConstant(D->getType(), 1);
374 B = SE->getNegativeSCEV(A);
375 C = SE->getNegativeSCEV(D);
376 AssociatedLoop = CurLoop;
377}
378
379
380void DependenceAnalysis::Constraint::setEmpty() {
381 Kind = Empty;
382}
383
384
385void DependenceAnalysis::Constraint::setAny(ScalarEvolution *NewSE) {
386 SE = NewSE;
387 Kind = Any;
388}
389
390
391// For debugging purposes. Dumps the constraint out to OS.
392void DependenceAnalysis::Constraint::dump(raw_ostream &OS) const {
393 if (isEmpty())
394 OS << " Empty\n";
395 else if (isAny())
396 OS << " Any\n";
397 else if (isPoint())
398 OS << " Point is <" << *getX() << ", " << *getY() << ">\n";
399 else if (isDistance())
400 OS << " Distance is " << *getD() <<
401 " (" << *getA() << "*X + " << *getB() << "*Y = " << *getC() << ")\n";
402 else if (isLine())
403 OS << " Line is " << *getA() << "*X + " <<
404 *getB() << "*Y = " << *getC() << "\n";
405 else
406 llvm_unreachable("unknown constraint type in Constraint::dump");
407}
408
409
410// Updates X with the intersection
411// of the Constraints X and Y. Returns true if X has changed.
412// Corresponds to Figure 4 from the paper
413//
414// Practical Dependence Testing
415// Goff, Kennedy, Tseng
416// PLDI 1991
417bool DependenceAnalysis::intersectConstraints(Constraint *X,
418 const Constraint *Y) {
419 ++DeltaApplications;
420 DEBUG(dbgs() << "\tintersect constraints\n");
421 DEBUG(dbgs() << "\t X ="; X->dump(dbgs()));
422 DEBUG(dbgs() << "\t Y ="; Y->dump(dbgs()));
423 assert(!Y->isPoint() && "Y must not be a Point");
424 if (X->isAny()) {
425 if (Y->isAny())
426 return false;
427 *X = *Y;
428 return true;
429 }
430 if (X->isEmpty())
431 return false;
432 if (Y->isEmpty()) {
433 X->setEmpty();
434 return true;
435 }
436
437 if (X->isDistance() && Y->isDistance()) {
438 DEBUG(dbgs() << "\t intersect 2 distances\n");
439 if (isKnownPredicate(CmpInst::ICMP_EQ, X->getD(), Y->getD()))
440 return false;
441 if (isKnownPredicate(CmpInst::ICMP_NE, X->getD(), Y->getD())) {
442 X->setEmpty();
443 ++DeltaSuccesses;
444 return true;
445 }
446 // Hmmm, interesting situation.
447 // I guess if either is constant, keep it and ignore the other.
448 if (isa<SCEVConstant>(Y->getD())) {
449 *X = *Y;
450 return true;
451 }
452 return false;
453 }
454
455 // At this point, the pseudo-code in Figure 4 of the paper
456 // checks if (X->isPoint() && Y->isPoint()).
457 // This case can't occur in our implementation,
458 // since a Point can only arise as the result of intersecting
459 // two Line constraints, and the right-hand value, Y, is never
460 // the result of an intersection.
461 assert(!(X->isPoint() && Y->isPoint()) &&
462 "We shouldn't ever see X->isPoint() && Y->isPoint()");
463
464 if (X->isLine() && Y->isLine()) {
465 DEBUG(dbgs() << "\t intersect 2 lines\n");
466 const SCEV *Prod1 = SE->getMulExpr(X->getA(), Y->getB());
467 const SCEV *Prod2 = SE->getMulExpr(X->getB(), Y->getA());
468 if (isKnownPredicate(CmpInst::ICMP_EQ, Prod1, Prod2)) {
469 // slopes are equal, so lines are parallel
470 DEBUG(dbgs() << "\t\tsame slope\n");
471 Prod1 = SE->getMulExpr(X->getC(), Y->getB());
472 Prod2 = SE->getMulExpr(X->getB(), Y->getC());
473 if (isKnownPredicate(CmpInst::ICMP_EQ, Prod1, Prod2))
474 return false;
475 if (isKnownPredicate(CmpInst::ICMP_NE, Prod1, Prod2)) {
476 X->setEmpty();
477 ++DeltaSuccesses;
478 return true;
479 }
480 return false;
481 }
482 if (isKnownPredicate(CmpInst::ICMP_NE, Prod1, Prod2)) {
483 // slopes differ, so lines intersect
484 DEBUG(dbgs() << "\t\tdifferent slopes\n");
485 const SCEV *C1B2 = SE->getMulExpr(X->getC(), Y->getB());
486 const SCEV *C1A2 = SE->getMulExpr(X->getC(), Y->getA());
487 const SCEV *C2B1 = SE->getMulExpr(Y->getC(), X->getB());
488 const SCEV *C2A1 = SE->getMulExpr(Y->getC(), X->getA());
489 const SCEV *A1B2 = SE->getMulExpr(X->getA(), Y->getB());
490 const SCEV *A2B1 = SE->getMulExpr(Y->getA(), X->getB());
491 const SCEVConstant *C1A2_C2A1 =
492 dyn_cast<SCEVConstant>(SE->getMinusSCEV(C1A2, C2A1));
493 const SCEVConstant *C1B2_C2B1 =
494 dyn_cast<SCEVConstant>(SE->getMinusSCEV(C1B2, C2B1));
495 const SCEVConstant *A1B2_A2B1 =
496 dyn_cast<SCEVConstant>(SE->getMinusSCEV(A1B2, A2B1));
497 const SCEVConstant *A2B1_A1B2 =
498 dyn_cast<SCEVConstant>(SE->getMinusSCEV(A2B1, A1B2));
499 if (!C1B2_C2B1 || !C1A2_C2A1 ||
500 !A1B2_A2B1 || !A2B1_A1B2)
501 return false;
502 APInt Xtop = C1B2_C2B1->getValue()->getValue();
503 APInt Xbot = A1B2_A2B1->getValue()->getValue();
504 APInt Ytop = C1A2_C2A1->getValue()->getValue();
505 APInt Ybot = A2B1_A1B2->getValue()->getValue();
506 DEBUG(dbgs() << "\t\tXtop = " << Xtop << "\n");
507 DEBUG(dbgs() << "\t\tXbot = " << Xbot << "\n");
508 DEBUG(dbgs() << "\t\tYtop = " << Ytop << "\n");
509 DEBUG(dbgs() << "\t\tYbot = " << Ybot << "\n");
510 APInt Xq = Xtop; // these need to be initialized, even
511 APInt Xr = Xtop; // though they're just going to be overwritten
512 APInt::sdivrem(Xtop, Xbot, Xq, Xr);
513 APInt Yq = Ytop;
514 APInt Yr = Ytop;;
515 APInt::sdivrem(Ytop, Ybot, Yq, Yr);
516 if (Xr != 0 || Yr != 0) {
517 X->setEmpty();
518 ++DeltaSuccesses;
519 return true;
520 }
521 DEBUG(dbgs() << "\t\tX = " << Xq << ", Y = " << Yq << "\n");
522 if (Xq.slt(0) || Yq.slt(0)) {
523 X->setEmpty();
524 ++DeltaSuccesses;
525 return true;
526 }
527 if (const SCEVConstant *CUB =
528 collectConstantUpperBound(X->getAssociatedLoop(), Prod1->getType())) {
529 APInt UpperBound = CUB->getValue()->getValue();
530 DEBUG(dbgs() << "\t\tupper bound = " << UpperBound << "\n");
531 if (Xq.sgt(UpperBound) || Yq.sgt(UpperBound)) {
532 X->setEmpty();
533 ++DeltaSuccesses;
534 return true;
535 }
536 }
537 X->setPoint(SE->getConstant(Xq),
538 SE->getConstant(Yq),
539 X->getAssociatedLoop());
540 ++DeltaSuccesses;
541 return true;
542 }
543 return false;
544 }
545
546 // if (X->isLine() && Y->isPoint()) This case can't occur.
547 assert(!(X->isLine() && Y->isPoint()) && "This case should never occur");
548
549 if (X->isPoint() && Y->isLine()) {
550 DEBUG(dbgs() << "\t intersect Point and Line\n");
551 const SCEV *A1X1 = SE->getMulExpr(Y->getA(), X->getX());
552 const SCEV *B1Y1 = SE->getMulExpr(Y->getB(), X->getY());
553 const SCEV *Sum = SE->getAddExpr(A1X1, B1Y1);
554 if (isKnownPredicate(CmpInst::ICMP_EQ, Sum, Y->getC()))
555 return false;
556 if (isKnownPredicate(CmpInst::ICMP_NE, Sum, Y->getC())) {
557 X->setEmpty();
558 ++DeltaSuccesses;
559 return true;
560 }
561 return false;
562 }
563
564 llvm_unreachable("shouldn't reach the end of Constraint intersection");
565 return false;
566}
567
568
569//===----------------------------------------------------------------------===//
570// DependenceAnalysis methods
571
572// For debugging purposes. Dumps a dependence to OS.
573void Dependence::dump(raw_ostream &OS) const {
574 bool Splitable = false;
575 if (isConfused())
576 OS << "confused";
577 else {
578 if (isConsistent())
579 OS << "consistent ";
580 if (isFlow())
581 OS << "flow";
582 else if (isOutput())
583 OS << "output";
584 else if (isAnti())
585 OS << "anti";
586 else if (isInput())
587 OS << "input";
588 unsigned Levels = getLevels();
589 if (Levels) {
590 OS << " [";
591 for (unsigned II = 1; II <= Levels; ++II) {
592 if (isSplitable(II))
593 Splitable = true;
594 if (isPeelFirst(II))
595 OS << 'p';
596 const SCEV *Distance = getDistance(II);
597 if (Distance)
598 OS << *Distance;
599 else if (isScalar(II))
600 OS << "S";
601 else {
602 unsigned Direction = getDirection(II);
603 if (Direction == DVEntry::ALL)
604 OS << "*";
605 else {
606 if (Direction & DVEntry::LT)
607 OS << "<";
608 if (Direction & DVEntry::EQ)
609 OS << "=";
610 if (Direction & DVEntry::GT)
611 OS << ">";
612 }
613 }
614 if (isPeelLast(II))
615 OS << 'p';
616 if (II < Levels)
617 OS << " ";
618 }
619 if (isLoopIndependent())
620 OS << "|<";
621 OS << "]";
622 if (Splitable)
623 OS << " splitable";
624 }
625 }
626 OS << "!\n";
627}
628
629
630
631static
632AliasAnalysis::AliasResult underlyingObjectsAlias(AliasAnalysis *AA,
633 const Value *A,
634 const Value *B) {
635 const Value *AObj = GetUnderlyingObject(A);
636 const Value *BObj = GetUnderlyingObject(B);
637 return AA->alias(AObj, AA->getTypeStoreSize(AObj->getType()),
638 BObj, AA->getTypeStoreSize(BObj->getType()));
639}
640
641
642// Returns true if the load or store can be analyzed. Atomic and volatile
643// operations have properties which this analysis does not understand.
644static
645bool isLoadOrStore(const Instruction *I) {
646 if (const LoadInst *LI = dyn_cast<LoadInst>(I))
647 return LI->isUnordered();
648 else if (const StoreInst *SI = dyn_cast<StoreInst>(I))
649 return SI->isUnordered();
650 return false;
651}
652
653
654static
655const Value *getPointerOperand(const Instruction *I) {
656 if (const LoadInst *LI = dyn_cast<LoadInst>(I))
657 return LI->getPointerOperand();
658 if (const StoreInst *SI = dyn_cast<StoreInst>(I))
659 return SI->getPointerOperand();
660 llvm_unreachable("Value is not load or store instruction");
661 return 0;
662}
663
664
665// Examines the loop nesting of the Src and Dst
666// instructions and establishes their shared loops. Sets the variables
667// CommonLevels, SrcLevels, and MaxLevels.
668// The source and destination instructions needn't be contained in the same
669// loop. The routine establishNestingLevels finds the level of most deeply
670// nested loop that contains them both, CommonLevels. An instruction that's
671// not contained in a loop is at level = 0. MaxLevels is equal to the level
672// of the source plus the level of the destination, minus CommonLevels.
673// This lets us allocate vectors MaxLevels in length, with room for every
674// distinct loop referenced in both the source and destination subscripts.
675// The variable SrcLevels is the nesting depth of the source instruction.
676// It's used to help calculate distinct loops referenced by the destination.
677// Here's the map from loops to levels:
678// 0 - unused
679// 1 - outermost common loop
680// ... - other common loops
681// CommonLevels - innermost common loop
682// ... - loops containing Src but not Dst
683// SrcLevels - innermost loop containing Src but not Dst
684// ... - loops containing Dst but not Src
685// MaxLevels - innermost loops containing Dst but not Src
686// Consider the follow code fragment:
687// for (a = ...) {
688// for (b = ...) {
689// for (c = ...) {
690// for (d = ...) {
691// A[] = ...;
692// }
693// }
694// for (e = ...) {
695// for (f = ...) {
696// for (g = ...) {
697// ... = A[];
698// }
699// }
700// }
701// }
702// }
703// If we're looking at the possibility of a dependence between the store
704// to A (the Src) and the load from A (the Dst), we'll note that they
705// have 2 loops in common, so CommonLevels will equal 2 and the direction
706// vector for Result will have 2 entries. SrcLevels = 4 and MaxLevels = 7.
707// A map from loop names to loop numbers would look like
708// a - 1
709// b - 2 = CommonLevels
710// c - 3
711// d - 4 = SrcLevels
712// e - 5
713// f - 6
714// g - 7 = MaxLevels
715void DependenceAnalysis::establishNestingLevels(const Instruction *Src,
716 const Instruction *Dst) {
717 const BasicBlock *SrcBlock = Src->getParent();
718 const BasicBlock *DstBlock = Dst->getParent();
719 unsigned SrcLevel = LI->getLoopDepth(SrcBlock);
720 unsigned DstLevel = LI->getLoopDepth(DstBlock);
721 const Loop *SrcLoop = LI->getLoopFor(SrcBlock);
722 const Loop *DstLoop = LI->getLoopFor(DstBlock);
723 SrcLevels = SrcLevel;
724 MaxLevels = SrcLevel + DstLevel;
725 while (SrcLevel > DstLevel) {
726 SrcLoop = SrcLoop->getParentLoop();
727 SrcLevel--;
728 }
729 while (DstLevel > SrcLevel) {
730 DstLoop = DstLoop->getParentLoop();
731 DstLevel--;
732 }
733 while (SrcLoop != DstLoop) {
734 SrcLoop = SrcLoop->getParentLoop();
735 DstLoop = DstLoop->getParentLoop();
736 SrcLevel--;
737 }
738 CommonLevels = SrcLevel;
739 MaxLevels -= CommonLevels;
740}
741
742
743// Given one of the loops containing the source, return
744// its level index in our numbering scheme.
745unsigned DependenceAnalysis::mapSrcLoop(const Loop *SrcLoop) const {
746 return SrcLoop->getLoopDepth();
747}
748
749
750// Given one of the loops containing the destination,
751// return its level index in our numbering scheme.
752unsigned DependenceAnalysis::mapDstLoop(const Loop *DstLoop) const {
753 unsigned D = DstLoop->getLoopDepth();
754 if (D > CommonLevels)
755 return D - CommonLevels + SrcLevels;
756 else
757 return D;
758}
759
760
761// Returns true if Expression is loop invariant in LoopNest.
762bool DependenceAnalysis::isLoopInvariant(const SCEV *Expression,
763 const Loop *LoopNest) const {
764 if (!LoopNest)
765 return true;
766 return SE->isLoopInvariant(Expression, LoopNest) &&
767 isLoopInvariant(Expression, LoopNest->getParentLoop());
768}
769
770
771
772// Finds the set of loops from the LoopNest that
773// have a level <= CommonLevels and are referred to by the SCEV Expression.
774void DependenceAnalysis::collectCommonLoops(const SCEV *Expression,
775 const Loop *LoopNest,
776 SmallBitVector &Loops) const {
777 while (LoopNest) {
778 unsigned Level = LoopNest->getLoopDepth();
779 if (Level <= CommonLevels && !SE->isLoopInvariant(Expression, LoopNest))
780 Loops.set(Level);
781 LoopNest = LoopNest->getParentLoop();
782 }
783}
784
785
786// removeMatchingExtensions - Examines a subscript pair.
787// If the source and destination are identically sign (or zero)
788// extended, it strips off the extension in an effect to simplify
789// the actual analysis.
790void DependenceAnalysis::removeMatchingExtensions(Subscript *Pair) {
791 const SCEV *Src = Pair->Src;
792 const SCEV *Dst = Pair->Dst;
793 if ((isa<SCEVZeroExtendExpr>(Src) && isa<SCEVZeroExtendExpr>(Dst)) ||
794 (isa<SCEVSignExtendExpr>(Src) && isa<SCEVSignExtendExpr>(Dst))) {
795 const SCEVCastExpr *SrcCast = cast<SCEVCastExpr>(Src);
796 const SCEVCastExpr *DstCast = cast<SCEVCastExpr>(Dst);
797 if (SrcCast->getType() == DstCast->getType()) {
798 Pair->Src = SrcCast->getOperand();
799 Pair->Dst = DstCast->getOperand();
800 }
801 }
802}
803
804
805// Examine the scev and return true iff it's linear.
806// Collect any loops mentioned in the set of "Loops".
807bool DependenceAnalysis::checkSrcSubscript(const SCEV *Src,
808 const Loop *LoopNest,
809 SmallBitVector &Loops) {
810 const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(Src);
811 if (!AddRec)
812 return isLoopInvariant(Src, LoopNest);
813 const SCEV *Start = AddRec->getStart();
814 const SCEV *Step = AddRec->getStepRecurrence(*SE);
815 if (!isLoopInvariant(Step, LoopNest))
816 return false;
817 Loops.set(mapSrcLoop(AddRec->getLoop()));
818 return checkSrcSubscript(Start, LoopNest, Loops);
819}
820
821
822
823// Examine the scev and return true iff it's linear.
824// Collect any loops mentioned in the set of "Loops".
825bool DependenceAnalysis::checkDstSubscript(const SCEV *Dst,
826 const Loop *LoopNest,
827 SmallBitVector &Loops) {
828 const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(Dst);
829 if (!AddRec)
830 return isLoopInvariant(Dst, LoopNest);
831 const SCEV *Start = AddRec->getStart();
832 const SCEV *Step = AddRec->getStepRecurrence(*SE);
833 if (!isLoopInvariant(Step, LoopNest))
834 return false;
835 Loops.set(mapDstLoop(AddRec->getLoop()));
836 return checkDstSubscript(Start, LoopNest, Loops);
837}
838
839
840// Examines the subscript pair (the Src and Dst SCEVs)
841// and classifies it as either ZIV, SIV, RDIV, MIV, or Nonlinear.
842// Collects the associated loops in a set.
843DependenceAnalysis::Subscript::ClassificationKind
844DependenceAnalysis::classifyPair(const SCEV *Src, const Loop *SrcLoopNest,
845 const SCEV *Dst, const Loop *DstLoopNest,
846 SmallBitVector &Loops) {
847 SmallBitVector SrcLoops(MaxLevels + 1);
848 SmallBitVector DstLoops(MaxLevels + 1);
849 if (!checkSrcSubscript(Src, SrcLoopNest, SrcLoops))
850 return Subscript::NonLinear;
851 if (!checkDstSubscript(Dst, DstLoopNest, DstLoops))
852 return Subscript::NonLinear;
853 Loops = SrcLoops;
854 Loops |= DstLoops;
855 unsigned N = Loops.count();
856 if (N == 0)
857 return Subscript::ZIV;
858 if (N == 1)
859 return Subscript::SIV;
860 if (N == 2 && (SrcLoops.count() == 0 ||
861 DstLoops.count() == 0 ||
862 (SrcLoops.count() == 1 && DstLoops.count() == 1)))
863 return Subscript::RDIV;
864 return Subscript::MIV;
865}
866
867
868// A wrapper around SCEV::isKnownPredicate.
869// Looks for cases where we're interested in comparing for equality.
870// If both X and Y have been identically sign or zero extended,
871// it strips off the (confusing) extensions before invoking
872// SCEV::isKnownPredicate. Perhaps, someday, the ScalarEvolution package
873// will be similarly updated.
