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Jessica Paquette596f4832017-03-06 21:31:18 +00001//===---- MachineOutliner.cpp - Outline instructions -----------*- 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/// \file
11/// Replaces repeated sequences of instructions with function calls.
12///
13/// This works by placing every instruction from every basic block in a
14/// suffix tree, and repeatedly querying that tree for repeated sequences of
15/// instructions. If a sequence of instructions appears often, then it ought
16/// to be beneficial to pull out into a function.
17///
18/// This was originally presented at the 2016 LLVM Developers' Meeting in the
19/// talk "Reducing Code Size Using Outlining". For a high-level overview of
20/// how this pass works, the talk is available on YouTube at
21///
22/// https://www.youtube.com/watch?v=yorld-WSOeU
23///
24/// The slides for the talk are available at
25///
26/// http://www.llvm.org/devmtg/2016-11/Slides/Paquette-Outliner.pdf
27///
28/// The talk provides an overview of how the outliner finds candidates and
29/// ultimately outlines them. It describes how the main data structure for this
30/// pass, the suffix tree, is queried and purged for candidates. It also gives
31/// a simplified suffix tree construction algorithm for suffix trees based off
32/// of the algorithm actually used here, Ukkonen's algorithm.
33///
34/// For the original RFC for this pass, please see
35///
36/// http://lists.llvm.org/pipermail/llvm-dev/2016-August/104170.html
37///
38/// For more information on the suffix tree data structure, please see
39/// https://www.cs.helsinki.fi/u/ukkonen/SuffixT1withFigs.pdf
40///
41//===----------------------------------------------------------------------===//
42#include "llvm/ADT/DenseMap.h"
43#include "llvm/ADT/Statistic.h"
44#include "llvm/ADT/Twine.h"
45#include "llvm/CodeGen/MachineFrameInfo.h"
46#include "llvm/CodeGen/MachineFunction.h"
47#include "llvm/CodeGen/MachineInstrBuilder.h"
48#include "llvm/CodeGen/MachineModuleInfo.h"
49#include "llvm/CodeGen/Passes.h"
50#include "llvm/IR/IRBuilder.h"
51#include "llvm/Support/Allocator.h"
52#include "llvm/Support/Debug.h"
53#include "llvm/Support/raw_ostream.h"
54#include "llvm/Target/TargetInstrInfo.h"
55#include "llvm/Target/TargetMachine.h"
56#include "llvm/Target/TargetRegisterInfo.h"
57#include "llvm/Target/TargetSubtargetInfo.h"
58#include <functional>
59#include <map>
60#include <sstream>
61#include <tuple>
62#include <vector>
63
64#define DEBUG_TYPE "machine-outliner"
65
66using namespace llvm;
67
68STATISTIC(NumOutlined, "Number of candidates outlined");
69STATISTIC(FunctionsCreated, "Number of functions created");
70
71namespace {
72
73/// Represents an undefined index in the suffix tree.
74const size_t EmptyIdx = -1;
75
76/// A node in a suffix tree which represents a substring or suffix.
77///
78/// Each node has either no children or at least two children, with the root
79/// being a exception in the empty tree.
80///
81/// Children are represented as a map between unsigned integers and nodes. If
82/// a node N has a child M on unsigned integer k, then the mapping represented
83/// by N is a proper prefix of the mapping represented by M. Note that this,
84/// although similar to a trie is somewhat different: each node stores a full
85/// substring of the full mapping rather than a single character state.
86///
87/// Each internal node contains a pointer to the internal node representing
88/// the same string, but with the first character chopped off. This is stored
89/// in \p Link. Each leaf node stores the start index of its respective
90/// suffix in \p SuffixIdx.
91struct SuffixTreeNode {
92
93 /// The children of this node.
94 ///
95 /// A child existing on an unsigned integer implies that from the mapping
96 /// represented by the current node, there is a way to reach another
97 /// mapping by tacking that character on the end of the current string.
98 DenseMap<unsigned, SuffixTreeNode *> Children;
99
100 /// A flag set to false if the node has been pruned from the tree.
101 bool IsInTree = true;
102
103 /// The start index of this node's substring in the main string.
104 size_t StartIdx = EmptyIdx;
105
106 /// The end index of this node's substring in the main string.
107 ///
108 /// Every leaf node must have its \p EndIdx incremented at the end of every
109 /// step in the construction algorithm. To avoid having to update O(N)
110 /// nodes individually at the end of every step, the end index is stored
111 /// as a pointer.
112 size_t *EndIdx = nullptr;
113
114 /// For leaves, the start index of the suffix represented by this node.
115 ///
116 /// For all other nodes, this is ignored.
117 size_t SuffixIdx = EmptyIdx;
118
119 /// \brief For internal nodes, a pointer to the internal node representing
120 /// the same sequence with the first character chopped off.
121 ///
122 /// This has two major purposes in the suffix tree. The first is as a
123 /// shortcut in Ukkonen's construction algorithm. One of the things that
124 /// Ukkonen's algorithm does to achieve linear-time construction is
125 /// keep track of which node the next insert should be at. This makes each
126 /// insert O(1), and there are a total of O(N) inserts. The suffix link
127 /// helps with inserting children of internal nodes.
128 ///
129 /// Say we add a child to an internal node with associated mapping S. The
130 /// next insertion must be at the node representing S - its first character.
131 /// This is given by the way that we iteratively build the tree in Ukkonen's
132 /// algorithm. The main idea is to look at the suffixes of each prefix in the
133 /// string, starting with the longest suffix of the prefix, and ending with
134 /// the shortest. Therefore, if we keep pointers between such nodes, we can
135 /// move to the next insertion point in O(1) time. If we don't, then we'd
136 /// have to query from the root, which takes O(N) time. This would make the
137 /// construction algorithm O(N^2) rather than O(N).
138 ///
139 /// The suffix link is also used during the tree pruning process to let us
140 /// quickly throw out a bunch of potential overlaps. Say we have a sequence
141 /// S we want to outline. Then each of its suffixes contribute to at least
142 /// one overlapping case. Therefore, we can follow the suffix links
143 /// starting at the node associated with S to the root and "delete" those
144 /// nodes, save for the root. For each candidate, this removes
145 /// O(|candidate|) overlaps from the search space. We don't actually
146 /// completely invalidate these nodes though; doing that is far too
147 /// aggressive. Consider the following pathological string:
148 ///
149 /// 1 2 3 1 2 3 2 3 2 3 2 3 2 3 2 3 2 3
150 ///
151 /// If we, for the sake of example, outlined 1 2 3, then we would throw
152 /// out all instances of 2 3. This isn't desirable. To get around this,
153 /// when we visit a link node, we decrement its occurrence count by the
154 /// number of sequences we outlined in the current step. In the pathological
155 /// example, the 2 3 node would have an occurrence count of 8, while the
156 /// 1 2 3 node would have an occurrence count of 2. Thus, the 2 3 node
157 /// would survive to the next round allowing us to outline the extra
158 /// instances of 2 3.
159 SuffixTreeNode *Link = nullptr;
160
161 /// The parent of this node. Every node except for the root has a parent.
162 SuffixTreeNode *Parent = nullptr;
163
164 /// The number of times this node's string appears in the tree.
165 ///
166 /// This is equal to the number of leaf children of the string. It represents
167 /// the number of suffixes that the node's string is a prefix of.
168 size_t OccurrenceCount = 0;
169
170 /// Returns true if this node is a leaf.
171 bool isLeaf() const { return SuffixIdx != EmptyIdx; }
172
173 /// Returns true if this node is the root of its owning \p SuffixTree.
174 bool isRoot() const { return StartIdx == EmptyIdx; }
175
176 /// Return the number of elements in the substring associated with this node.
177 size_t size() const {
178
179 // Is it the root? If so, it's the empty string so return 0.
180 if (isRoot())
181 return 0;
182
183 assert(*EndIdx != EmptyIdx && "EndIdx is undefined!");
184
185 // Size = the number of elements in the string.
186 // For example, [0 1 2 3] has length 4, not 3. 3-0 = 3, so we have 3-0+1.
187 return *EndIdx - StartIdx + 1;
188 }
189
190 SuffixTreeNode(size_t StartIdx, size_t *EndIdx, SuffixTreeNode *Link,
191 SuffixTreeNode *Parent)
192 : StartIdx(StartIdx), EndIdx(EndIdx), Link(Link), Parent(Parent) {}
193
194 SuffixTreeNode() {}
195};
196
197/// A data structure for fast substring queries.
198///
199/// Suffix trees represent the suffixes of their input strings in their leaves.
200/// A suffix tree is a type of compressed trie structure where each node
201/// represents an entire substring rather than a single character. Each leaf
202/// of the tree is a suffix.
203///
204/// A suffix tree can be seen as a type of state machine where each state is a
205/// substring of the full string. The tree is structured so that, for a string
206/// of length N, there are exactly N leaves in the tree. This structure allows
207/// us to quickly find repeated substrings of the input string.
208///
209/// In this implementation, a "string" is a vector of unsigned integers.
210/// These integers may result from hashing some data type. A suffix tree can
211/// contain 1 or many strings, which can then be queried as one large string.
212///
213/// The suffix tree is implemented using Ukkonen's algorithm for linear-time
214/// suffix tree construction. Ukkonen's algorithm is explained in more detail
215/// in the paper by Esko Ukkonen "On-line construction of suffix trees. The
216/// paper is available at
217///
218/// https://www.cs.helsinki.fi/u/ukkonen/SuffixT1withFigs.pdf
219class SuffixTree {
220private:
221 /// Each element is an integer representing an instruction in the module.
222 ArrayRef<unsigned> Str;
223
224 /// Maintains each node in the tree.
Jessica Paquetted4cb9c62017-03-08 23:55:33 +0000225 SpecificBumpPtrAllocator<SuffixTreeNode> NodeAllocator;
Jessica Paquette596f4832017-03-06 21:31:18 +0000226
227 /// The root of the suffix tree.
228 ///
229 /// The root represents the empty string. It is maintained by the
230 /// \p NodeAllocator like every other node in the tree.
231 SuffixTreeNode *Root = nullptr;
232
233 /// Stores each leaf in the tree for better pruning.
234 std::vector<SuffixTreeNode *> LeafVector;
235
236 /// Maintains the end indices of the internal nodes in the tree.
237 ///
238 /// Each internal node is guaranteed to never have its end index change
239 /// during the construction algorithm; however, leaves must be updated at
240 /// every step. Therefore, we need to store leaf end indices by reference
241 /// to avoid updating O(N) leaves at every step of construction. Thus,
242 /// every internal node must be allocated its own end index.