874//
875// If SCEV::isKnownPredicate can't prove the predicate,
876// we try simple subtraction, which seems to help in some cases
877// involving symbolics.
878bool DependenceAnalysis::isKnownPredicate(ICmpInst::Predicate Pred,
879 const SCEV *X,
880 const SCEV *Y) const {
881 if (Pred == CmpInst::ICMP_EQ ||
882 Pred == CmpInst::ICMP_NE) {
883 if ((isa<SCEVSignExtendExpr>(X) &&
884 isa<SCEVSignExtendExpr>(Y)) ||
885 (isa<SCEVZeroExtendExpr>(X) &&
886 isa<SCEVZeroExtendExpr>(Y))) {
887 const SCEVCastExpr *CX = cast<SCEVCastExpr>(X);
888 const SCEVCastExpr *CY = cast<SCEVCastExpr>(Y);
889 const SCEV *Xop = CX->getOperand();
890 const SCEV *Yop = CY->getOperand();
891 if (Xop->getType() == Yop->getType()) {
892 X = Xop;
893 Y = Yop;
894 }
895 }
896 }
897 if (SE->isKnownPredicate(Pred, X, Y))
898 return true;
899 // If SE->isKnownPredicate can't prove the condition,
900 // we try the brute-force approach of subtracting
901 // and testing the difference.
902 // By testing with SE->isKnownPredicate first, we avoid
903 // the possibility of overflow when the arguments are constants.
904 const SCEV *Delta = SE->getMinusSCEV(X, Y);
905 switch (Pred) {
906 case CmpInst::ICMP_EQ:
907 return Delta->isZero();
908 case CmpInst::ICMP_NE:
909 return SE->isKnownNonZero(Delta);
910 case CmpInst::ICMP_SGE:
911 return SE->isKnownNonNegative(Delta);
912 case CmpInst::ICMP_SLE:
913 return SE->isKnownNonPositive(Delta);
914 case CmpInst::ICMP_SGT:
915 return SE->isKnownPositive(Delta);
916 case CmpInst::ICMP_SLT:
917 return SE->isKnownNegative(Delta);
918 default:
919 llvm_unreachable("unexpected predicate in isKnownPredicate");
920 }
921}
922
923
924// All subscripts are all the same type.
925// Loop bound may be smaller (e.g., a char).
926// Should zero extend loop bound, since it's always >= 0.
927// This routine collects upper bound and extends if needed.
928// Return null if no bound available.
929const SCEV *DependenceAnalysis::collectUpperBound(const Loop *L,
930 Type *T) const {
931 if (SE->hasLoopInvariantBackedgeTakenCount(L)) {
932 const SCEV *UB = SE->getBackedgeTakenCount(L);
933 return SE->getNoopOrZeroExtend(UB, T);
934 }
935 return NULL;
936}
937
938
939// Calls collectUpperBound(), then attempts to cast it to SCEVConstant.
940// If the cast fails, returns NULL.
941const SCEVConstant *DependenceAnalysis::collectConstantUpperBound(const Loop *L,
942 Type *T
943 ) const {
944 if (const SCEV *UB = collectUpperBound(L, T))
945 return dyn_cast<SCEVConstant>(UB);
946 return NULL;
947}
948
949
950// testZIV -
951// When we have a pair of subscripts of the form [c1] and [c2],
952// where c1 and c2 are both loop invariant, we attack it using
953// the ZIV test. Basically, we test by comparing the two values,
954// but there are actually three possible results:
955// 1) the values are equal, so there's a dependence
956// 2) the values are different, so there's no dependence
957// 3) the values might be equal, so we have to assume a dependence.
958//
959// Return true if dependence disproved.
960bool DependenceAnalysis::testZIV(const SCEV *Src,
961 const SCEV *Dst,
962 FullDependence &Result) const {
963 DEBUG(dbgs() << " src = " << *Src << "\n");
964 DEBUG(dbgs() << " dst = " << *Dst << "\n");
965 ++ZIVapplications;
966 if (isKnownPredicate(CmpInst::ICMP_EQ, Src, Dst)) {
967 DEBUG(dbgs() << " provably dependent\n");
968 return false; // provably dependent
969 }
970 if (isKnownPredicate(CmpInst::ICMP_NE, Src, Dst)) {
971 DEBUG(dbgs() << " provably independent\n");
972 ++ZIVindependence;
973 return true; // provably independent
974 }
975 DEBUG(dbgs() << " possibly dependent\n");
976 Result.Consistent = false;
977 return false; // possibly dependent
978}
979
980
981// strongSIVtest -
982// From the paper, Practical Dependence Testing, Section 4.2.1
983//
984// When we have a pair of subscripts of the form [c1 + a*i] and [c2 + a*i],
985// where i is an induction variable, c1 and c2 are loop invariant,
986// and a is a constant, we can solve it exactly using the Strong SIV test.
987//
988// Can prove independence. Failing that, can compute distance (and direction).
989// In the presence of symbolic terms, we can sometimes make progress.
990//
991// If there's a dependence,
992//
993// c1 + a*i = c2 + a*i'
994//
995// The dependence distance is
996//
997// d = i' - i = (c1 - c2)/a
998//
999// A dependence only exists if d is an integer and abs(d) <= U, where U is the
1000// loop's upper bound. If a dependence exists, the dependence direction is
1001// defined as
1002//
1003// { < if d > 0
1004// direction = { = if d = 0
1005// { > if d < 0
1006//
1007// Return true if dependence disproved.
1008bool DependenceAnalysis::strongSIVtest(const SCEV *Coeff,
1009 const SCEV *SrcConst,
1010 const SCEV *DstConst,
1011 const Loop *CurLoop,
1012 unsigned Level,
1013 FullDependence &Result,
1014 Constraint &NewConstraint) const {
1015 DEBUG(dbgs() << "\tStrong SIV test\n");
1016 DEBUG(dbgs() << "\t Coeff = " << *Coeff);
1017 DEBUG(dbgs() << ", " << *Coeff->getType() << "\n");
1018 DEBUG(dbgs() << "\t SrcConst = " << *SrcConst);
1019 DEBUG(dbgs() << ", " << *SrcConst->getType() << "\n");
1020 DEBUG(dbgs() << "\t DstConst = " << *DstConst);
1021 DEBUG(dbgs() << ", " << *DstConst->getType() << "\n");
1022 ++StrongSIVapplications;
1023 assert(0 < Level && Level <= CommonLevels && "level out of range");
1024 Level--;
1025
1026 const SCEV *Delta = SE->getMinusSCEV(SrcConst, DstConst);
1027 DEBUG(dbgs() << "\t Delta = " << *Delta);
1028 DEBUG(dbgs() << ", " << *Delta->getType() << "\n");
1029
1030 // check that |Delta| < iteration count
1031 if (const SCEV *UpperBound = collectUpperBound(CurLoop, Delta->getType())) {
1032 DEBUG(dbgs() << "\t UpperBound = " << *UpperBound);
1033 DEBUG(dbgs() << ", " << *UpperBound->getType() << "\n");
1034 const SCEV *AbsDelta =
1035 SE->isKnownNonNegative(Delta) ? Delta : SE->getNegativeSCEV(Delta);
1036 const SCEV *AbsCoeff =
1037 SE->isKnownNonNegative(Coeff) ? Coeff : SE->getNegativeSCEV(Coeff);
1038 const SCEV *Product = SE->getMulExpr(UpperBound, AbsCoeff);
1039 if (isKnownPredicate(CmpInst::ICMP_SGT, AbsDelta, Product)) {
1040 // Distance greater than trip count - no dependence
1041 ++StrongSIVindependence;
1042 ++StrongSIVsuccesses;
1043 return true;
1044 }
1045 }
1046
1047 // Can we compute distance?
1048 if (isa<SCEVConstant>(Delta) && isa<SCEVConstant>(Coeff)) {
1049 APInt ConstDelta = cast<SCEVConstant>(Delta)->getValue()->getValue();
1050 APInt ConstCoeff = cast<SCEVConstant>(Coeff)->getValue()->getValue();
1051 APInt Distance = ConstDelta; // these need to be initialized
1052 APInt Remainder = ConstDelta;
1053 APInt::sdivrem(ConstDelta, ConstCoeff, Distance, Remainder);
1054 DEBUG(dbgs() << "\t Distance = " << Distance << "\n");
1055 DEBUG(dbgs() << "\t Remainder = " << Remainder << "\n");
1056 // Make sure Coeff divides Delta exactly
1057 if (Remainder != 0) {
1058 // Coeff doesn't divide Distance, no dependence
1059 ++StrongSIVindependence;
1060 ++StrongSIVsuccesses;
1061 return true;
1062 }
1063 Result.DV[Level].Distance = SE->getConstant(Distance);
1064 NewConstraint.setDistance(SE->getConstant(Distance), CurLoop);
1065 if (Distance.sgt(0))
1066 Result.DV[Level].Direction &= Dependence::DVEntry::LT;
1067 else if (Distance.slt(0))
1068 Result.DV[Level].Direction &= Dependence::DVEntry::GT;
1069 else
1070 Result.DV[Level].Direction &= Dependence::DVEntry::EQ;
1071 ++StrongSIVsuccesses;
1072 }
1073 else if (Delta->isZero()) {
1074 // since 0/X == 0
1075 Result.DV[Level].Distance = Delta;
1076 NewConstraint.setDistance(Delta, CurLoop);
1077 Result.DV[Level].Direction &= Dependence::DVEntry::EQ;
1078 ++StrongSIVsuccesses;
1079 }
1080 else {
1081 if (Coeff->isOne()) {
1082 DEBUG(dbgs() << "\t Distance = " << *Delta << "\n");
1083 Result.DV[Level].Distance = Delta; // since X/1 == X
1084 NewConstraint.setDistance(Delta, CurLoop);
1085 }
1086 else {
1087 Result.Consistent = false;
1088 NewConstraint.setLine(Coeff,
1089 SE->getNegativeSCEV(Coeff),
1090 SE->getNegativeSCEV(Delta), CurLoop);
1091 }
1092
1093 // maybe we can get a useful direction
1094 bool DeltaMaybeZero = !SE->isKnownNonZero(Delta);
1095 bool DeltaMaybePositive = !SE->isKnownNonPositive(Delta);
1096 bool DeltaMaybeNegative = !SE->isKnownNonNegative(Delta);
1097 bool CoeffMaybePositive = !SE->isKnownNonPositive(Coeff);
1098 bool CoeffMaybeNegative = !SE->isKnownNonNegative(Coeff);
1099 // The double negatives above are confusing.
1100 // It helps to read !SE->isKnownNonZero(Delta)
1101 // as "Delta might be Zero"
1102 unsigned NewDirection = Dependence::DVEntry::NONE;
1103 if ((DeltaMaybePositive && CoeffMaybePositive) ||
1104 (DeltaMaybeNegative && CoeffMaybeNegative))
1105 NewDirection = Dependence::DVEntry::LT;
1106 if (DeltaMaybeZero)
1107 NewDirection |= Dependence::DVEntry::EQ;
1108 if ((DeltaMaybeNegative && CoeffMaybePositive) ||
1109 (DeltaMaybePositive && CoeffMaybeNegative))
1110 NewDirection |= Dependence::DVEntry::GT;
1111 if (NewDirection < Result.DV[Level].Direction)
1112 ++StrongSIVsuccesses;
1113 Result.DV[Level].Direction &= NewDirection;
1114 }
1115 return false;
1116}
1117
1118
1119// weakCrossingSIVtest -
1120// From the paper, Practical Dependence Testing, Section 4.2.2
1121//
1122// When we have a pair of subscripts of the form [c1 + a*i] and [c2 - a*i],
1123// where i is an induction variable, c1 and c2 are loop invariant,
1124// and a is a constant, we can solve it exactly using the
1125// Weak-Crossing SIV test.
1126//
1127// Given c1 + a*i = c2 - a*i', we can look for the intersection of
1128// the two lines, where i = i', yielding
1129//
1130// c1 + a*i = c2 - a*i
1131// 2a*i = c2 - c1
1132// i = (c2 - c1)/2a
1133//
1134// If i < 0, there is no dependence.
1135// If i > upperbound, there is no dependence.
1136// If i = 0 (i.e., if c1 = c2), there's a dependence with distance = 0.
1137// If i = upperbound, there's a dependence with distance = 0.
1138// If i is integral, there's a dependence (all directions).
1139// If the non-integer part = 1/2, there's a dependence (<> directions).
1140// Otherwise, there's no dependence.
1141//
1142// Can prove independence. Failing that,
1143// can sometimes refine the directions.
1144// Can determine iteration for splitting.
1145//
1146// Return true if dependence disproved.
1147bool DependenceAnalysis::weakCrossingSIVtest(const SCEV *Coeff,
1148 const SCEV *SrcConst,
1149 const SCEV *DstConst,
1150 const Loop *CurLoop,
1151 unsigned Level,
1152 FullDependence &Result,
1153 Constraint &NewConstraint,
1154 const SCEV *&SplitIter) const {
1155 DEBUG(dbgs() << "\tWeak-Crossing SIV test\n");
1156 DEBUG(dbgs() << "\t Coeff = " << *Coeff << "\n");
1157 DEBUG(dbgs() << "\t SrcConst = " << *SrcConst << "\n");
1158 DEBUG(dbgs() << "\t DstConst = " << *DstConst << "\n");
1159 ++WeakCrossingSIVapplications;
1160 assert(0 < Level && Level <= CommonLevels && "Level out of range");
1161 Level--;
1162 Result.Consistent = false;
1163 const SCEV *Delta = SE->getMinusSCEV(DstConst, SrcConst);
1164 DEBUG(dbgs() << "\t Delta = " << *Delta << "\n");
1165 NewConstraint.setLine(Coeff, Coeff, Delta, CurLoop);
1166 if (Delta->isZero()) {
Sebastian Popb4164282012-10-12 02:04:32 +00001167 Result.DV[Level].Direction &= unsigned(~Dependence::DVEntry::LT);
1168 Result.DV[Level].Direction &= unsigned(~Dependence::DVEntry::GT);
Sebastian Popad434992012-10-11 07:32:34 +00001169 ++WeakCrossingSIVsuccesses;
1170 if (!Result.DV[Level].Direction) {
1171 ++WeakCrossingSIVindependence;
1172 return true;
1173 }
1174 Result.DV[Level].Distance = Delta; // = 0
1175 return false;
1176 }
1177 const SCEVConstant *ConstCoeff = dyn_cast<SCEVConstant>(Coeff);
1178 if (!ConstCoeff)
1179 return false;
1180
1181 Result.DV[Level].Splitable = true;
1182 if (SE->isKnownNegative(ConstCoeff)) {
1183 ConstCoeff = dyn_cast<SCEVConstant>(SE->getNegativeSCEV(ConstCoeff));
1184 assert(ConstCoeff &&
1185 "dynamic cast of negative of ConstCoeff should yield constant");
1186 Delta = SE->getNegativeSCEV(Delta);
1187 }
1188 assert(SE->isKnownPositive(ConstCoeff) && "ConstCoeff should be positive");
1189
1190 // compute SplitIter for use by DependenceAnalysis::getSplitIteration()
1191 SplitIter =
1192 SE->getUDivExpr(SE->getSMaxExpr(SE->getConstant(Delta->getType(), 0),
1193 Delta),
1194 SE->getMulExpr(SE->getConstant(Delta->getType(), 2),
1195 ConstCoeff));
1196 DEBUG(dbgs() << "\t Split iter = " << *SplitIter << "\n");
1197
1198 const SCEVConstant *ConstDelta = dyn_cast<SCEVConstant>(Delta);
1199 if (!ConstDelta)
1200 return false;
1201
1202 // We're certain that ConstCoeff > 0; therefore,
1203 // if Delta < 0, then no dependence.
1204 DEBUG(dbgs() << "\t Delta = " << *Delta << "\n");
1205 DEBUG(dbgs() << "\t ConstCoeff = " << *ConstCoeff << "\n");
1206 if (SE->isKnownNegative(Delta)) {
1207 // No dependence, Delta < 0
1208 ++WeakCrossingSIVindependence;
1209 ++WeakCrossingSIVsuccesses;
1210 return true;
1211 }
1212
1213 // We're certain that Delta > 0 and ConstCoeff > 0.
1214 // Check Delta/(2*ConstCoeff) against upper loop bound
1215 if (const SCEV *UpperBound = collectUpperBound(CurLoop, Delta->getType())) {
1216 DEBUG(dbgs() << "\t UpperBound = " << *UpperBound << "\n");
1217 const SCEV *ConstantTwo = SE->getConstant(UpperBound->getType(), 2);
1218 const SCEV *ML = SE->getMulExpr(SE->getMulExpr(ConstCoeff, UpperBound),
1219 ConstantTwo);
1220 DEBUG(dbgs() << "\t ML = " << *ML << "\n");
1221 if (isKnownPredicate(CmpInst::ICMP_SGT, Delta, ML)) {
1222 // Delta too big, no dependence
1223 ++WeakCrossingSIVindependence;
1224 ++WeakCrossingSIVsuccesses;
1225 return true;
1226 }
1227 if (isKnownPredicate(CmpInst::ICMP_EQ, Delta, ML)) {
1228 // i = i' = UB
Sebastian Popb4164282012-10-12 02:04:32 +00001229 Result.DV[Level].Direction &= unsigned(~Dependence::DVEntry::LT);
1230 Result.DV[Level].Direction &= unsigned(~Dependence::DVEntry::GT);
Sebastian Popad434992012-10-11 07:32:34 +00001231 ++WeakCrossingSIVsuccesses;
1232 if (!Result.DV[Level].Direction) {
1233 ++WeakCrossingSIVindependence;
1234 return true;
1235 }
1236 Result.DV[Level].Splitable = false;
1237 Result.DV[Level].Distance = SE->getConstant(Delta->getType(), 0);
1238 return false;
1239 }
1240 }
1241
1242 // check that Coeff divides Delta
1243 APInt APDelta = ConstDelta->getValue()->getValue();
1244 APInt APCoeff = ConstCoeff->getValue()->getValue();
1245 APInt Distance = APDelta; // these need to be initialzed
1246 APInt Remainder = APDelta;
1247 APInt::sdivrem(APDelta, APCoeff, Distance, Remainder);
1248 DEBUG(dbgs() << "\t Remainder = " << Remainder << "\n");
1249 if (Remainder != 0) {
1250 // Coeff doesn't divide Delta, no dependence
1251 ++WeakCrossingSIVindependence;
1252 ++WeakCrossingSIVsuccesses;
1253 return true;
1254 }
1255 DEBUG(dbgs() << "\t Distance = " << Distance << "\n");
1256
1257 // if 2*Coeff doesn't divide Delta, then the equal direction isn't possible
1258 APInt Two = APInt(Distance.getBitWidth(), 2, true);
1259 Remainder = Distance.srem(Two);
1260 DEBUG(dbgs() << "\t Remainder = " << Remainder << "\n");
1261 if (Remainder != 0) {
1262 // Equal direction isn't possible
Sebastian Popb4164282012-10-12 02:04:32 +00001263 Result.DV[Level].Direction &= unsigned(~Dependence::DVEntry::EQ);
Sebastian Popad434992012-10-11 07:32:34 +00001264 ++WeakCrossingSIVsuccesses;
1265 }
1266 return false;
1267}
1268
1269
1270// Kirch's algorithm, from
1271//
1272// Optimizing Supercompilers for Supercomputers
1273// Michael Wolfe
1274// MIT Press, 1989
1275//
1276// Program 2.1, page 29.
1277// Computes the GCD of AM and BM.
1278// Also finds a solution to the equation ax - by = gdc(a, b).
1279// Returns true iff the gcd divides Delta.