243 BumpPtrAllocator InternalEndIdxAllocator;
244
245 /// The end index of each leaf in the tree.
246 size_t LeafEndIdx = -1;
247
248 /// \brief Helper struct which keeps track of the next insertion point in
249 /// Ukkonen's algorithm.
250 struct ActiveState {
251 /// The next node to insert at.
252 SuffixTreeNode *Node;
253
254 /// The index of the first character in the substring currently being added.
255 size_t Idx = EmptyIdx;
256
257 /// The length of the substring we have to add at the current step.
258 size_t Len = 0;
259 };
260
261 /// \brief The point the next insertion will take place at in the
262 /// construction algorithm.
263 ActiveState Active;
264
265 /// Allocate a leaf node and add it to the tree.
266 ///
267 /// \param Parent The parent of this node.
268 /// \param StartIdx The start index of this node's associated string.
269 /// \param Edge The label on the edge leaving \p Parent to this node.
270 ///
271 /// \returns A pointer to the allocated leaf node.
272 SuffixTreeNode *insertLeaf(SuffixTreeNode &Parent, size_t StartIdx,
273 unsigned Edge) {
274
275 assert(StartIdx <= LeafEndIdx && "String can't start after it ends!");
276
Jessica Paquetted4cb9c62017-03-08 23:55:33 +0000277 SuffixTreeNode *N = new (NodeAllocator.Allocate()) SuffixTreeNode(StartIdx,
278 &LeafEndIdx,
279 nullptr,
280 &Parent);
Jessica Paquette596f4832017-03-06 21:31:18 +0000281 Parent.Children[Edge] = N;
282
283 return N;
284 }
285
286 /// Allocate an internal node and add it to the tree.
287 ///
288 /// \param Parent The parent of this node. Only null when allocating the root.
289 /// \param StartIdx The start index of this node's associated string.
290 /// \param EndIdx The end index of this node's associated string.
291 /// \param Edge The label on the edge leaving \p Parent to this node.
292 ///
293 /// \returns A pointer to the allocated internal node.
294 SuffixTreeNode *insertInternalNode(SuffixTreeNode *Parent, size_t StartIdx,
295 size_t EndIdx, unsigned Edge) {
296
297 assert(StartIdx <= EndIdx && "String can't start after it ends!");
298 assert(!(!Parent && StartIdx != EmptyIdx) &&
299 "Non-root internal nodes must have parents!");
300
301 size_t *E = new (InternalEndIdxAllocator) size_t(EndIdx);
Jessica Paquetted4cb9c62017-03-08 23:55:33 +0000302 SuffixTreeNode *N = new (NodeAllocator.Allocate()) SuffixTreeNode(StartIdx,
303 E,
304 Root,
305 Parent);
Jessica Paquette596f4832017-03-06 21:31:18 +0000306 if (Parent)
307 Parent->Children[Edge] = N;
308
309 return N;
310 }
311
312 /// \brief Set the suffix indices of the leaves to the start indices of their
313 /// respective suffixes. Also stores each leaf in \p LeafVector at its
314 /// respective suffix index.
315 ///
316 /// \param[in] CurrNode The node currently being visited.
317 /// \param CurrIdx The current index of the string being visited.
318 void setSuffixIndices(SuffixTreeNode &CurrNode, size_t CurrIdx) {
319
320 bool IsLeaf = CurrNode.Children.size() == 0 && !CurrNode.isRoot();
321
322 // Traverse the tree depth-first.
323 for (auto &ChildPair : CurrNode.Children) {
324 assert(ChildPair.second && "Node had a null child!");
325 setSuffixIndices(*ChildPair.second,
326 CurrIdx + ChildPair.second->size());
327 }
328
329 // Is this node a leaf?
330 if (IsLeaf) {
331 // If yes, give it a suffix index and bump its parent's occurrence count.
332 CurrNode.SuffixIdx = Str.size() - CurrIdx;
333 assert(CurrNode.Parent && "CurrNode had no parent!");
334 CurrNode.Parent->OccurrenceCount++;
335
336 // Store the leaf in the leaf vector for pruning later.
337 LeafVector[CurrNode.SuffixIdx] = &CurrNode;
338 }
339 }
340
341 /// \brief Construct the suffix tree for the prefix of the input ending at
342 /// \p EndIdx.
343 ///
344 /// Used to construct the full suffix tree iteratively. At the end of each
345 /// step, the constructed suffix tree is either a valid suffix tree, or a
346 /// suffix tree with implicit suffixes. At the end of the final step, the
347 /// suffix tree is a valid tree.
348 ///
349 /// \param EndIdx The end index of the current prefix in the main string.
350 /// \param SuffixesToAdd The number of suffixes that must be added
351 /// to complete the suffix tree at the current phase.
352 ///
353 /// \returns The number of suffixes that have not been added at the end of
354 /// this step.
355 unsigned extend(size_t EndIdx, size_t SuffixesToAdd) {
356 SuffixTreeNode *NeedsLink = nullptr;
357
358 while (SuffixesToAdd > 0) {
359
360 // Are we waiting to add anything other than just the last character?
361 if (Active.Len == 0) {
362 // If not, then say the active index is the end index.