1280static
1281bool findGCD(unsigned Bits, APInt AM, APInt BM, APInt Delta,
1282 APInt &G, APInt &X, APInt &Y) {
1283 APInt A0(Bits, 1, true), A1(Bits, 0, true);
1284 APInt B0(Bits, 0, true), B1(Bits, 1, true);
1285 APInt G0 = AM.abs();
1286 APInt G1 = BM.abs();
1287 APInt Q = G0; // these need to be initialized
1288 APInt R = G0;
1289 APInt::sdivrem(G0, G1, Q, R);
1290 while (R != 0) {
1291 APInt A2 = A0 - Q*A1; A0 = A1; A1 = A2;
1292 APInt B2 = B0 - Q*B1; B0 = B1; B1 = B2;
1293 G0 = G1; G1 = R;
1294 APInt::sdivrem(G0, G1, Q, R);
1295 }
1296 G = G1;
1297 DEBUG(dbgs() << "\t GCD = " << G << "\n");
1298 X = AM.slt(0) ? -A1 : A1;
1299 Y = BM.slt(0) ? B1 : -B1;
1300
1301 // make sure gcd divides Delta
1302 R = Delta.srem(G);
1303 if (R != 0)
1304 return true; // gcd doesn't divide Delta, no dependence
1305 Q = Delta.sdiv(G);
1306 X *= Q;
1307 Y *= Q;
1308 return false;
1309}
1310
1311
1312static
1313APInt floorOfQuotient(APInt A, APInt B) {
1314 APInt Q = A; // these need to be initialized
1315 APInt R = A;
1316 APInt::sdivrem(A, B, Q, R);
1317 if (R == 0)
1318 return Q;
1319 if ((A.sgt(0) && B.sgt(0)) ||
1320 (A.slt(0) && B.slt(0)))
1321 return Q;
1322 else
1323 return Q - 1;
1324}
1325
1326
1327static
1328APInt ceilingOfQuotient(APInt A, APInt B) {
1329 APInt Q = A; // these need to be initialized
1330 APInt R = A;
1331 APInt::sdivrem(A, B, Q, R);
1332 if (R == 0)
1333 return Q;
1334 if ((A.sgt(0) && B.sgt(0)) ||
1335 (A.slt(0) && B.slt(0)))
1336 return Q + 1;
1337 else
1338 return Q;
1339}
1340
1341
1342static
1343APInt maxAPInt(APInt A, APInt B) {
1344 return A.sgt(B) ? A : B;
1345}
1346
1347
1348static
1349APInt minAPInt(APInt A, APInt B) {
1350 return A.slt(B) ? A : B;
1351}
1352
1353
1354// exactSIVtest -
1355// When we have a pair of subscripts of the form [c1 + a1*i] and [c2 + a2*i],
1356// where i is an induction variable, c1 and c2 are loop invariant, and a1
1357// and a2 are constant, we can solve it exactly using an algorithm developed
1358// by Banerjee and Wolfe. See Section 2.5.3 in
1359//
1360// Optimizing Supercompilers for Supercomputers
1361// Michael Wolfe
1362// MIT Press, 1989
1363//
1364// It's slower than the specialized tests (strong SIV, weak-zero SIV, etc),
1365// so use them if possible. They're also a bit better with symbolics and,
1366// in the case of the strong SIV test, can compute Distances.
1367//
1368// Return true if dependence disproved.
1369bool DependenceAnalysis::exactSIVtest(const SCEV *SrcCoeff,
1370 const SCEV *DstCoeff,
1371 const SCEV *SrcConst,
1372 const SCEV *DstConst,
1373 const Loop *CurLoop,
1374 unsigned Level,
1375 FullDependence &Result,
1376 Constraint &NewConstraint) const {
1377 DEBUG(dbgs() << "\tExact SIV test\n");
1378 DEBUG(dbgs() << "\t SrcCoeff = " << *SrcCoeff << " = AM\n");
1379 DEBUG(dbgs() << "\t DstCoeff = " << *DstCoeff << " = BM\n");
1380 DEBUG(dbgs() << "\t SrcConst = " << *SrcConst << "\n");
1381 DEBUG(dbgs() << "\t DstConst = " << *DstConst << "\n");
1382 ++ExactSIVapplications;
1383 assert(0 < Level && Level <= CommonLevels && "Level out of range");
1384 Level--;
1385 Result.Consistent = false;
1386 const SCEV *Delta = SE->getMinusSCEV(DstConst, SrcConst);
1387 DEBUG(dbgs() << "\t Delta = " << *Delta << "\n");
1388 NewConstraint.setLine(SrcCoeff, SE->getNegativeSCEV(DstCoeff),
1389 Delta, CurLoop);
1390 const SCEVConstant *ConstDelta = dyn_cast<SCEVConstant>(Delta);
1391 const SCEVConstant *ConstSrcCoeff = dyn_cast<SCEVConstant>(SrcCoeff);
1392 const SCEVConstant *ConstDstCoeff = dyn_cast<SCEVConstant>(DstCoeff);
1393 if (!ConstDelta || !ConstSrcCoeff || !ConstDstCoeff)
1394 return false;
1395
1396 // find gcd
1397 APInt G, X, Y;
1398 APInt AM = ConstSrcCoeff->getValue()->getValue();
1399 APInt BM = ConstDstCoeff->getValue()->getValue();
1400 unsigned Bits = AM.getBitWidth();
1401 if (findGCD(Bits, AM, BM, ConstDelta->getValue()->getValue(), G, X, Y)) {
1402 // gcd doesn't divide Delta, no dependence
1403 ++ExactSIVindependence;
1404 ++ExactSIVsuccesses;
1405 return true;
1406 }
1407
1408 DEBUG(dbgs() << "\t X = " << X << ", Y = " << Y << "\n");
1409
1410 // since SCEV construction normalizes, LM = 0
1411 APInt UM(Bits, 1, true);
1412 bool UMvalid = false;
1413 // UM is perhaps unavailable, let's check
1414 if (const SCEVConstant *CUB =
1415 collectConstantUpperBound(CurLoop, Delta->getType())) {
1416 UM = CUB->getValue()->getValue();
1417 DEBUG(dbgs() << "\t UM = " << UM << "\n");
1418 UMvalid = true;
1419 }
1420
1421 APInt TU(APInt::getSignedMaxValue(Bits));
1422 APInt TL(APInt::getSignedMinValue(Bits));
1423
1424 // test(BM/G, LM-X) and test(-BM/G, X-UM)
1425 APInt TMUL = BM.sdiv(G);
1426 if (TMUL.sgt(0)) {
1427 TL = maxAPInt(TL, ceilingOfQuotient(-X, TMUL));
1428 DEBUG(dbgs() << "\t TL = " << TL << "\n");
1429 if (UMvalid) {
1430 TU = minAPInt(TU, floorOfQuotient(UM - X, TMUL));
1431 DEBUG(dbgs() << "\t TU = " << TU << "\n");
1432 }
1433 }
1434 else {
1435 TU = minAPInt(TU, floorOfQuotient(-X, TMUL));
1436 DEBUG(dbgs() << "\t TU = " << TU << "\n");
1437 if (UMvalid) {
1438 TL = maxAPInt(TL, ceilingOfQuotient(UM - X, TMUL));
1439 DEBUG(dbgs() << "\t TL = " << TL << "\n");
1440 }
1441 }
1442
1443 // test(AM/G, LM-Y) and test(-AM/G, Y-UM)
1444 TMUL = AM.sdiv(G);
1445 if (TMUL.sgt(0)) {
1446 TL = maxAPInt(TL, ceilingOfQuotient(-Y, TMUL));
1447 DEBUG(dbgs() << "\t TL = " << TL << "\n");
1448 if (UMvalid) {
1449 TU = minAPInt(TU, floorOfQuotient(UM - Y, TMUL));
1450 DEBUG(dbgs() << "\t TU = " << TU << "\n");
1451 }
1452 }
1453 else {
1454 TU = minAPInt(TU, floorOfQuotient(-Y, TMUL));
1455 DEBUG(dbgs() << "\t TU = " << TU << "\n");
1456 if (UMvalid) {
1457 TL = maxAPInt(TL, ceilingOfQuotient(UM - Y, TMUL));
1458 DEBUG(dbgs() << "\t TL = " << TL << "\n");
1459 }
1460 }
1461 if (TL.sgt(TU)) {
1462 ++ExactSIVindependence;
1463 ++ExactSIVsuccesses;
1464 return true;
1465 }
1466
1467 // explore directions
1468 unsigned NewDirection = Dependence::DVEntry::NONE;
1469
1470 // less than
1471 APInt SaveTU(TU); // save these
1472 APInt SaveTL(TL);
1473 DEBUG(dbgs() << "\t exploring LT direction\n");
1474 TMUL = AM - BM;
1475 if (TMUL.sgt(0)) {
1476 TL = maxAPInt(TL, ceilingOfQuotient(X - Y + 1, TMUL));
1477 DEBUG(dbgs() << "\t\t TL = " << TL << "\n");
1478 }
1479 else {
1480 TU = minAPInt(TU, floorOfQuotient(X - Y + 1, TMUL));
1481 DEBUG(dbgs() << "\t\t TU = " << TU << "\n");
1482 }
1483 if (TL.sle(TU)) {
1484 NewDirection |= Dependence::DVEntry::LT;
1485 ++ExactSIVsuccesses;
1486 }
1487
1488 // equal
1489 TU = SaveTU; // restore
1490 TL = SaveTL;
1491 DEBUG(dbgs() << "\t exploring EQ direction\n");
1492 if (TMUL.sgt(0)) {
1493 TL = maxAPInt(TL, ceilingOfQuotient(X - Y, TMUL));
1494 DEBUG(dbgs() << "\t\t TL = " << TL << "\n");
1495 }
1496 else {
1497 TU = minAPInt(TU, floorOfQuotient(X - Y, TMUL));
1498 DEBUG(dbgs() << "\t\t TU = " << TU << "\n");
1499 }
1500 TMUL = BM - AM;
1501 if (TMUL.sgt(0)) {
1502 TL = maxAPInt(TL, ceilingOfQuotient(Y - X, TMUL));
1503 DEBUG(dbgs() << "\t\t TL = " << TL << "\n");
1504 }
1505 else {
1506 TU = minAPInt(TU, floorOfQuotient(Y - X, TMUL));
1507 DEBUG(dbgs() << "\t\t TU = " << TU << "\n");
1508 }
1509 if (TL.sle(TU)) {
1510 NewDirection |= Dependence::DVEntry::EQ;
1511 ++ExactSIVsuccesses;
1512 }
1513
1514 // greater than
1515 TU = SaveTU; // restore
1516 TL = SaveTL;
1517 DEBUG(dbgs() << "\t exploring GT direction\n");
1518 if (TMUL.sgt(0)) {
1519 TL = maxAPInt(TL, ceilingOfQuotient(Y - X + 1, TMUL));
1520 DEBUG(dbgs() << "\t\t TL = " << TL << "\n");
1521 }
1522 else {
1523 TU = minAPInt(TU, floorOfQuotient(Y - X + 1, TMUL));
1524 DEBUG(dbgs() << "\t\t TU = " << TU << "\n");
1525 }
1526 if (TL.sle(TU)) {
1527 NewDirection |= Dependence::DVEntry::GT;
1528 ++ExactSIVsuccesses;
1529 }
1530
1531 // finished
1532 Result.DV[Level].Direction &= NewDirection;
1533 if (Result.DV[Level].Direction == Dependence::DVEntry::NONE)
1534 ++ExactSIVindependence;
1535 return Result.DV[Level].Direction == Dependence::DVEntry::NONE;
1536}
1537
1538
1539
1540// Return true if the divisor evenly divides the dividend.
1541static
1542bool isRemainderZero(const SCEVConstant *Dividend,
1543 const SCEVConstant *Divisor) {
1544 APInt ConstDividend = Dividend->getValue()->getValue();
1545 APInt ConstDivisor = Divisor->getValue()->getValue();
1546 return ConstDividend.srem(ConstDivisor) == 0;
1547}
1548
1549
1550// weakZeroSrcSIVtest -
1551// From the paper, Practical Dependence Testing, Section 4.2.2
1552//
1553// When we have a pair of subscripts of the form [c1] and [c2 + a*i],
1554// where i is an induction variable, c1 and c2 are loop invariant,
1555// and a is a constant, we can solve it exactly using the
1556// Weak-Zero SIV test.
1557//
1558// Given
1559//
1560// c1 = c2 + a*i
1561//
1562// we get
1563//
1564// (c1 - c2)/a = i
1565//
1566// If i is not an integer, there's no dependence.
1567// If i < 0 or > UB, there's no dependence.
1568// If i = 0, the direction is <= and peeling the
1569// 1st iteration will break the dependence.
1570// If i = UB, the direction is >= and peeling the
1571// last iteration will break the dependence.
1572// Otherwise, the direction is *.
1573//
1574// Can prove independence. Failing that, we can sometimes refine
1575// the directions. Can sometimes show that first or last
1576// iteration carries all the dependences (so worth peeling).
1577//
1578// (see also weakZeroDstSIVtest)
1579//
1580// Return true if dependence disproved.
1581bool DependenceAnalysis::weakZeroSrcSIVtest(const SCEV *DstCoeff,
1582 const SCEV *SrcConst,
1583 const SCEV *DstConst,
1584 const Loop *CurLoop,
1585 unsigned Level,
1586 FullDependence &Result,
1587 Constraint &NewConstraint) const {
1588 // For the WeakSIV test, it's possible the loop isn't common to
1589 // the Src and Dst loops. If it isn't, then there's no need to
1590 // record a direction.
1591 DEBUG(dbgs() << "\tWeak-Zero (src) SIV test\n");
1592 DEBUG(dbgs() << "\t DstCoeff = " << *DstCoeff << "\n");
1593 DEBUG(dbgs() << "\t SrcConst = " << *SrcConst << "\n");
1594 DEBUG(dbgs() << "\t DstConst = " << *DstConst << "\n");
1595 ++WeakZeroSIVapplications;
1596 assert(0 < Level && Level <= MaxLevels && "Level out of range");
1597 Level--;
1598 Result.Consistent = false;
1599 const SCEV *Delta = SE->getMinusSCEV(SrcConst, DstConst);
1600 NewConstraint.setLine(SE->getConstant(Delta->getType(), 0),
1601 DstCoeff, Delta, CurLoop);
1602 DEBUG(dbgs() << "\t Delta = " << *Delta << "\n");
1603 if (isKnownPredicate(CmpInst::ICMP_EQ, SrcConst, DstConst)) {
1604 if (Level < CommonLevels) {
1605 Result.DV[Level].Direction &= Dependence::DVEntry::LE;
1606 Result.DV[Level].PeelFirst = true;
1607 ++WeakZeroSIVsuccesses;
1608 }
1609 return false; // dependences caused by first iteration
1610 }
1611 const SCEVConstant *ConstCoeff = dyn_cast<SCEVConstant>(DstCoeff);
1612 if (!ConstCoeff)
1613 return false;
1614 const SCEV *AbsCoeff =
1615 SE->isKnownNegative(ConstCoeff) ?
1616 SE->getNegativeSCEV(ConstCoeff) : ConstCoeff;
1617 const SCEV *NewDelta =
1618 SE->isKnownNegative(ConstCoeff) ? SE->getNegativeSCEV(Delta) : Delta;
1619
1620 // check that Delta/SrcCoeff < iteration count
1621 // really check NewDelta < count*AbsCoeff
1622 if (const SCEV *UpperBound = collectUpperBound(CurLoop, Delta->getType())) {
1623 DEBUG(dbgs() << "\t UpperBound = " << *UpperBound << "\n");
1624 const SCEV *Product = SE->getMulExpr(AbsCoeff, UpperBound);
1625 if (isKnownPredicate(CmpInst::ICMP_SGT, NewDelta, Product)) {
1626 ++WeakZeroSIVindependence;
1627 ++WeakZeroSIVsuccesses;
1628 return true;
1629 }
1630 if (isKnownPredicate(CmpInst::ICMP_EQ, NewDelta, Product)) {
1631 // dependences caused by last iteration
1632 if (Level < CommonLevels) {
1633 Result.DV[Level].Direction &= Dependence::DVEntry::GE;
1634 Result.DV[Level].PeelLast = true;
1635 ++WeakZeroSIVsuccesses;
1636 }
1637 return false;
1638 }
1639 }
1640
1641 // check that Delta/SrcCoeff >= 0
1642 // really check that NewDelta >= 0
1643 if (SE->isKnownNegative(NewDelta)) {
1644 // No dependence, newDelta < 0
1645 ++WeakZeroSIVindependence;
1646 ++WeakZeroSIVsuccesses;
1647 return true;
1648 }
1649
1650 // if SrcCoeff doesn't divide Delta, then no dependence
1651 if (isa<SCEVConstant>(Delta) &&
1652 !isRemainderZero(cast<SCEVConstant>(Delta), ConstCoeff)) {
1653 ++WeakZeroSIVindependence;
1654 ++WeakZeroSIVsuccesses;
1655 return true;
1656 }
1657 return false;
1658}
1659
1660
1661// weakZeroDstSIVtest -
1662// From the paper, Practical Dependence Testing, Section 4.2.2
1663//
1664// When we have a pair of subscripts of the form [c1 + a*i] and [c2],
1665// where i is an induction variable, c1 and c2 are loop invariant,
1666// and a is a constant, we can solve it exactly using the
1667// Weak-Zero SIV test.
1668//
1669// Given
1670//
1671// c1 + a*i = c2
1672//
1673// we get
1674//
1675// i = (c2 - c1)/a
1676//
1677// If i is not an integer, there's no dependence.
1678// If i < 0 or > UB, there's no dependence.
1679// If i = 0, the direction is <= and peeling the
1680// 1st iteration will break the dependence.
1681// If i = UB, the direction is >= and peeling the
1682// last iteration will break the dependence.
1683// Otherwise, the direction is *.
1684//
1685// Can prove independence. Failing that, we can sometimes refine
1686// the directions. Can sometimes show that first or last
1687// iteration carries all the dependences (so worth peeling).
1688//
1689// (see also weakZeroSrcSIVtest)
1690//
1691// Return true if dependence disproved.
1692bool DependenceAnalysis::weakZeroDstSIVtest(const SCEV *SrcCoeff,
1693 const SCEV *SrcConst,
1694 const SCEV *DstConst,
1695 const Loop *CurLoop,
1696 unsigned Level,
1697 FullDependence &Result,
1698 Constraint &NewConstraint) const {
1699 // For the WeakSIV test, it's possible the loop isn't common to the
1700 // Src and Dst loops. If it isn't, then there's no need to record a direction.
1701 DEBUG(dbgs() << "\tWeak-Zero (dst) SIV test\n");
1702 DEBUG(dbgs() << "\t SrcCoeff = " << *SrcCoeff << "\n");
1703 DEBUG(dbgs() << "\t SrcConst = " << *SrcConst << "\n");
1704 DEBUG(dbgs() << "\t DstConst = " << *DstConst << "\n");
1705 ++WeakZeroSIVapplications;
1706 assert(0 < Level && Level <= SrcLevels && "Level out of range");
1707 Level--;
1708 Result.Consistent = false;
1709 const SCEV *Delta = SE->getMinusSCEV(DstConst, SrcConst);
1710 NewConstraint.setLine(SrcCoeff, SE->getConstant(Delta->getType(), 0),
1711 Delta, CurLoop);
1712 DEBUG(dbgs() << "\t Delta = " << *Delta << "\n");
1713 if (isKnownPredicate(CmpInst::ICMP_EQ, DstConst, SrcConst)) {
1714 if (Level < CommonLevels) {
1715 Result.DV[Level].Direction &= Dependence::DVEntry::LE;
1716 Result.DV[Level].PeelFirst = true;
1717 ++WeakZeroSIVsuccesses;
1718 }
1719 return false; // dependences caused by first iteration
1720 }
1721 const SCEVConstant *ConstCoeff = dyn_cast<SCEVConstant>(SrcCoeff);
1722 if (!ConstCoeff)
1723 return false;
1724 const SCEV *AbsCoeff =
1725 SE->isKnownNegative(ConstCoeff) ?
1726 SE->getNegativeSCEV(ConstCoeff) : ConstCoeff;
1727 const SCEV *NewDelta =
1728 SE->isKnownNegative(ConstCoeff) ? SE->getNegativeSCEV(Delta) : Delta;
1729
1730 // check that Delta/SrcCoeff < iteration count
1731 // really check NewDelta < count*AbsCoeff
1732 if (const SCEV *UpperBound = collectUpperBound(CurLoop, Delta->getType())) {
1733 DEBUG(dbgs() << "\t UpperBound = " << *UpperBound << "\n");
1734 const SCEV *Product = SE->getMulExpr(AbsCoeff, UpperBound);
1735 if (isKnownPredicate(CmpInst::ICMP_SGT, NewDelta, Product)) {
1736 ++WeakZeroSIVindependence;
1737 ++WeakZeroSIVsuccesses;
1738 return true;
1739 }
1740 if (isKnownPredicate(CmpInst::ICMP_EQ, NewDelta, Product)) {
1741 // dependences caused by last iteration
1742 if (Level < CommonLevels) {
1743 Result.DV[Level].Direction &= Dependence::DVEntry::GE;
1744 Result.DV[Level].PeelLast = true;
1745 ++WeakZeroSIVsuccesses;
1746 }
1747 return false;
1748 }
1749 }
1750
1751 // check that Delta/SrcCoeff >= 0
1752 // really check that NewDelta >= 0
1753 if (SE->isKnownNegative(NewDelta)) {
1754 // No dependence, newDelta < 0
1755 ++WeakZeroSIVindependence;
1756 ++WeakZeroSIVsuccesses;
1757 return true;
1758 }
1759
1760 // if SrcCoeff doesn't divide Delta, then no dependence
1761 if (isa<SCEVConstant>(Delta) &&
1762 !isRemainderZero(cast<SCEVConstant>(Delta), ConstCoeff)) {
1763 ++WeakZeroSIVindependence;
1764 ++WeakZeroSIVsuccesses;
1765 return true;
1766 }
1767 return false;
1768}
1769
1770
1771// exactRDIVtest - Tests the RDIV subscript pair for dependence.