363 Active.Idx = EndIdx;
364 }
365
366 assert(Active.Idx <= EndIdx && "Start index can't be after end index!");
367
368 // The first character in the current substring we're looking at.
369 unsigned FirstChar = Str[Active.Idx];
370
371 // Have we inserted anything starting with FirstChar at the current node?
372 if (Active.Node->Children.count(FirstChar) == 0) {
373 // If not, then we can just insert a leaf and move too the next step.
374 insertLeaf(*Active.Node, EndIdx, FirstChar);
375
376 // The active node is an internal node, and we visited it, so it must
377 // need a link if it doesn't have one.
378 if (NeedsLink) {
379 NeedsLink->Link = Active.Node;
380 NeedsLink = nullptr;
381 }
382 } else {
383 // There's a match with FirstChar, so look for the point in the tree to
384 // insert a new node.
385 SuffixTreeNode *NextNode = Active.Node->Children[FirstChar];
386
387 size_t SubstringLen = NextNode->size();
388
389 // Is the current suffix we're trying to insert longer than the size of
390 // the child we want to move to?
391 if (Active.Len >= SubstringLen) {
392 // If yes, then consume the characters we've seen and move to the next
393 // node.
394 Active.Idx += SubstringLen;
395 Active.Len -= SubstringLen;
396 Active.Node = NextNode;
397 continue;
398 }
399
400 // Otherwise, the suffix we're trying to insert must be contained in the
401 // next node we want to move to.
402 unsigned LastChar = Str[EndIdx];
403
404 // Is the string we're trying to insert a substring of the next node?
405 if (Str[NextNode->StartIdx + Active.Len] == LastChar) {
406 // If yes, then we're done for this step. Remember our insertion point
407 // and move to the next end index. At this point, we have an implicit
408 // suffix tree.
409 if (NeedsLink && !Active.Node->isRoot()) {
410 NeedsLink->Link = Active.Node;
411 NeedsLink = nullptr;
412 }
413
414 Active.Len++;
415 break;
416 }
417
418 // The string we're trying to insert isn't a substring of the next node,
419 // but matches up to a point. Split the node.
420 //
421 // For example, say we ended our search at a node n and we're trying to
422 // insert ABD. Then we'll create a new node s for AB, reduce n to just
423 // representing C, and insert a new leaf node l to represent d. This
424 // allows us to ensure that if n was a leaf, it remains a leaf.
425 //
426 // | ABC ---split---> | AB
427 // n s
428 // C / \ D
429 // n l
430
431 // The node s from the diagram
432 SuffixTreeNode *SplitNode =
433 insertInternalNode(Active.Node,
434 NextNode->StartIdx,
435 NextNode->StartIdx + Active.Len - 1,
436 FirstChar);
437
438 // Insert the new node representing the new substring into the tree as
439 // a child of the split node. This is the node l from the diagram.
440 insertLeaf(*SplitNode, EndIdx, LastChar);
441
442 // Make the old node a child of the split node and update its start
443 // index. This is the node n from the diagram.
444 NextNode->StartIdx += Active.Len;
445 NextNode->Parent = SplitNode;
446 SplitNode->Children[Str[NextNode->StartIdx]] = NextNode;
447
448 // SplitNode is an internal node, update the suffix link.
449 if (NeedsLink)
450 NeedsLink->Link = SplitNode;
451
452 NeedsLink = SplitNode;
453 }
454
455 // We've added something new to the tree, so there's one less suffix to
456 // add.
457 SuffixesToAdd--;
458
459 if (Active.Node->isRoot()) {
460 if (Active.Len > 0) {
461 Active.Len--;
462 Active.Idx = EndIdx - SuffixesToAdd + 1;
463 }
464 } else {
465 // Start the next phase at the next smallest suffix.
466 Active.Node = Active.Node->Link;
467 }
468 }
469
470 return SuffixesToAdd;
471 }
472
473 /// \brief Return the start index and length of a string which maximizes a
474 /// benefit function by traversing the tree depth-first.
475 ///
476 /// Helper function for \p bestRepeatedSubstring.
477 ///
478 /// \param CurrNode The node currently being visited.
479 /// \param CurrLen Length of the current string.
480 /// \param[out] BestLen Length of the most beneficial substring.
481 /// \param[out] MaxBenefit Benefit of the most beneficial substring.
482 /// \param[out] BestStartIdx Start index of the most beneficial substring.
483 /// \param BenefitFn The function the query should return a maximum string
484 /// for.
485 void findBest(SuffixTreeNode &CurrNode, size_t CurrLen, size_t &BestLen,
486 size_t &MaxBenefit, size_t &BestStartIdx,
487 const std::function<unsigned(SuffixTreeNode &, size_t CurrLen)>
488 &BenefitFn) {
489
490 if (!CurrNode.IsInTree)
491 return;
492
493 // Can we traverse further down the tree?
494 if (!CurrNode.isLeaf()) {
495 // If yes, continue the traversal.
496 for (auto &ChildPair : CurrNode.Children) {
497 if (ChildPair.second && ChildPair.second->IsInTree)
498 findBest(*ChildPair.second, CurrLen + ChildPair.second->size(),
499 BestLen, MaxBenefit, BestStartIdx, BenefitFn);
500 }
501 } else {
502 // We hit a leaf.
503 size_t StringLen = CurrLen - CurrNode.size();
504 unsigned Benefit = BenefitFn(CurrNode, StringLen);
505
506 // Did we do better than in the last step?