1772// Things of the form [c1 + a*i] and [c2 + b*j],
1773// where i and j are induction variable, c1 and c2 are loop invariant,
1774// and a and b are constants.
1775// Returns true if any possible dependence is disproved.
1776// Marks the result as inconsistant.
1777// Works in some cases that symbolicRDIVtest doesn't, and vice versa.
1778bool DependenceAnalysis::exactRDIVtest(const SCEV *SrcCoeff,
1779 const SCEV *DstCoeff,
1780 const SCEV *SrcConst,
1781 const SCEV *DstConst,
1782 const Loop *SrcLoop,
1783 const Loop *DstLoop,
1784 FullDependence &Result) const {
1785 DEBUG(dbgs() << "\tExact RDIV test\n");
1786 DEBUG(dbgs() << "\t SrcCoeff = " << *SrcCoeff << " = AM\n");
1787 DEBUG(dbgs() << "\t DstCoeff = " << *DstCoeff << " = BM\n");
1788 DEBUG(dbgs() << "\t SrcConst = " << *SrcConst << "\n");
1789 DEBUG(dbgs() << "\t DstConst = " << *DstConst << "\n");
1790 ++ExactRDIVapplications;
1791 Result.Consistent = false;
1792 const SCEV *Delta = SE->getMinusSCEV(DstConst, SrcConst);
1793 DEBUG(dbgs() << "\t Delta = " << *Delta << "\n");
1794 const SCEVConstant *ConstDelta = dyn_cast<SCEVConstant>(Delta);
1795 const SCEVConstant *ConstSrcCoeff = dyn_cast<SCEVConstant>(SrcCoeff);
1796 const SCEVConstant *ConstDstCoeff = dyn_cast<SCEVConstant>(DstCoeff);
1797 if (!ConstDelta || !ConstSrcCoeff || !ConstDstCoeff)
1798 return false;
1799
1800 // find gcd
1801 APInt G, X, Y;
1802 APInt AM = ConstSrcCoeff->getValue()->getValue();
1803 APInt BM = ConstDstCoeff->getValue()->getValue();
1804 unsigned Bits = AM.getBitWidth();
1805 if (findGCD(Bits, AM, BM, ConstDelta->getValue()->getValue(), G, X, Y)) {
1806 // gcd doesn't divide Delta, no dependence
1807 ++ExactRDIVindependence;
1808 return true;
1809 }
1810
1811 DEBUG(dbgs() << "\t X = " << X << ", Y = " << Y << "\n");
1812
1813 // since SCEV construction seems to normalize, LM = 0
1814 APInt SrcUM(Bits, 1, true);
1815 bool SrcUMvalid = false;
1816 // SrcUM is perhaps unavailable, let's check
1817 if (const SCEVConstant *UpperBound =
1818 collectConstantUpperBound(SrcLoop, Delta->getType())) {
1819 SrcUM = UpperBound->getValue()->getValue();
1820 DEBUG(dbgs() << "\t SrcUM = " << SrcUM << "\n");
1821 SrcUMvalid = true;
1822 }
1823
1824 APInt DstUM(Bits, 1, true);
1825 bool DstUMvalid = false;
1826 // UM is perhaps unavailable, let's check
1827 if (const SCEVConstant *UpperBound =
1828 collectConstantUpperBound(DstLoop, Delta->getType())) {
1829 DstUM = UpperBound->getValue()->getValue();
1830 DEBUG(dbgs() << "\t DstUM = " << DstUM << "\n");
1831 DstUMvalid = true;
1832 }
1833
1834 APInt TU(APInt::getSignedMaxValue(Bits));
1835 APInt TL(APInt::getSignedMinValue(Bits));
1836
1837 // test(BM/G, LM-X) and test(-BM/G, X-UM)
1838 APInt TMUL = BM.sdiv(G);
1839 if (TMUL.sgt(0)) {
1840 TL = maxAPInt(TL, ceilingOfQuotient(-X, TMUL));
1841 DEBUG(dbgs() << "\t TL = " << TL << "\n");
1842 if (SrcUMvalid) {
1843 TU = minAPInt(TU, floorOfQuotient(SrcUM - X, TMUL));
1844 DEBUG(dbgs() << "\t TU = " << TU << "\n");
1845 }
1846 }
1847 else {
1848 TU = minAPInt(TU, floorOfQuotient(-X, TMUL));
1849 DEBUG(dbgs() << "\t TU = " << TU << "\n");
1850 if (SrcUMvalid) {
1851 TL = maxAPInt(TL, ceilingOfQuotient(SrcUM - X, TMUL));
1852 DEBUG(dbgs() << "\t TL = " << TL << "\n");
1853 }
1854 }
1855
1856 // test(AM/G, LM-Y) and test(-AM/G, Y-UM)
1857 TMUL = AM.sdiv(G);
1858 if (TMUL.sgt(0)) {
1859 TL = maxAPInt(TL, ceilingOfQuotient(-Y, TMUL));
1860 DEBUG(dbgs() << "\t TL = " << TL << "\n");
1861 if (DstUMvalid) {
1862 TU = minAPInt(TU, floorOfQuotient(DstUM - Y, TMUL));
1863 DEBUG(dbgs() << "\t TU = " << TU << "\n");
1864 }
1865 }
1866 else {
1867 TU = minAPInt(TU, floorOfQuotient(-Y, TMUL));
1868 DEBUG(dbgs() << "\t TU = " << TU << "\n");
1869 if (DstUMvalid) {
1870 TL = maxAPInt(TL, ceilingOfQuotient(DstUM - Y, TMUL));
1871 DEBUG(dbgs() << "\t TL = " << TL << "\n");
1872 }
1873 }
1874 if (TL.sgt(TU))
1875 ++ExactRDIVindependence;
1876 return TL.sgt(TU);
1877}
1878
1879
1880// symbolicRDIVtest -
1881// In Section 4.5 of the Practical Dependence Testing paper,the authors
1882// introduce a special case of Banerjee's Inequalities (also called the
1883// Extreme-Value Test) that can handle some of the SIV and RDIV cases,
1884// particularly cases with symbolics. Since it's only able to disprove
1885// dependence (not compute distances or directions), we'll use it as a
1886// fall back for the other tests.
1887//
1888// When we have a pair of subscripts of the form [c1 + a1*i] and [c2 + a2*j]
1889// where i and j are induction variables and c1 and c2 are loop invariants,
1890// we can use the symbolic tests to disprove some dependences, serving as a
1891// backup for the RDIV test. Note that i and j can be the same variable,
1892// letting this test serve as a backup for the various SIV tests.
1893//
1894// For a dependence to exist, c1 + a1*i must equal c2 + a2*j for some
1895// 0 <= i <= N1 and some 0 <= j <= N2, where N1 and N2 are the (normalized)
1896// loop bounds for the i and j loops, respectively. So, ...
1897//
1898// c1 + a1*i = c2 + a2*j
1899// a1*i - a2*j = c2 - c1
1900//
1901// To test for a dependence, we compute c2 - c1 and make sure it's in the
1902// range of the maximum and minimum possible values of a1*i - a2*j.
1903// Considering the signs of a1 and a2, we have 4 possible cases:
1904//
1905// 1) If a1 >= 0 and a2 >= 0, then
1906// a1*0 - a2*N2 <= c2 - c1 <= a1*N1 - a2*0
1907// -a2*N2 <= c2 - c1 <= a1*N1
1908//
1909// 2) If a1 >= 0 and a2 <= 0, then
1910// a1*0 - a2*0 <= c2 - c1 <= a1*N1 - a2*N2
1911// 0 <= c2 - c1 <= a1*N1 - a2*N2
1912//
1913// 3) If a1 <= 0 and a2 >= 0, then
1914// a1*N1 - a2*N2 <= c2 - c1 <= a1*0 - a2*0
1915// a1*N1 - a2*N2 <= c2 - c1 <= 0
1916//
1917// 4) If a1 <= 0 and a2 <= 0, then
1918// a1*N1 - a2*0 <= c2 - c1 <= a1*0 - a2*N2
1919// a1*N1 <= c2 - c1 <= -a2*N2
1920//
1921// return true if dependence disproved
1922bool DependenceAnalysis::symbolicRDIVtest(const SCEV *A1,
1923 const SCEV *A2,
1924 const SCEV *C1,
1925 const SCEV *C2,
1926 const Loop *Loop1,
1927 const Loop *Loop2) const {
1928 ++SymbolicRDIVapplications;
1929 DEBUG(dbgs() << "\ttry symbolic RDIV test\n");
1930 DEBUG(dbgs() << "\t A1 = " << *A1);
1931 DEBUG(dbgs() << ", type = " << *A1->getType() << "\n");
1932 DEBUG(dbgs() << "\t A2 = " << *A2 << "\n");
1933 DEBUG(dbgs() << "\t C1 = " << *C1 << "\n");
1934 DEBUG(dbgs() << "\t C2 = " << *C2 << "\n");
1935 const SCEV *N1 = collectUpperBound(Loop1, A1->getType());
1936 const SCEV *N2 = collectUpperBound(Loop2, A1->getType());
1937 DEBUG(if (N1) dbgs() << "\t N1 = " << *N1 << "\n");
1938 DEBUG(if (N2) dbgs() << "\t N2 = " << *N2 << "\n");
1939 const SCEV *C2_C1 = SE->getMinusSCEV(C2, C1);
1940 const SCEV *C1_C2 = SE->getMinusSCEV(C1, C2);
1941 DEBUG(dbgs() << "\t C2 - C1 = " << *C2_C1 << "\n");
1942 DEBUG(dbgs() << "\t C1 - C2 = " << *C1_C2 << "\n");
1943 if (SE->isKnownNonNegative(A1)) {
1944 if (SE->isKnownNonNegative(A2)) {
1945 // A1 >= 0 && A2 >= 0
1946 if (N1) {
1947 // make sure that c2 - c1 <= a1*N1
1948 const SCEV *A1N1 = SE->getMulExpr(A1, N1);
1949 DEBUG(dbgs() << "\t A1*N1 = " << *A1N1 << "\n");
1950 if (isKnownPredicate(CmpInst::ICMP_SGT, C2_C1, A1N1)) {
1951 ++SymbolicRDIVindependence;
1952 return true;
1953 }
1954 }
1955 if (N2) {
1956 // make sure that -a2*N2 <= c2 - c1, or a2*N2 >= c1 - c2
1957 const SCEV *A2N2 = SE->getMulExpr(A2, N2);
1958 DEBUG(dbgs() << "\t A2*N2 = " << *A2N2 << "\n");
1959 if (isKnownPredicate(CmpInst::ICMP_SLT, A2N2, C1_C2)) {
1960 ++SymbolicRDIVindependence;
1961 return true;
1962 }
1963 }
1964 }
1965 else if (SE->isKnownNonPositive(A2)) {
1966 // a1 >= 0 && a2 <= 0
1967 if (N1 && N2) {
1968 // make sure that c2 - c1 <= a1*N1 - a2*N2
1969 const SCEV *A1N1 = SE->getMulExpr(A1, N1);
1970 const SCEV *A2N2 = SE->getMulExpr(A2, N2);
1971 const SCEV *A1N1_A2N2 = SE->getMinusSCEV(A1N1, A2N2);
1972 DEBUG(dbgs() << "\t A1*N1 - A2*N2 = " << *A1N1_A2N2 << "\n");
1973 if (isKnownPredicate(CmpInst::ICMP_SGT, C2_C1, A1N1_A2N2)) {
1974 ++SymbolicRDIVindependence;
1975 return true;
1976 }
1977 }
1978 // make sure that 0 <= c2 - c1
1979 if (SE->isKnownNegative(C2_C1)) {
1980 ++SymbolicRDIVindependence;
1981 return true;
1982 }
1983 }
1984 }
1985 else if (SE->isKnownNonPositive(A1)) {
1986 if (SE->isKnownNonNegative(A2)) {
1987 // a1 <= 0 && a2 >= 0
1988 if (N1 && N2) {
1989 // make sure that a1*N1 - a2*N2 <= c2 - c1
1990 const SCEV *A1N1 = SE->getMulExpr(A1, N1);
1991 const SCEV *A2N2 = SE->getMulExpr(A2, N2);
1992 const SCEV *A1N1_A2N2 = SE->getMinusSCEV(A1N1, A2N2);
1993 DEBUG(dbgs() << "\t A1*N1 - A2*N2 = " << *A1N1_A2N2 << "\n");
1994 if (isKnownPredicate(CmpInst::ICMP_SGT, A1N1_A2N2, C2_C1)) {
1995 ++SymbolicRDIVindependence;
1996 return true;
1997 }
1998 }
1999 // make sure that c2 - c1 <= 0
2000 if (SE->isKnownPositive(C2_C1)) {
2001 ++SymbolicRDIVindependence;
2002 return true;
2003 }
2004 }
2005 else if (SE->isKnownNonPositive(A2)) {
2006 // a1 <= 0 && a2 <= 0
2007 if (N1) {
2008 // make sure that a1*N1 <= c2 - c1
2009 const SCEV *A1N1 = SE->getMulExpr(A1, N1);
2010 DEBUG(dbgs() << "\t A1*N1 = " << *A1N1 << "\n");
2011 if (isKnownPredicate(CmpInst::ICMP_SGT, A1N1, C2_C1)) {
2012 ++SymbolicRDIVindependence;
2013 return true;
2014 }
2015 }
2016 if (N2) {
2017 // make sure that c2 - c1 <= -a2*N2, or c1 - c2 >= a2*N2
2018 const SCEV *A2N2 = SE->getMulExpr(A2, N2);
2019 DEBUG(dbgs() << "\t A2*N2 = " << *A2N2 << "\n");
2020 if (isKnownPredicate(CmpInst::ICMP_SLT, C1_C2, A2N2)) {
2021 ++SymbolicRDIVindependence;
2022 return true;
2023 }
2024 }
2025 }
2026 }
2027 return false;
2028}
2029
2030
2031// testSIV -
2032// When we have a pair of subscripts of the form [c1 + a1*i] and [c2 - a2*i]
2033// where i is an induction variable, c1 and c2 are loop invariant, and a1 and
2034// a2 are constant, we attack it with an SIV test. While they can all be
2035// solved with the Exact SIV test, it's worthwhile to use simpler tests when
2036// they apply; they're cheaper and sometimes more precise.
2037//
2038// Return true if dependence disproved.
2039bool DependenceAnalysis::testSIV(const SCEV *Src,
2040 const SCEV *Dst,
2041 unsigned &Level,
2042 FullDependence &Result,
2043 Constraint &NewConstraint,
2044 const SCEV *&SplitIter) const {
2045 DEBUG(dbgs() << " src = " << *Src << "\n");
2046 DEBUG(dbgs() << " dst = " << *Dst << "\n");
2047 const SCEVAddRecExpr *SrcAddRec = dyn_cast<SCEVAddRecExpr>(Src);
2048 const SCEVAddRecExpr *DstAddRec = dyn_cast<SCEVAddRecExpr>(Dst);
2049 if (SrcAddRec && DstAddRec) {
2050 const SCEV *SrcConst = SrcAddRec->getStart();
2051 const SCEV *DstConst = DstAddRec->getStart();
2052 const SCEV *SrcCoeff = SrcAddRec->getStepRecurrence(*SE);
2053 const SCEV *DstCoeff = DstAddRec->getStepRecurrence(*SE);
2054 const Loop *CurLoop = SrcAddRec->getLoop();
2055 assert(CurLoop == DstAddRec->getLoop() &&
2056 "both loops in SIV should be same");
2057 Level = mapSrcLoop(CurLoop);
2058 bool disproven;
2059 if (SrcCoeff == DstCoeff)
2060 disproven = strongSIVtest(SrcCoeff, SrcConst, DstConst, CurLoop,
2061 Level, Result, NewConstraint);
2062 else if (SrcCoeff == SE->getNegativeSCEV(DstCoeff))
2063 disproven = weakCrossingSIVtest(SrcCoeff, SrcConst, DstConst, CurLoop,
2064 Level, Result, NewConstraint, SplitIter);
2065 else
2066 disproven = exactSIVtest(SrcCoeff, DstCoeff, SrcConst, DstConst, CurLoop,
2067 Level, Result, NewConstraint);
2068 return disproven ||
2069 gcdMIVtest(Src, Dst, Result) ||
2070 symbolicRDIVtest(SrcCoeff, DstCoeff, SrcConst, DstConst, CurLoop, CurLoop);
2071 }
2072 if (SrcAddRec) {
2073 const SCEV *SrcConst = SrcAddRec->getStart();
2074 const SCEV *SrcCoeff = SrcAddRec->getStepRecurrence(*SE);
2075 const SCEV *DstConst = Dst;
2076 const Loop *CurLoop = SrcAddRec->getLoop();
2077 Level = mapSrcLoop(CurLoop);
2078 return weakZeroDstSIVtest(SrcCoeff, SrcConst, DstConst, CurLoop,
2079 Level, Result, NewConstraint) ||
2080 gcdMIVtest(Src, Dst, Result);
2081 }
2082 if (DstAddRec) {
2083 const SCEV *DstConst = DstAddRec->getStart();
2084 const SCEV *DstCoeff = DstAddRec->getStepRecurrence(*SE);
2085 const SCEV *SrcConst = Src;
2086 const Loop *CurLoop = DstAddRec->getLoop();
2087 Level = mapDstLoop(CurLoop);
2088 return weakZeroSrcSIVtest(DstCoeff, SrcConst, DstConst,
2089 CurLoop, Level, Result, NewConstraint) ||
2090 gcdMIVtest(Src, Dst, Result);
2091 }
2092 llvm_unreachable("SIV test expected at least one AddRec");
2093 return false;
2094}
2095
2096
2097// testRDIV -
2098// When we have a pair of subscripts of the form [c1 + a1*i] and [c2 + a2*j]
2099// where i and j are induction variables, c1 and c2 are loop invariant,
2100// and a1 and a2 are constant, we can solve it exactly with an easy adaptation
2101// of the Exact SIV test, the Restricted Double Index Variable (RDIV) test.
2102// It doesn't make sense to talk about distance or direction in this case,
2103// so there's no point in making special versions of the Strong SIV test or
2104// the Weak-crossing SIV test.
2105//
2106// With minor algebra, this test can also be used for things like
2107// [c1 + a1*i + a2*j][c2].
2108//
2109// Return true if dependence disproved.