507 if (Benefit <= MaxBenefit)
508 return;
509
510 // We did better, so update the best string.
511 MaxBenefit = Benefit;
512 BestStartIdx = CurrNode.SuffixIdx;
513 BestLen = StringLen;
514 }
515 }
516
517public:
518
519 /// \brief Return a substring of the tree with maximum benefit if such a
520 /// substring exists.
521 ///
522 /// Clears the input vector and fills it with a maximum substring or empty.
523 ///
524 /// \param[in,out] Best The most beneficial substring in the tree. Empty
525 /// if it does not exist.
526 /// \param BenefitFn The function the query should return a maximum string
527 /// for.
528 void bestRepeatedSubstring(std::vector<unsigned> &Best,
529 const std::function<unsigned(SuffixTreeNode &, size_t CurrLen)>
530 &BenefitFn) {
531 Best.clear();
532 size_t Length = 0; // Becomes the length of the best substring.
533 size_t Benefit = 0; // Becomes the benefit of the best substring.
534 size_t StartIdx = 0; // Becomes the start index of the best substring.
535 findBest(*Root, 0, Length, Benefit, StartIdx, BenefitFn);
536
537 for (size_t Idx = 0; Idx < Length; Idx++)
538 Best.push_back(Str[Idx + StartIdx]);
539 }
540
541 /// Perform a depth-first search for \p QueryString on the suffix tree.
542 ///
543 /// \param QueryString The string to search for.
544 /// \param CurrIdx The current index in \p QueryString that is being matched
545 /// against.
546 /// \param CurrNode The suffix tree node being searched in.
547 ///
548 /// \returns A \p SuffixTreeNode that \p QueryString appears in if such a
549 /// node exists, and \p nullptr otherwise.
550 SuffixTreeNode *findString(const std::vector<unsigned> &QueryString,
551 size_t &CurrIdx, SuffixTreeNode *CurrNode) {
552
553 // The search ended at a nonexistent or pruned node. Quit.
554 if (!CurrNode || !CurrNode->IsInTree)
555 return nullptr;
556
557 unsigned Edge = QueryString[CurrIdx]; // The edge we want to move on.
558 SuffixTreeNode *NextNode = CurrNode->Children[Edge]; // Next node in query.
559
560 if (CurrNode->isRoot()) {
561 // If we're at the root we have to check if there's a child, and move to
562 // that child. Don't consume the character since \p Root represents the
563 // empty string.
564 if (NextNode && NextNode->IsInTree)
565 return findString(QueryString, CurrIdx, NextNode);
566 return nullptr;
567 }
568
569 size_t StrIdx = CurrNode->StartIdx;
570 size_t MaxIdx = QueryString.size();
571 bool ContinueSearching = false;
572
573 // Match as far as possible into the string. If there's a mismatch, quit.
574 for (; CurrIdx < MaxIdx; CurrIdx++, StrIdx++) {
575 Edge = QueryString[CurrIdx];
576
577 // We matched perfectly, but still have a remainder to search.
578 if (StrIdx > *(CurrNode->EndIdx)) {
579 ContinueSearching = true;
580 break;
581 }
582
583 if (Edge != Str[StrIdx])
584 return nullptr;
585 }
586
587 NextNode = CurrNode->Children[Edge];
588
589 // Move to the node which matches what we're looking for and continue
590 // searching.
591 if (ContinueSearching)
592 return findString(QueryString, CurrIdx, NextNode);
593
594 // We matched perfectly so we're done.
595 return CurrNode;
596 }
597
598 /// \brief Remove a node from a tree and all nodes representing proper
599 /// suffixes of that node's string.
600 ///
601 /// This is used in the outlining algorithm to reduce the number of
602 /// overlapping candidates
603 ///
604 /// \param N The suffix tree node to start pruning from.
605 /// \param Len The length of the string to be pruned.
606 ///
607 /// \returns True if this candidate didn't overlap with a previously chosen
608 /// candidate.
609 bool prune(SuffixTreeNode *N, size_t Len) {
610
611 bool NoOverlap = true;
612 std::vector<unsigned> IndicesToPrune;
613
614 // Look at each of N's children.
615 for (auto &ChildPair : N->Children) {
616 SuffixTreeNode *M = ChildPair.second;
617
618 // Is this a leaf child?
619 if (M && M->IsInTree && M->isLeaf()) {
620 // Save each leaf child's suffix indices and remove them from the tree.
621 IndicesToPrune.push_back(M->SuffixIdx);
622 M->IsInTree = false;
623 }
624 }
625
626 // Remove each suffix we have to prune from the tree. Each of these will be
627 // I + some offset for I in IndicesToPrune and some offset < Len.
628 unsigned Offset = 1;
629 for (unsigned CurrentSuffix = 1; CurrentSuffix < Len; CurrentSuffix++) {
630 for (unsigned I : IndicesToPrune) {
631
632 unsigned PruneIdx = I + Offset;
633
634 // Is this index actually in the string?
635 if (PruneIdx < LeafVector.size()) {
636 // If yes, we have to try and prune it.
637 // Was the current leaf already pruned by another candidate?
638 if (LeafVector[PruneIdx]->IsInTree) {
639 // If not, prune it.
640 LeafVector[PruneIdx]->IsInTree = false;
641 } else {
642 // If yes, signify that we've found an overlap, but keep pruning.