2110bool DependenceAnalysis::testRDIV(const SCEV *Src,
2111 const SCEV *Dst,
2112 FullDependence &Result) const {
2113 // we have 3 possible situations here:
2114 // 1) [a*i + b] and [c*j + d]
2115 // 2) [a*i + c*j + b] and [d]
2116 // 3) [b] and [a*i + c*j + d]
2117 // We need to find what we've got and get organized
2118
2119 const SCEV *SrcConst, *DstConst;
2120 const SCEV *SrcCoeff, *DstCoeff;
2121 const Loop *SrcLoop, *DstLoop;
2122
2123 DEBUG(dbgs() << " src = " << *Src << "\n");
2124 DEBUG(dbgs() << " dst = " << *Dst << "\n");
2125 const SCEVAddRecExpr *SrcAddRec = dyn_cast<SCEVAddRecExpr>(Src);
2126 const SCEVAddRecExpr *DstAddRec = dyn_cast<SCEVAddRecExpr>(Dst);
2127 if (SrcAddRec && DstAddRec) {
2128 SrcConst = SrcAddRec->getStart();
2129 SrcCoeff = SrcAddRec->getStepRecurrence(*SE);
2130 SrcLoop = SrcAddRec->getLoop();
2131 DstConst = DstAddRec->getStart();
2132 DstCoeff = DstAddRec->getStepRecurrence(*SE);
2133 DstLoop = DstAddRec->getLoop();
2134 }
2135 else if (SrcAddRec) {
2136 if (const SCEVAddRecExpr *tmpAddRec =
2137 dyn_cast<SCEVAddRecExpr>(SrcAddRec->getStart())) {
2138 SrcConst = tmpAddRec->getStart();
2139 SrcCoeff = tmpAddRec->getStepRecurrence(*SE);
2140 SrcLoop = tmpAddRec->getLoop();
2141 DstConst = Dst;
2142 DstCoeff = SE->getNegativeSCEV(SrcAddRec->getStepRecurrence(*SE));
2143 DstLoop = SrcAddRec->getLoop();
2144 }
2145 else
2146 llvm_unreachable("RDIV reached by surprising SCEVs");
2147 }
2148 else if (DstAddRec) {
2149 if (const SCEVAddRecExpr *tmpAddRec =
2150 dyn_cast<SCEVAddRecExpr>(DstAddRec->getStart())) {
2151 DstConst = tmpAddRec->getStart();
2152 DstCoeff = tmpAddRec->getStepRecurrence(*SE);
2153 DstLoop = tmpAddRec->getLoop();
2154 SrcConst = Src;
2155 SrcCoeff = SE->getNegativeSCEV(DstAddRec->getStepRecurrence(*SE));
2156 SrcLoop = DstAddRec->getLoop();
2157 }
2158 else
2159 llvm_unreachable("RDIV reached by surprising SCEVs");
2160 }
2161 else
2162 llvm_unreachable("RDIV expected at least one AddRec");
2163 return exactRDIVtest(SrcCoeff, DstCoeff,
2164 SrcConst, DstConst,
2165 SrcLoop, DstLoop,
2166 Result) ||
2167 gcdMIVtest(Src, Dst, Result) ||
2168 symbolicRDIVtest(SrcCoeff, DstCoeff,
2169 SrcConst, DstConst,
2170 SrcLoop, DstLoop);
2171}
2172
2173
2174// Tests the single-subscript MIV pair (Src and Dst) for dependence.
2175// Return true if dependence disproved.
2176// Can sometimes refine direction vectors.
2177bool DependenceAnalysis::testMIV(const SCEV *Src,
2178 const SCEV *Dst,
2179 const SmallBitVector &Loops,
2180 FullDependence &Result) const {
2181 DEBUG(dbgs() << " src = " << *Src << "\n");
2182 DEBUG(dbgs() << " dst = " << *Dst << "\n");
2183 Result.Consistent = false;
2184 return gcdMIVtest(Src, Dst, Result) ||
2185 banerjeeMIVtest(Src, Dst, Loops, Result);
2186}
2187
2188
2189// Given a product, e.g., 10*X*Y, returns the first constant operand,
2190// in this case 10. If there is no constant part, returns NULL.
2191static
2192const SCEVConstant *getConstantPart(const SCEVMulExpr *Product) {
2193 for (unsigned Op = 0, Ops = Product->getNumOperands(); Op < Ops; Op++) {
2194 if (const SCEVConstant *Constant = dyn_cast<SCEVConstant>(Product->getOperand(Op)))
2195 return Constant;
2196 }
2197 return NULL;
2198}
2199
2200
2201//===----------------------------------------------------------------------===//
2202// gcdMIVtest -
2203// Tests an MIV subscript pair for dependence.
2204// Returns true if any possible dependence is disproved.
2205// Marks the result as inconsistant.
2206// Can sometimes disprove the equal direction for 1 or more loops,
2207// as discussed in Michael Wolfe's book,
2208// High Performance Compilers for Parallel Computing, page 235.
2209//
2210// We spend some effort (code!) to handle cases like
2211// [10*i + 5*N*j + 15*M + 6], where i and j are induction variables,
2212// but M and N are just loop-invariant variables.
2213// This should help us handle linearized subscripts;
2214// also makes this test a useful backup to the various SIV tests.
2215//
2216// It occurs to me that the presence of loop-invariant variables
2217// changes the nature of the test from "greatest common divisor"
2218// to "a common divisor!"
2219bool DependenceAnalysis::gcdMIVtest(const SCEV *Src,
2220 const SCEV *Dst,
2221 FullDependence &Result) const {
2222 DEBUG(dbgs() << "starting gcd\n");
2223 ++GCDapplications;
2224 unsigned BitWidth = Src->getType()->getIntegerBitWidth();
2225 APInt RunningGCD = APInt::getNullValue(BitWidth);
2226
2227 // Examine Src coefficients.
2228 // Compute running GCD and record source constant.
2229 // Because we're looking for the constant at the end of the chain,
2230 // we can't quit the loop just because the GCD == 1.
2231 const SCEV *Coefficients = Src;
2232 while (const SCEVAddRecExpr *AddRec =
2233 dyn_cast<SCEVAddRecExpr>(Coefficients)) {
2234 const SCEV *Coeff = AddRec->getStepRecurrence(*SE);
2235 const SCEVConstant *Constant = dyn_cast<SCEVConstant>(Coeff);
2236 if (const SCEVMulExpr *Product = dyn_cast<SCEVMulExpr>(Coeff))
2237 // If the coefficient is the product of a constant and other stuff,
2238 // we can use the constant in the GCD computation.
2239 Constant = getConstantPart(Product);
2240 if (!Constant)
2241 return false;
2242 APInt ConstCoeff = Constant->getValue()->getValue();
2243 RunningGCD = APIntOps::GreatestCommonDivisor(RunningGCD, ConstCoeff.abs());
2244 Coefficients = AddRec->getStart();
2245 }
2246 const SCEV *SrcConst = Coefficients;
2247
2248 // Examine Dst coefficients.
2249 // Compute running GCD and record destination constant.
2250 // Because we're looking for the constant at the end of the chain,
2251 // we can't quit the loop just because the GCD == 1.
2252 Coefficients = Dst;
2253 while (const SCEVAddRecExpr *AddRec =
2254 dyn_cast<SCEVAddRecExpr>(Coefficients)) {
2255 const SCEV *Coeff = AddRec->getStepRecurrence(*SE);
2256 const SCEVConstant *Constant = dyn_cast<SCEVConstant>(Coeff);
2257 if (const SCEVMulExpr *Product = dyn_cast<SCEVMulExpr>(Coeff))
2258 // If the coefficient is the product of a constant and other stuff,
2259 // we can use the constant in the GCD computation.
2260 Constant = getConstantPart(Product);
2261 if (!Constant)
2262 return false;
2263 APInt ConstCoeff = Constant->getValue()->getValue();
2264 RunningGCD = APIntOps::GreatestCommonDivisor(RunningGCD, ConstCoeff.abs());
2265 Coefficients = AddRec->getStart();
2266 }
2267 const SCEV *DstConst = Coefficients;
2268
2269 APInt ExtraGCD = APInt::getNullValue(BitWidth);
2270 const SCEV *Delta = SE->getMinusSCEV(DstConst, SrcConst);
2271 DEBUG(dbgs() << " Delta = " << *Delta << "\n");
2272 const SCEVConstant *Constant = dyn_cast<SCEVConstant>(Delta);
2273 if (const SCEVAddExpr *Sum = dyn_cast<SCEVAddExpr>(Delta)) {
2274 // If Delta is a sum of products, we may be able to make further progress.
2275 for (unsigned Op = 0, Ops = Sum->getNumOperands(); Op < Ops; Op++) {
2276 const SCEV *Operand = Sum->getOperand(Op);
2277 if (isa<SCEVConstant>(Operand)) {
2278 assert(!Constant && "Surprised to find multiple constants");
2279 Constant = cast<SCEVConstant>(Operand);
2280 }
Benjamin Kramer061938b2012-10-31 09:20:38 +00002281 else if (const SCEVMulExpr *Product = dyn_cast<SCEVMulExpr>(Operand)) {
Sebastian Popad434992012-10-11 07:32:34 +00002282 // Search for constant operand to participate in GCD;
2283 // If none found; return false.
Benjamin Kramer061938b2012-10-31 09:20:38 +00002284 const SCEVConstant *ConstOp = getConstantPart(Product);
2285 if (!ConstOp)
2286 return false;
Sebastian Popad434992012-10-11 07:32:34 +00002287 APInt ConstOpValue = ConstOp->getValue()->getValue();
2288 ExtraGCD = APIntOps::GreatestCommonDivisor(ExtraGCD,
2289 ConstOpValue.abs());
2290 }
2291 else
2292 return false;
2293 }
2294 }
2295 if (!Constant)
2296 return false;
2297 APInt ConstDelta = cast<SCEVConstant>(Constant)->getValue()->getValue();
2298 DEBUG(dbgs() << " ConstDelta = " << ConstDelta << "\n");
2299 if (ConstDelta == 0)
2300 return false;
2301 RunningGCD = APIntOps::GreatestCommonDivisor(RunningGCD, ExtraGCD);
2302 DEBUG(dbgs() << " RunningGCD = " << RunningGCD << "\n");
2303 APInt Remainder = ConstDelta.srem(RunningGCD);
2304 if (Remainder != 0) {
2305 ++GCDindependence;
2306 return true;
2307 }
2308
2309 // Try to disprove equal directions.
2310 // For example, given a subscript pair [3*i + 2*j] and [i' + 2*j' - 1],
2311 // the code above can't disprove the dependence because the GCD = 1.
2312 // So we consider what happen if i = i' and what happens if j = j'.
2313 // If i = i', we can simplify the subscript to [2*i + 2*j] and [2*j' - 1],
2314 // which is infeasible, so we can disallow the = direction for the i level.
2315 // Setting j = j' doesn't help matters, so we end up with a direction vector
2316 // of [<>, *]
2317 //
2318 // Given A[5*i + 10*j*M + 9*M*N] and A[15*i + 20*j*M - 21*N*M + 5],
2319 // we need to remember that the constant part is 5 and the RunningGCD should
2320 // be initialized to ExtraGCD = 30.
2321 DEBUG(dbgs() << " ExtraGCD = " << ExtraGCD << '\n');
2322
2323 bool Improved = false;
2324 Coefficients = Src;
2325 while (const SCEVAddRecExpr *AddRec =
2326 dyn_cast<SCEVAddRecExpr>(Coefficients)) {
2327 Coefficients = AddRec->getStart();
2328 const Loop *CurLoop = AddRec->getLoop();
2329 RunningGCD = ExtraGCD;
2330 const SCEV *SrcCoeff = AddRec->getStepRecurrence(*SE);
2331 const SCEV *DstCoeff = SE->getMinusSCEV(SrcCoeff, SrcCoeff);
2332 const SCEV *Inner = Src;
2333 while (RunningGCD != 1 && isa<SCEVAddRecExpr>(Inner)) {
2334 AddRec = cast<SCEVAddRecExpr>(Inner);
2335 const SCEV *Coeff = AddRec->getStepRecurrence(*SE);
2336 if (CurLoop == AddRec->getLoop())
2337 ; // SrcCoeff == Coeff
2338 else {
2339 if (const SCEVMulExpr *Product = dyn_cast<SCEVMulExpr>(Coeff))
2340 // If the coefficient is the product of a constant and other stuff,
2341 // we can use the constant in the GCD computation.
2342 Constant = getConstantPart(Product);
2343 else
2344 Constant = cast<SCEVConstant>(Coeff);
2345 APInt ConstCoeff = Constant->getValue()->getValue();
2346 RunningGCD = APIntOps::GreatestCommonDivisor(RunningGCD, ConstCoeff.abs());
2347 }
2348 Inner = AddRec->getStart();
2349 }
2350 Inner = Dst;
2351 while (RunningGCD != 1 && isa<SCEVAddRecExpr>(Inner)) {
2352 AddRec = cast<SCEVAddRecExpr>(Inner);
2353 const SCEV *Coeff = AddRec->getStepRecurrence(*SE);
2354 if (CurLoop == AddRec->getLoop())
2355 DstCoeff = Coeff;
2356 else {
2357 if (const SCEVMulExpr *Product = dyn_cast<SCEVMulExpr>(Coeff))
2358 // If the coefficient is the product of a constant and other stuff,
2359 // we can use the constant in the GCD computation.
2360 Constant = getConstantPart(Product);
2361 else
2362 Constant = cast<SCEVConstant>(Coeff);
2363 APInt ConstCoeff = Constant->getValue()->getValue();
2364 RunningGCD = APIntOps::GreatestCommonDivisor(RunningGCD, ConstCoeff.abs());
2365 }
2366 Inner = AddRec->getStart();
2367 }
2368 Delta = SE->getMinusSCEV(SrcCoeff, DstCoeff);
2369 if (const SCEVMulExpr *Product = dyn_cast<SCEVMulExpr>(Delta))
2370 // If the coefficient is the product of a constant and other stuff,
2371 // we can use the constant in the GCD computation.
2372 Constant = getConstantPart(Product);
2373 else if (isa<SCEVConstant>(Delta))
2374 Constant = cast<SCEVConstant>(Delta);
2375 else {
2376 // The difference of the two coefficients might not be a product
2377 // or constant, in which case we give up on this direction.
2378 continue;
2379 }
2380 APInt ConstCoeff = Constant->getValue()->getValue();
2381 RunningGCD = APIntOps::GreatestCommonDivisor(RunningGCD, ConstCoeff.abs());
2382 DEBUG(dbgs() << "\tRunningGCD = " << RunningGCD << "\n");
2383 if (RunningGCD != 0) {
2384 Remainder = ConstDelta.srem(RunningGCD);
2385 DEBUG(dbgs() << "\tRemainder = " << Remainder << "\n");
2386 if (Remainder != 0) {
2387 unsigned Level = mapSrcLoop(CurLoop);
Sebastian Popb4164282012-10-12 02:04:32 +00002388 Result.DV[Level - 1].Direction &= unsigned(~Dependence::DVEntry::EQ);
Sebastian Popad434992012-10-11 07:32:34 +00002389 Improved = true;
2390 }
2391 }
2392 }
2393 if (Improved)
2394 ++GCDsuccesses;
2395 DEBUG(dbgs() << "all done\n");
2396 return false;
2397}
2398
2399
2400//===----------------------------------------------------------------------===//
2401// banerjeeMIVtest -
2402// Use Banerjee's Inequalities to test an MIV subscript pair.
2403// (Wolfe, in the race-car book, calls this the Extreme Value Test.)
2404// Generally follows the discussion in Section 2.5.2 of
2405//
2406// Optimizing Supercompilers for Supercomputers
2407// Michael Wolfe
2408//
2409// The inequalities given on page 25 are simplified in that loops are
2410// normalized so that the lower bound is always 0 and the stride is always 1.
2411// For example, Wolfe gives
2412//
2413// LB^<_k = (A^-_k - B_k)^- (U_k - L_k - N_k) + (A_k - B_k)L_k - B_k N_k
2414//
2415// where A_k is the coefficient of the kth index in the source subscript,
2416// B_k is the coefficient of the kth index in the destination subscript,
2417// U_k is the upper bound of the kth index, L_k is the lower bound of the Kth
2418// index, and N_k is the stride of the kth index. Since all loops are normalized
2419// by the SCEV package, N_k = 1 and L_k = 0, allowing us to simplify the
2420// equation to
2421//
2422// LB^<_k = (A^-_k - B_k)^- (U_k - 0 - 1) + (A_k - B_k)0 - B_k 1
2423// = (A^-_k - B_k)^- (U_k - 1) - B_k
2424//
2425// Similar simplifications are possible for the other equations.
2426//
2427// When we can't determine the number of iterations for a loop,
2428// we use NULL as an indicator for the worst case, infinity.
2429// When computing the upper bound, NULL denotes +inf;
2430// for the lower bound, NULL denotes -inf.
2431//
2432// Return true if dependence disproved.
2433bool DependenceAnalysis::banerjeeMIVtest(const SCEV *Src,
2434 const SCEV *Dst,
2435 const SmallBitVector &Loops,
2436 FullDependence &Result) const {
2437 DEBUG(dbgs() << "starting Banerjee\n");
2438 ++BanerjeeApplications;
2439 DEBUG(dbgs() << " Src = " << *Src << '\n');
2440 const SCEV *A0;
2441 CoefficientInfo *A = collectCoeffInfo(Src, true, A0);
2442 DEBUG(dbgs() << " Dst = " << *Dst << '\n');
2443 const SCEV *B0;
2444 CoefficientInfo *B = collectCoeffInfo(Dst, false, B0);
2445 BoundInfo *Bound = new BoundInfo[MaxLevels + 1];
2446 const SCEV *Delta = SE->getMinusSCEV(B0, A0);
2447 DEBUG(dbgs() << "\tDelta = " << *Delta << '\n');
2448
2449 // Compute bounds for all the * directions.
2450 DEBUG(dbgs() << "\tBounds[*]\n");
2451 for (unsigned K = 1; K <= MaxLevels; ++K) {
2452 Bound[K].Iterations = A[K].Iterations ? A[K].Iterations : B[K].Iterations;
2453 Bound[K].Direction = Dependence::DVEntry::ALL;
2454 Bound[K].DirSet = Dependence::DVEntry::NONE;
2455 findBoundsALL(A, B, Bound, K);
2456#ifndef NDEBUG
2457 DEBUG(dbgs() << "\t " << K << '\t');
2458 if (Bound[K].Lower[Dependence::DVEntry::ALL])
2459 DEBUG(dbgs() << *Bound[K].Lower[Dependence::DVEntry::ALL] << '\t');
2460 else
2461 DEBUG(dbgs() << "-inf\t");
2462 if (Bound[K].Upper[Dependence::DVEntry::ALL])
2463 DEBUG(dbgs() << *Bound[K].Upper[Dependence::DVEntry::ALL] << '\n');
2464 else
2465 DEBUG(dbgs() << "+inf\n");
2466#endif
2467 }
2468
2469 // Test the *, *, *, ... case.
2470 bool Disproved = false;
2471 if (testBounds(Dependence::DVEntry::ALL, 0, Bound, Delta)) {
2472 // Explore the direction vector hierarchy.
2473 unsigned DepthExpanded = 0;
2474 unsigned NewDeps = exploreDirections(1, A, B, Bound,
2475 Loops, DepthExpanded, Delta);
2476 if (NewDeps > 0) {
2477 bool Improved = false;
2478 for (unsigned K = 1; K <= CommonLevels; ++K) {
2479 if (Loops[K]) {
2480 unsigned Old = Result.DV[K - 1].Direction;
2481 Result.DV[K - 1].Direction = Old & Bound[K].DirSet;
2482 Improved |= Old != Result.DV[K - 1].Direction;
2483 if (!Result.DV[K - 1].Direction) {
2484 Improved = false;
2485 Disproved = true;
2486 break;
2487 }
2488 }
2489 }
2490 if (Improved)
2491 ++BanerjeeSuccesses;
2492 }
2493 else {
2494 ++BanerjeeIndependence;
2495 Disproved = true;
2496 }
2497 }
2498 else {
2499 ++BanerjeeIndependence;
2500 Disproved = true;
2501 }
2502 delete [] Bound;
2503 delete [] A;
2504 delete [] B;
2505 return Disproved;
2506}
2507
2508
2509// Hierarchically expands the direction vector
2510// search space, combining the directions of discovered dependences
2511// in the DirSet field of Bound. Returns the number of distinct
2512// dependences discovered. If the dependence is disproved,
2513// it will return 0.