643 NoOverlap = false;
644 }
645
646 // Update the parent of the current leaf's occurrence count.
647 SuffixTreeNode *Parent = LeafVector[PruneIdx]->Parent;
648
649 // Is the parent still in the tree?
650 if (Parent->OccurrenceCount > 0) {
651 Parent->OccurrenceCount--;
652 Parent->IsInTree = (Parent->OccurrenceCount > 1);
653 }
654 }
655 }
656
657 // Move to the next character in the string.
658 Offset++;
659 }
660
661 // We know we can never outline anything which starts one index back from
662 // the indices we want to outline. This is because our minimum outlining
663 // length is always 2.
664 for (unsigned I : IndicesToPrune) {
665 if (I > 0) {
666
667 unsigned PruneIdx = I-1;
668 SuffixTreeNode *Parent = LeafVector[PruneIdx]->Parent;
669
670 // Was the leaf one index back from I already pruned?
671 if (LeafVector[PruneIdx]->IsInTree) {
672 // If not, prune it.
673 LeafVector[PruneIdx]->IsInTree = false;
674 } else {
675 // If yes, signify that we've found an overlap, but keep pruning.
676 NoOverlap = false;
677 }
678
679 // Update the parent of the current leaf's occurrence count.
680 if (Parent->OccurrenceCount > 0) {
681 Parent->OccurrenceCount--;
682 Parent->IsInTree = (Parent->OccurrenceCount > 1);
683 }
684 }
685 }
686
687 // Finally, remove N from the tree and set its occurrence count to 0.
688 N->IsInTree = false;
689 N->OccurrenceCount = 0;
690
691 return NoOverlap;
692 }
693
694 /// \brief Find each occurrence of of a string in \p QueryString and prune
695 /// their nodes.
696 ///
697 /// \param QueryString The string to search for.
698 /// \param[out] Occurrences The start indices of each occurrence.
699 ///
700 /// \returns Whether or not the occurrence overlaps with a previous candidate.
701 bool findOccurrencesAndPrune(const std::vector<unsigned> &QueryString,
702 std::vector<size_t> &Occurrences) {
703 size_t Dummy = 0;
704 SuffixTreeNode *N = findString(QueryString, Dummy, Root);
705
706 if (!N || !N->IsInTree)
707 return false;
708
709 // If this is an internal node, occurrences are the number of leaf children
710 // of the node.
711 for (auto &ChildPair : N->Children) {
712 SuffixTreeNode *M = ChildPair.second;
713
714 // Is it a leaf? If so, we have an occurrence.
715 if (M && M->IsInTree && M->isLeaf())
716 Occurrences.push_back(M->SuffixIdx);
717 }
718
719 // If we're in a leaf, then this node is the only occurrence.
720 if (N->isLeaf())
721 Occurrences.push_back(N->SuffixIdx);
722
723 return prune(N, QueryString.size());
724 }
725
726 /// Construct a suffix tree from a sequence of unsigned integers.
727 ///
728 /// \param Str The string to construct the suffix tree for.
729 SuffixTree(const std::vector<unsigned> &Str) : Str(Str) {
730 Root = insertInternalNode(nullptr, EmptyIdx, EmptyIdx, 0);
731 Root->IsInTree = true;
732 Active.Node = Root;
733 LeafVector = std::vector<SuffixTreeNode*>(Str.size());
734
735 // Keep track of the number of suffixes we have to add of the current
736 // prefix.
737 size_t SuffixesToAdd = 0;
738 Active.Node = Root;
739
740 // Construct the suffix tree iteratively on each prefix of the string.
741 // PfxEndIdx is the end index of the current prefix.
742 // End is one past the last element in the string.
743 for (size_t PfxEndIdx = 0, End = Str.size(); PfxEndIdx < End; PfxEndIdx++) {
744 SuffixesToAdd++;
745 LeafEndIdx = PfxEndIdx; // Extend each of the leaves.
746 SuffixesToAdd = extend(PfxEndIdx, SuffixesToAdd);
747 }
748
749 // Set the suffix indices of each leaf.
750 assert(Root && "Root node can't be nullptr!");
751 setSuffixIndices(*Root, 0);
752 }
753};
754
755/// \brief An individual sequence of instructions to be replaced with a call to
756/// an outlined function.
757struct Candidate {
758
759 /// Set to false if the candidate overlapped with another candidate.
760 bool InCandidateList = true;
761
762 /// The start index of this \p Candidate.
763 size_t StartIdx;
764
765 /// The number of instructions in this \p Candidate.
766 size_t Len;
767
768 /// The index of this \p Candidate's \p OutlinedFunction in the list of
769 /// \p OutlinedFunctions.
770 size_t FunctionIdx;
771
772 Candidate(size_t StartIdx, size_t Len, size_t FunctionIdx)
773 : StartIdx(StartIdx), Len(Len), FunctionIdx(FunctionIdx) {}
774
775 Candidate() {}
776
777 /// \brief Used to ensure that \p Candidates are outlined in an order that
778 /// preserves the start and end indices of other \p Candidates.
779 bool operator<(const Candidate &RHS) const { return StartIdx > RHS.StartIdx; }
780};
781
782/// \brief The information necessary to create an outlined function for some
783/// class of candidate.
784struct OutlinedFunction {
785
786 /// The actual outlined function created.