2514unsigned DependenceAnalysis::exploreDirections(unsigned Level,
2515 CoefficientInfo *A,
2516 CoefficientInfo *B,
2517 BoundInfo *Bound,
2518 const SmallBitVector &Loops,
2519 unsigned &DepthExpanded,
2520 const SCEV *Delta) const {
2521 if (Level > CommonLevels) {
2522 // record result
2523 DEBUG(dbgs() << "\t[");
2524 for (unsigned K = 1; K <= CommonLevels; ++K) {
2525 if (Loops[K]) {
2526 Bound[K].DirSet |= Bound[K].Direction;
2527#ifndef NDEBUG
2528 switch (Bound[K].Direction) {
2529 case Dependence::DVEntry::LT:
2530 DEBUG(dbgs() << " <");
2531 break;
2532 case Dependence::DVEntry::EQ:
2533 DEBUG(dbgs() << " =");
2534 break;
2535 case Dependence::DVEntry::GT:
2536 DEBUG(dbgs() << " >");
2537 break;
2538 case Dependence::DVEntry::ALL:
2539 DEBUG(dbgs() << " *");
2540 break;
2541 default:
2542 llvm_unreachable("unexpected Bound[K].Direction");
2543 }
2544#endif
2545 }
2546 }
2547 DEBUG(dbgs() << " ]\n");
2548 return 1;
2549 }
2550 if (Loops[Level]) {
2551 if (Level > DepthExpanded) {
2552 DepthExpanded = Level;
2553 // compute bounds for <, =, > at current level
2554 findBoundsLT(A, B, Bound, Level);
2555 findBoundsGT(A, B, Bound, Level);
2556 findBoundsEQ(A, B, Bound, Level);
2557#ifndef NDEBUG
2558 DEBUG(dbgs() << "\tBound for level = " << Level << '\n');
2559 DEBUG(dbgs() << "\t <\t");
2560 if (Bound[Level].Lower[Dependence::DVEntry::LT])
2561 DEBUG(dbgs() << *Bound[Level].Lower[Dependence::DVEntry::LT] << '\t');
2562 else
2563 DEBUG(dbgs() << "-inf\t");
2564 if (Bound[Level].Upper[Dependence::DVEntry::LT])
2565 DEBUG(dbgs() << *Bound[Level].Upper[Dependence::DVEntry::LT] << '\n');
2566 else
2567 DEBUG(dbgs() << "+inf\n");
2568 DEBUG(dbgs() << "\t =\t");
2569 if (Bound[Level].Lower[Dependence::DVEntry::EQ])
2570 DEBUG(dbgs() << *Bound[Level].Lower[Dependence::DVEntry::EQ] << '\t');
2571 else
2572 DEBUG(dbgs() << "-inf\t");
2573 if (Bound[Level].Upper[Dependence::DVEntry::EQ])
2574 DEBUG(dbgs() << *Bound[Level].Upper[Dependence::DVEntry::EQ] << '\n');
2575 else
2576 DEBUG(dbgs() << "+inf\n");
2577 DEBUG(dbgs() << "\t >\t");
2578 if (Bound[Level].Lower[Dependence::DVEntry::GT])
2579 DEBUG(dbgs() << *Bound[Level].Lower[Dependence::DVEntry::GT] << '\t');
2580 else
2581 DEBUG(dbgs() << "-inf\t");
2582 if (Bound[Level].Upper[Dependence::DVEntry::GT])
2583 DEBUG(dbgs() << *Bound[Level].Upper[Dependence::DVEntry::GT] << '\n');
2584 else
2585 DEBUG(dbgs() << "+inf\n");
2586#endif
2587 }
2588
2589 unsigned NewDeps = 0;
2590
2591 // test bounds for <, *, *, ...
2592 if (testBounds(Dependence::DVEntry::LT, Level, Bound, Delta))
2593 NewDeps += exploreDirections(Level + 1, A, B, Bound,
2594 Loops, DepthExpanded, Delta);
2595
2596 // Test bounds for =, *, *, ...
2597 if (testBounds(Dependence::DVEntry::EQ, Level, Bound, Delta))
2598 NewDeps += exploreDirections(Level + 1, A, B, Bound,
2599 Loops, DepthExpanded, Delta);
2600
2601 // test bounds for >, *, *, ...
2602 if (testBounds(Dependence::DVEntry::GT, Level, Bound, Delta))
2603 NewDeps += exploreDirections(Level + 1, A, B, Bound,
2604 Loops, DepthExpanded, Delta);
2605
2606 Bound[Level].Direction = Dependence::DVEntry::ALL;
2607 return NewDeps;
2608 }
2609 else
2610 return exploreDirections(Level + 1, A, B, Bound, Loops, DepthExpanded, Delta);
2611}
2612
2613
2614// Returns true iff the current bounds are plausible.
2615bool DependenceAnalysis::testBounds(unsigned char DirKind,
2616 unsigned Level,
2617 BoundInfo *Bound,
2618 const SCEV *Delta) const {
2619 Bound[Level].Direction = DirKind;
2620 if (const SCEV *LowerBound = getLowerBound(Bound))
2621 if (isKnownPredicate(CmpInst::ICMP_SGT, LowerBound, Delta))
2622 return false;
2623 if (const SCEV *UpperBound = getUpperBound(Bound))
2624 if (isKnownPredicate(CmpInst::ICMP_SGT, Delta, UpperBound))
2625 return false;
2626 return true;
2627}
2628
2629
2630// Computes the upper and lower bounds for level K
2631// using the * direction. Records them in Bound.
2632// Wolfe gives the equations
2633//
2634// LB^*_k = (A^-_k - B^+_k)(U_k - L_k) + (A_k - B_k)L_k
2635// UB^*_k = (A^+_k - B^-_k)(U_k - L_k) + (A_k - B_k)L_k
2636//
2637// Since we normalize loops, we can simplify these equations to
2638//
2639// LB^*_k = (A^-_k - B^+_k)U_k
2640// UB^*_k = (A^+_k - B^-_k)U_k
2641//
2642// We must be careful to handle the case where the upper bound is unknown.
2643// Note that the lower bound is always <= 0
2644// and the upper bound is always >= 0.
2645void DependenceAnalysis::findBoundsALL(CoefficientInfo *A,
2646 CoefficientInfo *B,
2647 BoundInfo *Bound,
2648 unsigned K) const {
2649 Bound[K].Lower[Dependence::DVEntry::ALL] = NULL; // Default value = -infinity.
2650 Bound[K].Upper[Dependence::DVEntry::ALL] = NULL; // Default value = +infinity.
2651 if (Bound[K].Iterations) {
2652 Bound[K].Lower[Dependence::DVEntry::ALL] =
2653 SE->getMulExpr(SE->getMinusSCEV(A[K].NegPart, B[K].PosPart),
2654 Bound[K].Iterations);
2655 Bound[K].Upper[Dependence::DVEntry::ALL] =
2656 SE->getMulExpr(SE->getMinusSCEV(A[K].PosPart, B[K].NegPart),
2657 Bound[K].Iterations);
2658 }
2659 else {
2660 // If the difference is 0, we won't need to know the number of iterations.
2661 if (isKnownPredicate(CmpInst::ICMP_EQ, A[K].NegPart, B[K].PosPart))
2662 Bound[K].Lower[Dependence::DVEntry::ALL] =
2663 SE->getConstant(A[K].Coeff->getType(), 0);
2664 if (isKnownPredicate(CmpInst::ICMP_EQ, A[K].PosPart, B[K].NegPart))
2665 Bound[K].Upper[Dependence::DVEntry::ALL] =
2666 SE->getConstant(A[K].Coeff->getType(), 0);
2667 }
2668}
2669
2670
2671// Computes the upper and lower bounds for level K
2672// using the = direction. Records them in Bound.
2673// Wolfe gives the equations
2674//
2675// LB^=_k = (A_k - B_k)^- (U_k - L_k) + (A_k - B_k)L_k
2676// UB^=_k = (A_k - B_k)^+ (U_k - L_k) + (A_k - B_k)L_k
2677//
2678// Since we normalize loops, we can simplify these equations to
2679//
2680// LB^=_k = (A_k - B_k)^- U_k
2681// UB^=_k = (A_k - B_k)^+ U_k
2682//
2683// We must be careful to handle the case where the upper bound is unknown.
2684// Note that the lower bound is always <= 0
2685// and the upper bound is always >= 0.
2686void DependenceAnalysis::findBoundsEQ(CoefficientInfo *A,
2687 CoefficientInfo *B,
2688 BoundInfo *Bound,
2689 unsigned K) const {
2690 Bound[K].Lower[Dependence::DVEntry::EQ] = NULL; // Default value = -infinity.
2691 Bound[K].Upper[Dependence::DVEntry::EQ] = NULL; // Default value = +infinity.
2692 if (Bound[K].Iterations) {
2693 const SCEV *Delta = SE->getMinusSCEV(A[K].Coeff, B[K].Coeff);
2694 const SCEV *NegativePart = getNegativePart(Delta);
2695 Bound[K].Lower[Dependence::DVEntry::EQ] =
2696 SE->getMulExpr(NegativePart, Bound[K].Iterations);
2697 const SCEV *PositivePart = getPositivePart(Delta);
2698 Bound[K].Upper[Dependence::DVEntry::EQ] =
2699 SE->getMulExpr(PositivePart, Bound[K].Iterations);
2700 }
2701 else {
2702 // If the positive/negative part of the difference is 0,
2703 // we won't need to know the number of iterations.
2704 const SCEV *Delta = SE->getMinusSCEV(A[K].Coeff, B[K].Coeff);
2705 const SCEV *NegativePart = getNegativePart(Delta);
2706 if (NegativePart->isZero())
2707 Bound[K].Lower[Dependence::DVEntry::EQ] = NegativePart; // Zero
2708 const SCEV *PositivePart = getPositivePart(Delta);
2709 if (PositivePart->isZero())
2710 Bound[K].Upper[Dependence::DVEntry::EQ] = PositivePart; // Zero
2711 }
2712}
2713
2714
2715// Computes the upper and lower bounds for level K
2716// using the < direction. Records them in Bound.
2717// Wolfe gives the equations
2718//
2719// LB^<_k = (A^-_k - B_k)^- (U_k - L_k - N_k) + (A_k - B_k)L_k - B_k N_k
2720// UB^<_k = (A^+_k - B_k)^+ (U_k - L_k - N_k) + (A_k - B_k)L_k - B_k N_k
2721//
2722// Since we normalize loops, we can simplify these equations to
2723//
2724// LB^<_k = (A^-_k - B_k)^- (U_k - 1) - B_k
2725// UB^<_k = (A^+_k - B_k)^+ (U_k - 1) - B_k
2726//
2727// We must be careful to handle the case where the upper bound is unknown.
2728void DependenceAnalysis::findBoundsLT(CoefficientInfo *A,
2729 CoefficientInfo *B,
2730 BoundInfo *Bound,
2731 unsigned K) const {
2732 Bound[K].Lower[Dependence::DVEntry::LT] = NULL; // Default value = -infinity.
2733 Bound[K].Upper[Dependence::DVEntry::LT] = NULL; // Default value = +infinity.
2734 if (Bound[K].Iterations) {
2735 const SCEV *Iter_1 =
2736 SE->getMinusSCEV(Bound[K].Iterations,
2737 SE->getConstant(Bound[K].Iterations->getType(), 1));
2738 const SCEV *NegPart =
2739 getNegativePart(SE->getMinusSCEV(A[K].NegPart, B[K].Coeff));
2740 Bound[K].Lower[Dependence::DVEntry::LT] =
2741 SE->getMinusSCEV(SE->getMulExpr(NegPart, Iter_1), B[K].Coeff);
2742 const SCEV *PosPart =
2743 getPositivePart(SE->getMinusSCEV(A[K].PosPart, B[K].Coeff));
2744 Bound[K].Upper[Dependence::DVEntry::LT] =
2745 SE->getMinusSCEV(SE->getMulExpr(PosPart, Iter_1), B[K].Coeff);
2746 }
2747 else {
2748 // If the positive/negative part of the difference is 0,
2749 // we won't need to know the number of iterations.
2750 const SCEV *NegPart =
2751 getNegativePart(SE->getMinusSCEV(A[K].NegPart, B[K].Coeff));
2752 if (NegPart->isZero())
2753 Bound[K].Lower[Dependence::DVEntry::LT] = SE->getNegativeSCEV(B[K].Coeff);
2754 const SCEV *PosPart =
2755 getPositivePart(SE->getMinusSCEV(A[K].PosPart, B[K].Coeff));
2756 if (PosPart->isZero())
2757 Bound[K].Upper[Dependence::DVEntry::LT] = SE->getNegativeSCEV(B[K].Coeff);
2758 }
2759}
2760
2761
2762// Computes the upper and lower bounds for level K
2763// using the > direction. Records them in Bound.
2764// Wolfe gives the equations
2765//
2766// LB^>_k = (A_k - B^+_k)^- (U_k - L_k - N_k) + (A_k - B_k)L_k + A_k N_k
2767// UB^>_k = (A_k - B^-_k)^+ (U_k - L_k - N_k) + (A_k - B_k)L_k + A_k N_k
2768//
2769// Since we normalize loops, we can simplify these equations to
2770//
2771// LB^>_k = (A_k - B^+_k)^- (U_k - 1) + A_k
2772// UB^>_k = (A_k - B^-_k)^+ (U_k - 1) + A_k
2773//
2774// We must be careful to handle the case where the upper bound is unknown.
2775void DependenceAnalysis::findBoundsGT(CoefficientInfo *A,
2776 CoefficientInfo *B,
2777 BoundInfo *Bound,
2778 unsigned K) const {
2779 Bound[K].Lower[Dependence::DVEntry::GT] = NULL; // Default value = -infinity.
2780 Bound[K].Upper[Dependence::DVEntry::GT] = NULL; // Default value = +infinity.
2781 if (Bound[K].Iterations) {
2782 const SCEV *Iter_1 =
2783 SE->getMinusSCEV(Bound[K].Iterations,
2784 SE->getConstant(Bound[K].Iterations->getType(), 1));
2785 const SCEV *NegPart =
2786 getNegativePart(SE->getMinusSCEV(A[K].Coeff, B[K].PosPart));
2787 Bound[K].Lower[Dependence::DVEntry::GT] =
2788 SE->getAddExpr(SE->getMulExpr(NegPart, Iter_1), A[K].Coeff);
2789 const SCEV *PosPart =
2790 getPositivePart(SE->getMinusSCEV(A[K].Coeff, B[K].NegPart));
2791 Bound[K].Upper[Dependence::DVEntry::GT] =
2792 SE->getAddExpr(SE->getMulExpr(PosPart, Iter_1), A[K].Coeff);
2793 }
2794 else {
2795 // If the positive/negative part of the difference is 0,
2796 // we won't need to know the number of iterations.
2797 const SCEV *NegPart = getNegativePart(SE->getMinusSCEV(A[K].Coeff, B[K].PosPart));
2798 if (NegPart->isZero())
2799 Bound[K].Lower[Dependence::DVEntry::GT] = A[K].Coeff;
2800 const SCEV *PosPart = getPositivePart(SE->getMinusSCEV(A[K].Coeff, B[K].NegPart));
2801 if (PosPart->isZero())
2802 Bound[K].Upper[Dependence::DVEntry::GT] = A[K].Coeff;
2803 }
2804}
2805
2806
2807// X^+ = max(X, 0)
2808const SCEV *DependenceAnalysis::getPositivePart(const SCEV *X) const {
2809 return SE->getSMaxExpr(X, SE->getConstant(X->getType(), 0));
2810}
2811
2812
2813// X^- = min(X, 0)
2814const SCEV *DependenceAnalysis::getNegativePart(const SCEV *X) const {
2815 return SE->getSMinExpr(X, SE->getConstant(X->getType(), 0));
2816}
2817
2818
2819// Walks through the subscript,
2820// collecting each coefficient, the associated loop bounds,
2821// and recording its positive and negative parts for later use.
2822DependenceAnalysis::CoefficientInfo *
2823DependenceAnalysis::collectCoeffInfo(const SCEV *Subscript,
2824 bool SrcFlag,
2825 const SCEV *&Constant) const {
2826 const SCEV *Zero = SE->getConstant(Subscript->getType(), 0);
2827 CoefficientInfo *CI = new CoefficientInfo[MaxLevels + 1];
2828 for (unsigned K = 1; K <= MaxLevels; ++K) {
2829 CI[K].Coeff = Zero;
2830 CI[K].PosPart = Zero;
2831 CI[K].NegPart = Zero;
2832 CI[K].Iterations = NULL;
2833 }
2834 while (const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(Subscript)) {
2835 const Loop *L = AddRec->getLoop();
2836 unsigned K = SrcFlag ? mapSrcLoop(L) : mapDstLoop(L);
2837 CI[K].Coeff = AddRec->getStepRecurrence(*SE);
2838 CI[K].PosPart = getPositivePart(CI[K].Coeff);
2839 CI[K].NegPart = getNegativePart(CI[K].Coeff);
2840 CI[K].Iterations = collectUpperBound(L, Subscript->getType());
2841 Subscript = AddRec->getStart();
2842 }
2843 Constant = Subscript;
2844#ifndef NDEBUG
2845 DEBUG(dbgs() << "\tCoefficient Info\n");
2846 for (unsigned K = 1; K <= MaxLevels; ++K) {
2847 DEBUG(dbgs() << "\t " << K << "\t" << *CI[K].Coeff);
2848 DEBUG(dbgs() << "\tPos Part = ");
2849 DEBUG(dbgs() << *CI[K].PosPart);
2850 DEBUG(dbgs() << "\tNeg Part = ");
2851 DEBUG(dbgs() << *CI[K].NegPart);
2852 DEBUG(dbgs() << "\tUpper Bound = ");
2853 if (CI[K].Iterations)
2854 DEBUG(dbgs() << *CI[K].Iterations);
2855 else
2856 DEBUG(dbgs() << "+inf");
2857 DEBUG(dbgs() << '\n');
2858 }
2859 DEBUG(dbgs() << "\t Constant = " << *Subscript << '\n');
2860#endif
2861 return CI;
2862}
2863
2864
2865// Looks through all the bounds info and
2866// computes the lower bound given the current direction settings
2867// at each level. If the lower bound for any level is -inf,
2868// the result is -inf.
2869const SCEV *DependenceAnalysis::getLowerBound(BoundInfo *Bound) const {
2870 const SCEV *Sum = Bound[1].Lower[Bound[1].Direction];
2871 for (unsigned K = 2; Sum && K <= MaxLevels; ++K) {
2872 if (Bound[K].Lower[Bound[K].Direction])
2873 Sum = SE->getAddExpr(Sum, Bound[K].Lower[Bound[K].Direction]);
2874 else
2875 Sum = NULL;
2876 }
2877 return Sum;
2878}
2879
2880
2881// Looks through all the bounds info and
2882// computes the upper bound given the current direction settings
2883// at each level. If the upper bound at any level is +inf,
2884// the result is +inf.
2885const SCEV *DependenceAnalysis::getUpperBound(BoundInfo *Bound) const {
2886 const SCEV *Sum = Bound[1].Upper[Bound[1].Direction];
2887 for (unsigned K = 2; Sum && K <= MaxLevels; ++K) {
2888 if (Bound[K].Upper[Bound[K].Direction])
2889 Sum = SE->getAddExpr(Sum, Bound[K].Upper[Bound[K].Direction]);
2890 else
2891 Sum = NULL;
2892 }
2893 return Sum;
2894}
2895
2896
2897//===----------------------------------------------------------------------===//
2898// Constraint manipulation for Delta test.
2899
2900// Given a linear SCEV,
2901// return the coefficient (the step)
2902// corresponding to the specified loop.
2903// If there isn't one, return 0.
2904// For example, given a*i + b*j + c*k, zeroing the coefficient
2905// corresponding to the j loop would yield b.
2906const SCEV *DependenceAnalysis::findCoefficient(const SCEV *Expr,
2907 const Loop *TargetLoop) const {
2908 const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(Expr);
2909 if (!AddRec)
2910 return SE->getConstant(Expr->getType(), 0);
2911 if (AddRec->getLoop() == TargetLoop)
2912 return AddRec->getStepRecurrence(*SE);
2913 return findCoefficient(AddRec->getStart(), TargetLoop);
2914}
2915
2916
2917// Given a linear SCEV,
2918// return the SCEV given by zeroing out the coefficient
2919// corresponding to the specified loop.
2920// For example, given a*i + b*j + c*k, zeroing the coefficient
2921// corresponding to the j loop would yield a*i + c*k.
2922const SCEV *DependenceAnalysis::zeroCoefficient(const SCEV *Expr,
2923 const Loop *TargetLoop) const {
2924 const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(Expr);
2925 if (!AddRec)
2926 return Expr; // ignore
2927 if (AddRec->getLoop() == TargetLoop)
2928 return AddRec->getStart();
2929 return SE->getAddRecExpr(zeroCoefficient(AddRec->getStart(), TargetLoop),
2930 AddRec->getStepRecurrence(*SE),
2931 AddRec->getLoop(),
2932 AddRec->getNoWrapFlags());
2933}
2934
2935
2936// Given a linear SCEV Expr,
2937// return the SCEV given by adding some Value to the
2938// coefficient corresponding to the specified TargetLoop.
2939// For example, given a*i + b*j + c*k, adding 1 to the coefficient
2940// corresponding to the j loop would yield a*i + (b+1)*j + c*k.
2941const SCEV *DependenceAnalysis::addToCoefficient(const SCEV *Expr,
2942 const Loop *TargetLoop,
2943 const SCEV *Value) const {
2944 const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(Expr);
2945 if (!AddRec) // create a new addRec
2946 return SE->getAddRecExpr(Expr,
2947 Value,
2948 TargetLoop,
2949 SCEV::FlagAnyWrap); // Worst case, with no info.
2950 if (AddRec->getLoop() == TargetLoop) {
2951 const SCEV *Sum = SE->getAddExpr(AddRec->getStepRecurrence(*SE), Value);
2952 if (Sum->isZero())
2953 return AddRec->getStart();
2954 return SE->getAddRecExpr(AddRec->getStart(),
2955 Sum,
2956 AddRec->getLoop(),
2957 AddRec->getNoWrapFlags());
2958 }
2959 return SE->getAddRecExpr(addToCoefficient(AddRec->getStart(),
2960 TargetLoop, Value),
2961 AddRec->getStepRecurrence(*SE),
2962 AddRec->getLoop(),
2963 AddRec->getNoWrapFlags());
2964}
2965
2966
2967// Review the constraints, looking for opportunities
2968// to simplify a subscript pair (Src and Dst).
2969// Return true if some simplification occurs.
2970// If the simplification isn't exact (that is, if it is conservative
2971// in terms of dependence), set consistent to false.
2972// Corresponds to Figure 5 from the paper
2973//
2974// Practical Dependence Testing
2975// Goff, Kennedy, Tseng
2976// PLDI 1991
2977bool DependenceAnalysis::propagate(const SCEV *&Src,
2978 const SCEV *&Dst,
2979 SmallBitVector &Loops,
2980 SmallVector<Constraint, 4> &Constraints,
2981 bool &Consistent) {
2982 bool Result = false;
2983 for (int LI = Loops.find_first(); LI >= 0; LI = Loops.find_next(LI)) {
2984 DEBUG(dbgs() << "\t Constraint[" << LI << "] is");
2985 DEBUG(Constraints[LI].dump(dbgs()));
2986 if (Constraints[LI].isDistance())
2987 Result |= propagateDistance(Src, Dst, Constraints[LI], Consistent);
2988 else if (Constraints[LI].isLine())
2989 Result |= propagateLine(Src, Dst, Constraints[LI], Consistent);
2990 else if (Constraints[LI].isPoint())
2991 Result |= propagatePoint(Src, Dst, Constraints[LI]);
2992 }
2993 return Result;
2994}
2995
2996
2997// Attempt to propagate a distance
2998// constraint into a subscript pair (Src and Dst).
2999// Return true if some simplification occurs.
3000// If the simplification isn't exact (that is, if it is conservative
3001// in terms of dependence), set consistent to false.
3002bool DependenceAnalysis::propagateDistance(const SCEV *&Src,
3003 const SCEV *&Dst,
3004 Constraint &CurConstraint,
3005 bool &Consistent) {
3006 const Loop *CurLoop = CurConstraint.getAssociatedLoop();
3007 DEBUG(dbgs() << "\t\tSrc is " << *Src << "\n");
3008 const SCEV *A_K = findCoefficient(Src, CurLoop);
3009 if (A_K->isZero())
3010 return false;
3011 const SCEV *DA_K = SE->getMulExpr(A_K, CurConstraint.getD());
3012 Src = SE->getMinusSCEV(Src, DA_K);
3013 Src = zeroCoefficient(Src, CurLoop);
3014 DEBUG(dbgs() << "\t\tnew Src is " << *Src << "\n");
3015 DEBUG(dbgs() << "\t\tDst is " << *Dst << "\n");
3016 Dst = addToCoefficient(Dst, CurLoop, SE->getNegativeSCEV(A_K));
3017 DEBUG(dbgs() << "\t\tnew Dst is " << *Dst << "\n");
3018 if (!findCoefficient(Dst, CurLoop)->isZero())
3019 Consistent = false;
3020 return true;
3021}
3022
3023
3024// Attempt to propagate a line
3025// constraint into a subscript pair (Src and Dst).
3026// Return true if some simplification occurs.
3027// If the simplification isn't exact (that is, if it is conservative
3028// in terms of dependence), set consistent to false.
3029bool DependenceAnalysis::propagateLine(const SCEV *&Src,
3030 const SCEV *&Dst,
3031 Constraint &CurConstraint,
3032 bool &Consistent) {
3033 const Loop *CurLoop = CurConstraint.getAssociatedLoop();
3034 const SCEV *A = CurConstraint.getA();
3035 const SCEV *B = CurConstraint.getB();
3036 const SCEV *C = CurConstraint.getC();
3037 DEBUG(dbgs() << "\t\tA = " << *A << ", B = " << *B << ", C = " << *C << "\n");
3038 DEBUG(dbgs() << "\t\tSrc = " << *Src << "\n");
3039 DEBUG(dbgs() << "\t\tDst = " << *Dst << "\n");
3040 if (A->isZero()) {
3041 const SCEVConstant *Bconst = dyn_cast<SCEVConstant>(B);
3042 const SCEVConstant *Cconst = dyn_cast<SCEVConstant>(C);
3043 if (!Bconst || !Cconst) return false;
3044 APInt Beta = Bconst->getValue()->getValue();
3045 APInt Charlie = Cconst->getValue()->getValue();
3046 APInt CdivB = Charlie.sdiv(Beta);
3047 assert(Charlie.srem(Beta) == 0 && "C should be evenly divisible by B");
3048 const SCEV *AP_K = findCoefficient(Dst, CurLoop);
3049 // Src = SE->getAddExpr(Src, SE->getMulExpr(AP_K, SE->getConstant(CdivB)));
3050 Src = SE->getMinusSCEV(Src, SE->getMulExpr(AP_K, SE->getConstant(CdivB)));
3051 Dst = zeroCoefficient(Dst, CurLoop);
3052 if (!findCoefficient(Src, CurLoop)->isZero())
3053 Consistent = false;
3054 }
3055 else if (B->isZero()) {
3056 const SCEVConstant *Aconst = dyn_cast<SCEVConstant>(A);
3057 const SCEVConstant *Cconst = dyn_cast<SCEVConstant>(C);
3058 if (!Aconst || !Cconst) return false;
3059 APInt Alpha = Aconst->getValue()->getValue();
3060 APInt Charlie = Cconst->getValue()->getValue();
3061 APInt CdivA = Charlie.sdiv(Alpha);
3062 assert(Charlie.srem(Alpha) == 0 && "C should be evenly divisible by A");
3063 const SCEV *A_K = findCoefficient(Src, CurLoop);
3064 Src = SE->getAddExpr(Src, SE->getMulExpr(A_K, SE->getConstant(CdivA)));
3065 Src = zeroCoefficient(Src, CurLoop);
3066 if (!findCoefficient(Dst, CurLoop)->isZero())
3067 Consistent = false;
3068 }
3069 else if (isKnownPredicate(CmpInst::ICMP_EQ, A, B)) {
3070 const SCEVConstant *Aconst = dyn_cast<SCEVConstant>(A);
3071 const SCEVConstant *Cconst = dyn_cast<SCEVConstant>(C);
3072 if (!Aconst || !Cconst) return false;
3073 APInt Alpha = Aconst->getValue()->getValue();
3074 APInt Charlie = Cconst->getValue()->getValue();
3075 APInt CdivA = Charlie.sdiv(Alpha);
3076 assert(Charlie.srem(Alpha) == 0 && "C should be evenly divisible by A");
3077 const SCEV *A_K = findCoefficient(Src, CurLoop);
3078 Src = SE->getAddExpr(Src, SE->getMulExpr(A_K, SE->getConstant(CdivA)));
3079 Src = zeroCoefficient(Src, CurLoop);
3080 Dst = addToCoefficient(Dst, CurLoop, A_K);
3081 if (!findCoefficient(Dst, CurLoop)->isZero())
3082 Consistent = false;
3083 }
3084 else {
3085 // paper is incorrect here, or perhaps just misleading
3086 const SCEV *A_K = findCoefficient(Src, CurLoop);
3087 Src = SE->getMulExpr(Src, A);
3088 Dst = SE->getMulExpr(Dst, A);
3089 Src = SE->getAddExpr(Src, SE->getMulExpr(A_K, C));
3090 Src = zeroCoefficient(Src, CurLoop);
3091 Dst = addToCoefficient(Dst, CurLoop, SE->getMulExpr(A_K, B));
3092 if (!findCoefficient(Dst, CurLoop)->isZero())
3093 Consistent = false;
3094 }
3095 DEBUG(dbgs() << "\t\tnew Src = " << *Src << "\n");
3096 DEBUG(dbgs() << "\t\tnew Dst = " << *Dst << "\n");
3097 return true;
3098}
3099
3100
3101// Attempt to propagate a point
3102// constraint into a subscript pair (Src and Dst).
3103// Return true if some simplification occurs.
3104bool DependenceAnalysis::propagatePoint(const SCEV *&Src,
3105 const SCEV *&Dst,
3106 Constraint &CurConstraint) {
3107 const Loop *CurLoop = CurConstraint.getAssociatedLoop();
3108 const SCEV *A_K = findCoefficient(Src, CurLoop);
3109 const SCEV *AP_K = findCoefficient(Dst, CurLoop);
3110 const SCEV *XA_K = SE->getMulExpr(A_K, CurConstraint.getX());
3111 const SCEV *YAP_K = SE->getMulExpr(AP_K, CurConstraint.getY());
3112 DEBUG(dbgs() << "\t\tSrc is " << *Src << "\n");
3113 Src = SE->getAddExpr(Src, SE->getMinusSCEV(XA_K, YAP_K));
3114 Src = zeroCoefficient(Src, CurLoop);
3115 DEBUG(dbgs() << "\t\tnew Src is " << *Src << "\n");
3116 DEBUG(dbgs() << "\t\tDst is " << *Dst << "\n");
3117 Dst = zeroCoefficient(Dst, CurLoop);
3118 DEBUG(dbgs() << "\t\tnew Dst is " << *Dst << "\n");
3119 return true;
3120}
3121
3122
3123// Update direction vector entry based on the current constraint.
3124void DependenceAnalysis::updateDirection(Dependence::DVEntry &Level,
3125 const Constraint &CurConstraint
3126 ) const {
3127 DEBUG(dbgs() << "\tUpdate direction, constraint =");
3128 DEBUG(CurConstraint.dump(dbgs()));
3129 if (CurConstraint.isAny())
3130 ; // use defaults
3131 else if (CurConstraint.isDistance()) {
3132 // this one is consistent, the others aren't
3133 Level.Scalar = false;
3134 Level.Distance = CurConstraint.getD();
3135 unsigned NewDirection = Dependence::DVEntry::NONE;
3136 if (!SE->isKnownNonZero(Level.Distance)) // if may be zero
3137 NewDirection = Dependence::DVEntry::EQ;
3138 if (!SE->isKnownNonPositive(Level.Distance)) // if may be positive
3139 NewDirection |= Dependence::DVEntry::LT;
3140 if (!SE->isKnownNonNegative(Level.Distance)) // if may be negative
3141 NewDirection |= Dependence::DVEntry::GT;
3142 Level.Direction &= NewDirection;
3143 }
3144 else if (CurConstraint.isLine()) {
3145 Level.Scalar = false;
3146 Level.Distance = NULL;
3147 // direction should be accurate
3148 }
3149 else if (CurConstraint.isPoint()) {
3150 Level.Scalar = false;
3151 Level.Distance = NULL;
3152 unsigned NewDirection = Dependence::DVEntry::NONE;
3153 if (!isKnownPredicate(CmpInst::ICMP_NE,
3154 CurConstraint.getY(),
3155 CurConstraint.getX()))
3156 // if X may be = Y
3157 NewDirection |= Dependence::DVEntry::EQ;
3158 if (!isKnownPredicate(CmpInst::ICMP_SLE,
3159 CurConstraint.getY(),
3160 CurConstraint.getX()))
3161 // if Y may be > X
3162 NewDirection |= Dependence::DVEntry::LT;
3163 if (!isKnownPredicate(CmpInst::ICMP_SGE,
3164 CurConstraint.getY(),
3165 CurConstraint.getX()))
3166 // if Y may be < X
3167 NewDirection |= Dependence::DVEntry::GT;
3168 Level.Direction &= NewDirection;
3169 }
3170 else
3171 llvm_unreachable("constraint has unexpected kind");
3172}
3173
3174
3175//===----------------------------------------------------------------------===//
3176
3177#ifndef NDEBUG
3178// For debugging purposes, dump a small bit vector to dbgs().
3179static void dumpSmallBitVector(SmallBitVector &BV) {
3180 dbgs() << "{";
3181 for (int VI = BV.find_first(); VI >= 0; VI = BV.find_next(VI)) {
3182 dbgs() << VI;
3183 if (BV.find_next(VI) >= 0)
3184 dbgs() << ' ';
3185 }
3186 dbgs() << "}\n";
3187}
3188#endif
3189
3190
3191// depends -
3192// Returns NULL if there is no dependence.
3193// Otherwise, return a Dependence with as many details as possible.
3194// Corresponds to Section 3.1 in the paper
3195//
3196// Practical Dependence Testing
3197// Goff, Kennedy, Tseng
3198// PLDI 1991
3199//
3200// Care is required to keep the code below up to date w.r.t. this routine.
3201Dependence *DependenceAnalysis::depends(const Instruction *Src,
3202 const Instruction *Dst,
3203 bool PossiblyLoopIndependent) {
3204 if ((!Src->mayReadFromMemory() && !Src->mayWriteToMemory()) ||
3205 (!Dst->mayReadFromMemory() && !Dst->mayWriteToMemory()))
3206 // if both instructions don't reference memory, there's no dependence
3207 return NULL;
3208
3209 if (!isLoadOrStore(Src) || !isLoadOrStore(Dst))
3210 // can only analyze simple loads and stores, i.e., no calls, invokes, etc.
3211 return new Dependence(Src, Dst);
3212
3213 const Value *SrcPtr = getPointerOperand(Src);
3214 const Value *DstPtr = getPointerOperand(Dst);
3215
3216 switch (underlyingObjectsAlias(AA, DstPtr, SrcPtr)) {
3217 case AliasAnalysis::MayAlias:
3218 case AliasAnalysis::PartialAlias:
3219 // cannot analyse objects if we don't understand their aliasing.
3220 return new Dependence(Src, Dst);
3221 case AliasAnalysis::NoAlias:
3222 // If the objects noalias, they are distinct, accesses are independent.
3223 return NULL;
3224 case AliasAnalysis::MustAlias:
3225 break; // The underlying objects alias; test accesses for dependence.
3226 }
3227
3228 const GEPOperator *SrcGEP = dyn_cast<GEPOperator>(SrcPtr);
3229 const GEPOperator *DstGEP = dyn_cast<GEPOperator>(DstPtr);
3230 if (!SrcGEP || !DstGEP)
3231 return new Dependence(Src, Dst); // missing GEP, assume dependence
3232
3233 if (SrcGEP->getPointerOperandType() != DstGEP->getPointerOperandType())
3234 return new Dependence(Src, Dst); // different types, assume dependence
3235
3236 // establish loop nesting levels
3237 establishNestingLevels(Src, Dst);
3238 DEBUG(dbgs() << " common nesting levels = " << CommonLevels << "\n");
3239 DEBUG(dbgs() << " maximum nesting levels = " << MaxLevels << "\n");
3240
3241 FullDependence Result(Src, Dst, PossiblyLoopIndependent, CommonLevels);
3242 ++TotalArrayPairs;
3243
3244 // classify subscript pairs
3245 unsigned Pairs = SrcGEP->idx_end() - SrcGEP->idx_begin();
3246 SmallVector<Subscript, 4> Pair(Pairs);
3247 for (unsigned SI = 0; SI < Pairs; ++SI) {
3248 Pair[SI].Loops.resize(MaxLevels + 1);
3249 Pair[SI].GroupLoops.resize(MaxLevels + 1);
3250 Pair[SI].Group.resize(Pairs);
3251 }
3252 Pairs = 0;
3253 for (GEPOperator::const_op_iterator SrcIdx = SrcGEP->idx_begin(),
3254 SrcEnd = SrcGEP->idx_end(),
3255 DstIdx = DstGEP->idx_begin(),
3256 DstEnd = DstGEP->idx_end();
3257 SrcIdx != SrcEnd && DstIdx != DstEnd;
3258 ++SrcIdx, ++DstIdx, ++Pairs) {
3259 Pair[Pairs].Src = SE->getSCEV(*SrcIdx);
3260 Pair[Pairs].Dst = SE->getSCEV(*DstIdx);
3261 removeMatchingExtensions(&Pair[Pairs]);
3262 Pair[Pairs].Classification =
3263 classifyPair(Pair[Pairs].Src, LI->getLoopFor(Src->getParent()),
3264 Pair[Pairs].Dst, LI->getLoopFor(Dst->getParent()),
3265 Pair[Pairs].Loops);
3266 Pair[Pairs].GroupLoops = Pair[Pairs].Loops;
3267 Pair[Pairs].Group.set(Pairs);
3268 DEBUG(dbgs() << " subscript " << Pairs << "\n");
3269 DEBUG(dbgs() << "\tsrc = " << *Pair[Pairs].Src << "\n");
3270 DEBUG(dbgs() << "\tdst = " << *Pair[Pairs].Dst << "\n");
3271 DEBUG(dbgs() << "\tclass = " << Pair[Pairs].Classification << "\n");
3272 DEBUG(dbgs() << "\tloops = ");
3273 DEBUG(dumpSmallBitVector(Pair[Pairs].Loops));
3274 }
3275
3276 SmallBitVector Separable(Pairs);
3277 SmallBitVector Coupled(Pairs);
3278
3279 // Partition subscripts into separable and minimally-coupled groups
3280 // Algorithm in paper is algorithmically better;
3281 // this may be faster in practice. Check someday.
3282 //
3283 // Here's an example of how it works. Consider this code:
3284 //
3285 // for (i = ...) {
3286 // for (j = ...) {
3287 // for (k = ...) {
3288 // for (l = ...) {
3289 // for (m = ...) {
3290 // A[i][j][k][m] = ...;
3291 // ... = A[0][j][l][i + j];
3292 // }
3293 // }
3294 // }
3295 // }
3296 // }
3297 //
3298 // There are 4 subscripts here:
3299 // 0 [i] and [0]
3300 // 1 [j] and [j]
3301 // 2 [k] and [l]
3302 // 3 [m] and [i + j]
3303 //
3304 // We've already classified each subscript pair as ZIV, SIV, etc.,
3305 // and collected all the loops mentioned by pair P in Pair[P].Loops.
3306 // In addition, we've initialized Pair[P].GroupLoops to Pair[P].Loops
3307 // and set Pair[P].Group = {P}.
3308 //
3309 // Src Dst Classification Loops GroupLoops Group
3310 // 0 [i] [0] SIV {1} {1} {0}
3311 // 1 [j] [j] SIV {2} {2} {1}
3312 // 2 [k] [l] RDIV {3,4} {3,4} {2}
3313 // 3 [m] [i + j] MIV {1,2,5} {1,2,5} {3}
3314 //
3315 // For each subscript SI 0 .. 3, we consider each remaining subscript, SJ.
3316 // So, 0 is compared against 1, 2, and 3; 1 is compared against 2 and 3, etc.
3317 //
3318 // We begin by comparing 0 and 1. The intersection of the GroupLoops is empty.
3319 // Next, 0 and 2. Again, the intersection of their GroupLoops is empty.
3320 // Next 0 and 3. The intersection of their GroupLoop = {1}, not empty,
3321 // so Pair[3].Group = {0,3} and Done = false (that is, 0 will not be added
3322 // to either Separable or Coupled).
3323 //
3324 // Next, we consider 1 and 2. The intersection of the GroupLoops is empty.
3325 // Next, 1 and 3. The intersectionof their GroupLoops = {2}, not empty,
3326 // so Pair[3].Group = {0, 1, 3} and Done = false.
3327 //
3328 // Next, we compare 2 against 3. The intersection of the GroupLoops is empty.
3329 // Since Done remains true, we add 2 to the set of Separable pairs.
3330 //
3331 // Finally, we consider 3. There's nothing to compare it with,
3332 // so Done remains true and we add it to the Coupled set.