787 /// This is initialized after we go through and create the actual function.
788 MachineFunction *MF = nullptr;
789
790 /// A number assigned to this function which appears at the end of its name.
791 size_t Name;
792
793 /// The number of times that this function has appeared.
794 size_t OccurrenceCount = 0;
795
796 /// \brief The sequence of integers corresponding to the instructions in this
797 /// function.
798 std::vector<unsigned> Sequence;
799
800 /// The number of instructions this function would save.
801 unsigned Benefit = 0;
802
803 OutlinedFunction(size_t Name, size_t OccurrenceCount,
804 const std::vector<unsigned> &Sequence,
805 unsigned Benefit)
806 : Name(Name), OccurrenceCount(OccurrenceCount), Sequence(Sequence),
807 Benefit(Benefit)
808 {}
809};
810
811/// \brief Maps \p MachineInstrs to unsigned integers and stores the mappings.
812struct InstructionMapper {
813
814 /// \brief The next available integer to assign to a \p MachineInstr that
815 /// cannot be outlined.
816 ///
817 /// Set to -3 for compatability with \p DenseMapInfo<unsigned>.
818 unsigned IllegalInstrNumber = -3;
819
820 /// \brief The next available integer to assign to a \p MachineInstr that can
821 /// be outlined.
822 unsigned LegalInstrNumber = 0;
823
824 /// Correspondence from \p MachineInstrs to unsigned integers.
825 DenseMap<MachineInstr *, unsigned, MachineInstrExpressionTrait>
826 InstructionIntegerMap;
827
828 /// Corresponcence from unsigned integers to \p MachineInstrs.
829 /// Inverse of \p InstructionIntegerMap.
830 DenseMap<unsigned, MachineInstr *> IntegerInstructionMap;
831
832 /// The vector of unsigned integers that the module is mapped to.
833 std::vector<unsigned> UnsignedVec;
834
835 /// \brief Stores the location of the instruction associated with the integer
836 /// at index i in \p UnsignedVec for each index i.
837 std::vector<MachineBasicBlock::iterator> InstrList;
838
839 /// \brief Maps \p *It to a legal integer.
840 ///
841 /// Updates \p InstrList, \p UnsignedVec, \p InstructionIntegerMap,
842 /// \p IntegerInstructionMap, and \p LegalInstrNumber.
843 ///
844 /// \returns The integer that \p *It was mapped to.
845 unsigned mapToLegalUnsigned(MachineBasicBlock::iterator &It) {
846
847 // Get the integer for this instruction or give it the current
848 // LegalInstrNumber.
849 InstrList.push_back(It);
850 MachineInstr &MI = *It;
851 bool WasInserted;
852 DenseMap<MachineInstr *, unsigned, MachineInstrExpressionTrait>::iterator
853 ResultIt;
854 std::tie(ResultIt, WasInserted) =
855 InstructionIntegerMap.insert(std::make_pair(&MI, LegalInstrNumber));
856 unsigned MINumber = ResultIt->second;
857
858 // There was an insertion.
859 if (WasInserted) {
860 LegalInstrNumber++;
861 IntegerInstructionMap.insert(std::make_pair(MINumber, &MI));
862 }
863
864 UnsignedVec.push_back(MINumber);
865
866 // Make sure we don't overflow or use any integers reserved by the DenseMap.
867 if (LegalInstrNumber >= IllegalInstrNumber)
868 report_fatal_error("Instruction mapping overflow!");
869
870 assert(LegalInstrNumber != DenseMapInfo<unsigned>::getEmptyKey()
871 && "Tried to assign DenseMap tombstone or empty key to instruction.");
872 assert(LegalInstrNumber != DenseMapInfo<unsigned>::getTombstoneKey()
873 && "Tried to assign DenseMap tombstone or empty key to instruction.");
874
875 return MINumber;
876 }
877
878 /// Maps \p *It to an illegal integer.
879 ///
880 /// Updates \p InstrList, \p UnsignedVec, and \p IllegalInstrNumber.
881 ///
882 /// \returns The integer that \p *It was mapped to.
883 unsigned mapToIllegalUnsigned(MachineBasicBlock::iterator &It) {
884 unsigned MINumber = IllegalInstrNumber;
885
886 InstrList.push_back(It);
887 UnsignedVec.push_back(IllegalInstrNumber);
888 IllegalInstrNumber--;
889
890 assert(LegalInstrNumber < IllegalInstrNumber &&
891 "Instruction mapping overflow!");
892
893 assert(IllegalInstrNumber !=
894 DenseMapInfo<unsigned>::getEmptyKey() &&
895 "IllegalInstrNumber cannot be DenseMap tombstone or empty key!");
896
897 assert(IllegalInstrNumber !=
898 DenseMapInfo<unsigned>::getTombstoneKey() &&
899 "IllegalInstrNumber cannot be DenseMap tombstone or empty key!");
900
901 return MINumber;
902 }
903
904 /// \brief Transforms a \p MachineBasicBlock into a \p vector of \p unsigneds
905 /// and appends it to \p UnsignedVec and \p InstrList.
906 ///
907 /// Two instructions are assigned the same integer if they are identical.
908 /// If an instruction is deemed unsafe to outline, then it will be assigned an
909 /// unique integer. The resulting mapping is placed into a suffix tree and
910 /// queried for candidates.