3333 // Pair[3].Group = {0, 1, 3} and GroupLoops = {1, 2, 5}.
3334 //
3335 // In the end, we've got 1 separable subscript and 1 coupled group.
3336 for (unsigned SI = 0; SI < Pairs; ++SI) {
3337 if (Pair[SI].Classification == Subscript::NonLinear) {
3338 // ignore these, but collect loops for later
3339 ++NonlinearSubscriptPairs;
3340 collectCommonLoops(Pair[SI].Src,
3341 LI->getLoopFor(Src->getParent()),
3342 Pair[SI].Loops);
3343 collectCommonLoops(Pair[SI].Dst,
3344 LI->getLoopFor(Dst->getParent()),
3345 Pair[SI].Loops);
3346 Result.Consistent = false;
3347 }
3348 else if (Pair[SI].Classification == Subscript::ZIV) {
3349 // always separable
3350 Separable.set(SI);
3351 }
3352 else {
3353 // SIV, RDIV, or MIV, so check for coupled group
3354 bool Done = true;
3355 for (unsigned SJ = SI + 1; SJ < Pairs; ++SJ) {
3356 SmallBitVector Intersection = Pair[SI].GroupLoops;
3357 Intersection &= Pair[SJ].GroupLoops;
3358 if (Intersection.any()) {
3359 // accumulate set of all the loops in group
3360 Pair[SJ].GroupLoops |= Pair[SI].GroupLoops;
3361 // accumulate set of all subscripts in group
3362 Pair[SJ].Group |= Pair[SI].Group;
3363 Done = false;
3364 }
3365 }
3366 if (Done) {
3367 if (Pair[SI].Group.count() == 1) {
3368 Separable.set(SI);
3369 ++SeparableSubscriptPairs;
3370 }
3371 else {
3372 Coupled.set(SI);
3373 ++CoupledSubscriptPairs;
3374 }
3375 }
3376 }
3377 }
3378
3379 DEBUG(dbgs() << " Separable = ");
3380 DEBUG(dumpSmallBitVector(Separable));
3381 DEBUG(dbgs() << " Coupled = ");
3382 DEBUG(dumpSmallBitVector(Coupled));
3383
3384 Constraint NewConstraint;
3385 NewConstraint.setAny(SE);
3386
3387 // test separable subscripts
3388 for (int SI = Separable.find_first(); SI >= 0; SI = Separable.find_next(SI)) {
3389 DEBUG(dbgs() << "testing subscript " << SI);
3390 switch (Pair[SI].Classification) {
3391 case Subscript::ZIV:
3392 DEBUG(dbgs() << ", ZIV\n");
3393 if (testZIV(Pair[SI].Src, Pair[SI].Dst, Result))
3394 return NULL;
3395 break;
3396 case Subscript::SIV: {
3397 DEBUG(dbgs() << ", SIV\n");
3398 unsigned Level;
3399 const SCEV *SplitIter = NULL;
3400 if (testSIV(Pair[SI].Src, Pair[SI].Dst, Level,
3401 Result, NewConstraint, SplitIter))
3402 return NULL;
3403 break;
3404 }
3405 case Subscript::RDIV:
3406 DEBUG(dbgs() << ", RDIV\n");
3407 if (testRDIV(Pair[SI].Src, Pair[SI].Dst, Result))
3408 return NULL;
3409 break;
3410 case Subscript::MIV:
3411 DEBUG(dbgs() << ", MIV\n");
3412 if (testMIV(Pair[SI].Src, Pair[SI].Dst, Pair[SI].Loops, Result))
3413 return NULL;
3414 break;
3415 default:
3416 llvm_unreachable("subscript has unexpected classification");
3417 }
3418 }
3419
3420 if (Coupled.count()) {
3421 // test coupled subscript groups
3422 DEBUG(dbgs() << "starting on coupled subscripts\n");
3423 DEBUG(dbgs() << "MaxLevels + 1 = " << MaxLevels + 1 << "\n");
3424 SmallVector<Constraint, 4> Constraints(MaxLevels + 1);
3425 for (unsigned II = 0; II <= MaxLevels; ++II)
3426 Constraints[II].setAny(SE);
3427 for (int SI = Coupled.find_first(); SI >= 0; SI = Coupled.find_next(SI)) {
3428 DEBUG(dbgs() << "testing subscript group " << SI << " { ");
3429 SmallBitVector Group(Pair[SI].Group);
3430 SmallBitVector Sivs(Pairs);
3431 SmallBitVector Mivs(Pairs);
3432 SmallBitVector ConstrainedLevels(MaxLevels + 1);
3433 for (int SJ = Group.find_first(); SJ >= 0; SJ = Group.find_next(SJ)) {
3434 DEBUG(dbgs() << SJ << " ");
3435 if (Pair[SJ].Classification == Subscript::SIV)
3436 Sivs.set(SJ);
3437 else
3438 Mivs.set(SJ);
3439 }
3440 DEBUG(dbgs() << "}\n");
3441 while (Sivs.any()) {
3442 bool Changed = false;
3443 for (int SJ = Sivs.find_first(); SJ >= 0; SJ = Sivs.find_next(SJ)) {
3444 DEBUG(dbgs() << "testing subscript " << SJ << ", SIV\n");
3445 // SJ is an SIV subscript that's part of the current coupled group
3446 unsigned Level;
3447 const SCEV *SplitIter = NULL;
3448 DEBUG(dbgs() << "SIV\n");
3449 if (testSIV(Pair[SJ].Src, Pair[SJ].Dst, Level,
3450 Result, NewConstraint, SplitIter))
3451 return NULL;
3452 ConstrainedLevels.set(Level);
3453 if (intersectConstraints(&Constraints[Level], &NewConstraint)) {
3454 if (Constraints[Level].isEmpty()) {
3455 ++DeltaIndependence;
3456 return NULL;
3457 }
3458 Changed = true;
3459 }
3460 Sivs.reset(SJ);
3461 }
3462 if (Changed) {
3463 // propagate, possibly creating new SIVs and ZIVs
3464 DEBUG(dbgs() << " propagating\n");
3465 DEBUG(dbgs() << "\tMivs = ");
3466 DEBUG(dumpSmallBitVector(Mivs));
3467 for (int SJ = Mivs.find_first(); SJ >= 0; SJ = Mivs.find_next(SJ)) {
3468 // SJ is an MIV subscript that's part of the current coupled group
3469 DEBUG(dbgs() << "\tSJ = " << SJ << "\n");
3470 if (propagate(Pair[SJ].Src, Pair[SJ].Dst, Pair[SJ].Loops,
3471 Constraints, Result.Consistent)) {
3472 DEBUG(dbgs() << "\t Changed\n");
3473 ++DeltaPropagations;
3474 Pair[SJ].Classification =
3475 classifyPair(Pair[SJ].Src, LI->getLoopFor(Src->getParent()),
3476 Pair[SJ].Dst, LI->getLoopFor(Dst->getParent()),
3477 Pair[SJ].Loops);
3478 switch (Pair[SJ].Classification) {
3479 case Subscript::ZIV:
3480 DEBUG(dbgs() << "ZIV\n");
3481 if (testZIV(Pair[SJ].Src, Pair[SJ].Dst, Result))
3482 return NULL;
3483 Mivs.reset(SJ);
3484 break;
3485 case Subscript::SIV:
3486 Sivs.set(SJ);
3487 Mivs.reset(SJ);
3488 break;
3489 case Subscript::RDIV:
3490 case Subscript::MIV:
3491 break;
3492 default:
3493 llvm_unreachable("bad subscript classification");
3494 }
3495 }
3496 }
3497 }
3498 }
3499
3500 // test & propagate remaining RDIVs
3501 for (int SJ = Mivs.find_first(); SJ >= 0; SJ = Mivs.find_next(SJ)) {
3502 if (Pair[SJ].Classification == Subscript::RDIV) {
3503 DEBUG(dbgs() << "RDIV test\n");
3504 if (testRDIV(Pair[SJ].Src, Pair[SJ].Dst, Result))
3505 return NULL;
3506 // I don't yet understand how to propagate RDIV results
3507 Mivs.reset(SJ);
3508 }
3509 }
3510
3511 // test remaining MIVs
3512 // This code is temporary.
3513 // Better to somehow test all remaining subscripts simultaneously.
3514 for (int SJ = Mivs.find_first(); SJ >= 0; SJ = Mivs.find_next(SJ)) {
3515 if (Pair[SJ].Classification == Subscript::MIV) {
3516 DEBUG(dbgs() << "MIV test\n");
3517 if (testMIV(Pair[SJ].Src, Pair[SJ].Dst, Pair[SJ].Loops, Result))
3518 return NULL;
3519 }
3520 else
3521 llvm_unreachable("expected only MIV subscripts at this point");
3522 }
3523
3524 // update Result.DV from constraint vector
3525 DEBUG(dbgs() << " updating\n");
3526 for (int SJ = ConstrainedLevels.find_first();
3527 SJ >= 0; SJ = ConstrainedLevels.find_next(SJ)) {
3528 updateDirection(Result.DV[SJ - 1], Constraints[SJ]);
3529 if (Result.DV[SJ - 1].Direction == Dependence::DVEntry::NONE)
3530 return NULL;
3531 }
3532 }
3533 }
3534
3535 // make sure Scalar flags are set correctly
3536 SmallBitVector CompleteLoops(MaxLevels + 1);
3537 for (unsigned SI = 0; SI < Pairs; ++SI)
3538 CompleteLoops |= Pair[SI].Loops;
3539 for (unsigned II = 1; II <= CommonLevels; ++II)
3540 if (CompleteLoops[II])
3541 Result.DV[II - 1].Scalar = false;
3542
3543 // make sure loopIndepent flag is set correctly
3544 if (PossiblyLoopIndependent) {
3545 for (unsigned II = 1; II <= CommonLevels; ++II) {
3546 if (!(Result.getDirection(II) & Dependence::DVEntry::EQ)) {
3547 Result.LoopIndependent = false;
3548 break;
3549 }
3550 }
3551 }
3552
3553 FullDependence *Final = new FullDependence(Result);
3554 Result.DV = NULL;
3555 return Final;
3556}
3557
3558
3559
3560//===----------------------------------------------------------------------===//
3561// getSplitIteration -
3562// Rather than spend rarely-used space recording the splitting iteration
3563// during the Weak-Crossing SIV test, we re-compute it on demand.
3564// The re-computation is basically a repeat of the entire dependence test,
3565// though simplified since we know that the dependence exists.
3566// It's tedious, since we must go through all propagations, etc.
3567//
3568// Care is required to keep this code up to date w.r.t. the code above.
3569//
3570// Generally, the dependence analyzer will be used to build
3571// a dependence graph for a function (basically a map from instructions
3572// to dependences). Looking for cycles in the graph shows us loops
3573// that cannot be trivially vectorized/parallelized.
3574//
3575// We can try to improve the situation by examining all the dependences
3576// that make up the cycle, looking for ones we can break.
3577// Sometimes, peeling the first or last iteration of a loop will break
3578// dependences, and we've got flags for those possibilities.
3579// Sometimes, splitting a loop at some other iteration will do the trick,
3580// and we've got a flag for that case. Rather than waste the space to
3581// record the exact iteration (since we rarely know), we provide
3582// a method that calculates the iteration. It's a drag that it must work
3583// from scratch, but wonderful in that it's possible.
3584//
3585// Here's an example:
3586//
3587// for (i = 0; i < 10; i++)
3588// A[i] = ...
3589// ... = A[11 - i]
3590//
3591// There's a loop-carried flow dependence from the store to the load,
3592// found by the weak-crossing SIV test. The dependence will have a flag,
3593// indicating that the dependence can be broken by splitting the loop.
3594// Calling getSplitIteration will return 5.
3595// Splitting the loop breaks the dependence, like so:
3596//
3597// for (i = 0; i <= 5; i++)
3598// A[i] = ...
3599// ... = A[11 - i]
3600// for (i = 6; i < 10; i++)
3601// A[i] = ...
3602// ... = A[11 - i]
3603//
3604// breaks the dependence and allows us to vectorize/parallelize
3605// both loops.
3606const SCEV *DependenceAnalysis::getSplitIteration(const Dependence *Dep,
3607 unsigned SplitLevel) {
3608 assert(Dep && "expected a pointer to a Dependence");
3609 assert(Dep->isSplitable(SplitLevel) &&
3610 "Dep should be splitable at SplitLevel");
3611 const Instruction *Src = Dep->getSrc();
3612 const Instruction *Dst = Dep->getDst();
3613 assert(Src->mayReadFromMemory() || Src->mayWriteToMemory());
3614 assert(Dst->mayReadFromMemory() || Dst->mayWriteToMemory());
3615 assert(isLoadOrStore(Src));
3616 assert(isLoadOrStore(Dst));
3617 const Value *SrcPtr = getPointerOperand(Src);
3618 const Value *DstPtr = getPointerOperand(Dst);
3619 assert(underlyingObjectsAlias(AA, DstPtr, SrcPtr) ==
3620 AliasAnalysis::MustAlias);
3621 const GEPOperator *SrcGEP = dyn_cast<GEPOperator>(SrcPtr);
3622 const GEPOperator *DstGEP = dyn_cast<GEPOperator>(DstPtr);
3623 assert(SrcGEP);
3624 assert(DstGEP);
3625 assert(SrcGEP->getPointerOperandType() == DstGEP->getPointerOperandType());
3626
3627 // establish loop nesting levels
3628 establishNestingLevels(Src, Dst);
3629
3630 FullDependence Result(Src, Dst, false, CommonLevels);
3631
3632 // classify subscript pairs
3633 unsigned Pairs = SrcGEP->idx_end() - SrcGEP->idx_begin();
3634 SmallVector<Subscript, 4> Pair(Pairs);
3635 for (unsigned SI = 0; SI < Pairs; ++SI) {
3636 Pair[SI].Loops.resize(MaxLevels + 1);
3637 Pair[SI].GroupLoops.resize(MaxLevels + 1);
3638 Pair[SI].Group.resize(Pairs);
3639 }
3640 Pairs = 0;
3641 for (GEPOperator::const_op_iterator SrcIdx = SrcGEP->idx_begin(),
3642 SrcEnd = SrcGEP->idx_end(),
3643 DstIdx = DstGEP->idx_begin(),
3644 DstEnd = DstGEP->idx_end();
3645 SrcIdx != SrcEnd && DstIdx != DstEnd;
3646 ++SrcIdx, ++DstIdx, ++Pairs) {
3647 Pair[Pairs].Src = SE->getSCEV(*SrcIdx);
3648 Pair[Pairs].Dst = SE->getSCEV(*DstIdx);
3649 Pair[Pairs].Classification =
3650 classifyPair(Pair[Pairs].Src, LI->getLoopFor(Src->getParent()),
3651 Pair[Pairs].Dst, LI->getLoopFor(Dst->getParent()),
3652 Pair[Pairs].Loops);
3653 Pair[Pairs].GroupLoops = Pair[Pairs].Loops;
3654 Pair[Pairs].Group.set(Pairs);
3655 }
3656
3657 SmallBitVector Separable(Pairs);
3658 SmallBitVector Coupled(Pairs);
3659
3660 // partition subscripts into separable and minimally-coupled groups
3661 for (unsigned SI = 0; SI < Pairs; ++SI) {
3662 if (Pair[SI].Classification == Subscript::NonLinear) {
3663 // ignore these, but collect loops for later
3664 collectCommonLoops(Pair[SI].Src,
3665 LI->getLoopFor(Src->getParent()),
3666 Pair[SI].Loops);
3667 collectCommonLoops(Pair[SI].Dst,
3668 LI->getLoopFor(Dst->getParent()),
3669 Pair[SI].Loops);
3670 Result.Consistent = false;
3671 }
3672 else if (Pair[SI].Classification == Subscript::ZIV)
3673 Separable.set(SI);
3674 else {
3675 // SIV, RDIV, or MIV, so check for coupled group
3676 bool Done = true;
3677 for (unsigned SJ = SI + 1; SJ < Pairs; ++SJ) {
3678 SmallBitVector Intersection = Pair[SI].GroupLoops;
3679 Intersection &= Pair[SJ].GroupLoops;
3680 if (Intersection.any()) {
3681 // accumulate set of all the loops in group
3682 Pair[SJ].GroupLoops |= Pair[SI].GroupLoops;
3683 // accumulate set of all subscripts in group
3684 Pair[SJ].Group |= Pair[SI].Group;
3685 Done = false;
3686 }
3687 }
3688 if (Done) {
3689 if (Pair[SI].Group.count() == 1)
3690 Separable.set(SI);
3691 else
3692 Coupled.set(SI);
3693 }
3694 }
3695 }
3696
3697 Constraint NewConstraint;
3698 NewConstraint.setAny(SE);
3699
3700 // test separable subscripts
3701 for (int SI = Separable.find_first(); SI >= 0; SI = Separable.find_next(SI)) {
3702 switch (Pair[SI].Classification) {
3703 case Subscript::SIV: {
3704 unsigned Level;
3705 const SCEV *SplitIter = NULL;
3706 (void) testSIV(Pair[SI].Src, Pair[SI].Dst, Level,
3707 Result, NewConstraint, SplitIter);
3708 if (Level == SplitLevel) {
3709 assert(SplitIter != NULL);
3710 return SplitIter;
3711 }
3712 break;
3713 }
3714 case Subscript::ZIV:
3715 case Subscript::RDIV:
3716 case Subscript::MIV:
3717 break;
3718 default:
3719 llvm_unreachable("subscript has unexpected classification");
3720 }
3721 }
3722
3723 if (Coupled.count()) {
3724 // test coupled subscript groups
3725 SmallVector<Constraint, 4> Constraints(MaxLevels + 1);
3726 for (unsigned II = 0; II <= MaxLevels; ++II)
3727 Constraints[II].setAny(SE);
3728 for (int SI = Coupled.find_first(); SI >= 0; SI = Coupled.find_next(SI)) {
3729 SmallBitVector Group(Pair[SI].Group);
3730 SmallBitVector Sivs(Pairs);
3731 SmallBitVector Mivs(Pairs);
3732 SmallBitVector ConstrainedLevels(MaxLevels + 1);
3733 for (int SJ = Group.find_first(); SJ >= 0; SJ = Group.find_next(SJ)) {
3734 if (Pair[SJ].Classification == Subscript::SIV)
3735 Sivs.set(SJ);
3736 else
3737 Mivs.set(SJ);
3738 }
3739 while (Sivs.any()) {
3740 bool Changed = false;
3741 for (int SJ = Sivs.find_first(); SJ >= 0; SJ = Sivs.find_next(SJ)) {
3742 // SJ is an SIV subscript that's part of the current coupled group
3743 unsigned Level;
3744 const SCEV *SplitIter = NULL;
3745 (void) testSIV(Pair[SJ].Src, Pair[SJ].Dst, Level,
3746 Result, NewConstraint, SplitIter);
3747 if (Level == SplitLevel && SplitIter)
3748 return SplitIter;
3749 ConstrainedLevels.set(Level);
3750 if (intersectConstraints(&Constraints[Level], &NewConstraint))
3751 Changed = true;
3752 Sivs.reset(SJ);
3753 }
3754 if (Changed) {
3755 // propagate, possibly creating new SIVs and ZIVs
3756 for (int SJ = Mivs.find_first(); SJ >= 0; SJ = Mivs.find_next(SJ)) {
3757 // SJ is an MIV subscript that's part of the current coupled group
3758 if (propagate(Pair[SJ].Src, Pair[SJ].Dst,
3759 Pair[SJ].Loops, Constraints, Result.Consistent)) {
3760 Pair[SJ].Classification =
3761 classifyPair(Pair[SJ].Src, LI->getLoopFor(Src->getParent()),
3762 Pair[SJ].Dst, LI->getLoopFor(Dst->getParent()),
3763 Pair[SJ].Loops);
3764 switch (Pair[SJ].Classification) {
3765 case Subscript::ZIV:
3766 Mivs.reset(SJ);
3767 break;
3768 case Subscript::SIV:
3769 Sivs.set(SJ);
3770 Mivs.reset(SJ);
3771 break;
3772 case Subscript::RDIV:
3773 case Subscript::MIV:
3774 break;
3775 default:
3776 llvm_unreachable("bad subscript classification");
3777 }
3778 }
3779 }
3780 }
3781 }
3782 }
3783 }
3784 llvm_unreachable("somehow reached end of routine");
3785 return NULL;
3786}