911 ///
912 /// \param MBB The \p MachineBasicBlock to be translated into integers.
913 /// \param TRI \p TargetRegisterInfo for the module.
914 /// \param TII \p TargetInstrInfo for the module.
915 void convertToUnsignedVec(MachineBasicBlock &MBB,
916 const TargetRegisterInfo &TRI,
917 const TargetInstrInfo &TII) {
918 for (MachineBasicBlock::iterator It = MBB.begin(), Et = MBB.end(); It != Et;
919 It++) {
920
921 // Keep track of where this instruction is in the module.
922 switch(TII.getOutliningType(*It)) {
923 case TargetInstrInfo::MachineOutlinerInstrType::Illegal:
924 mapToIllegalUnsigned(It);
925 break;
926
927 case TargetInstrInfo::MachineOutlinerInstrType::Legal:
928 mapToLegalUnsigned(It);
929 break;
930
931 case TargetInstrInfo::MachineOutlinerInstrType::Invisible:
932 break;
933 }
934 }
935
936 // After we're done every insertion, uniquely terminate this part of the
937 // "string". This makes sure we won't match across basic block or function
938 // boundaries since the "end" is encoded uniquely and thus appears in no
939 // repeated substring.
940 InstrList.push_back(MBB.end());
941 UnsignedVec.push_back(IllegalInstrNumber);
942 IllegalInstrNumber--;
943 }
944
945 InstructionMapper() {
946 // Make sure that the implementation of DenseMapInfo<unsigned> hasn't
947 // changed.
948 assert(DenseMapInfo<unsigned>::getEmptyKey() == (unsigned)-1 &&
949 "DenseMapInfo<unsigned>'s empty key isn't -1!");
950 assert(DenseMapInfo<unsigned>::getTombstoneKey() == (unsigned)-2 &&
951 "DenseMapInfo<unsigned>'s tombstone key isn't -2!");
952 }
953};
954
955/// \brief An interprocedural pass which finds repeated sequences of
956/// instructions and replaces them with calls to functions.
957///
958/// Each instruction is mapped to an unsigned integer and placed in a string.
959/// The resulting mapping is then placed in a \p SuffixTree. The \p SuffixTree
960/// is then repeatedly queried for repeated sequences of instructions. Each
961/// non-overlapping repeated sequence is then placed in its own
962/// \p MachineFunction and each instance is then replaced with a call to that
963/// function.
964struct MachineOutliner : public ModulePass {
965
966 static char ID;
967
968 StringRef getPassName() const override { return "Machine Outliner"; }
969
970 void getAnalysisUsage(AnalysisUsage &AU) const override {
971 AU.addRequired<MachineModuleInfo>();
972 AU.addPreserved<MachineModuleInfo>();
973 AU.setPreservesAll();
974 ModulePass::getAnalysisUsage(AU);
975 }
976
977 MachineOutliner() : ModulePass(ID) {
978 initializeMachineOutlinerPass(*PassRegistry::getPassRegistry());
979 }
980
981 /// \brief Replace the sequences of instructions represented by the
982 /// \p Candidates in \p CandidateList with calls to \p MachineFunctions
983 /// described in \p FunctionList.
984 ///
985 /// \param M The module we are outlining from.
986 /// \param CandidateList A list of candidates to be outlined.
987 /// \param FunctionList A list of functions to be inserted into the module.
988 /// \param Mapper Contains the instruction mappings for the module.
989 bool outline(Module &M, const ArrayRef<Candidate> &CandidateList,
990 std::vector<OutlinedFunction> &FunctionList,
991 InstructionMapper &Mapper);
992
993 /// Creates a function for \p OF and inserts it into the module.
994 MachineFunction *createOutlinedFunction(Module &M, const OutlinedFunction &OF,
995 InstructionMapper &Mapper);
996
997 /// Find potential outlining candidates and store them in \p CandidateList.
998 ///
999 /// For each type of potential candidate, also build an \p OutlinedFunction
1000 /// struct containing the information to build the function for that
1001 /// candidate.
1002 ///
1003 /// \param[out] CandidateList Filled with outlining candidates for the module.
1004 /// \param[out] FunctionList Filled with functions corresponding to each type
1005 /// of \p Candidate.
1006 /// \param ST The suffix tree for the module.
1007 /// \param TII TargetInstrInfo for the module.
1008 ///
1009 /// \returns The length of the longest candidate found. 0 if there are none.
1010 unsigned buildCandidateList(std::vector<Candidate> &CandidateList,
1011 std::vector<OutlinedFunction> &FunctionList,
1012 SuffixTree &ST, const TargetInstrInfo &TII);
1013
1014 /// \brief Remove any overlapping candidates that weren't handled by the
1015 /// suffix tree's pruning method.
1016 ///
1017 /// Pruning from the suffix tree doesn't necessarily remove all overlaps.
1018 /// If a short candidate is chosen for outlining, then a longer candidate
1019 /// which has that short candidate as a suffix is chosen, the tree's pruning
1020 /// method will not find it. Thus, we need to prune before outlining as well.
1021 ///
1022 /// \param[in,out] CandidateList A list of outlining candidates.
1023 /// \param[in,out] FunctionList A list of functions to be outlined.
1024 /// \param MaxCandidateLen The length of the longest candidate.
1025 /// \param TII TargetInstrInfo for the module.
1026 void pruneOverlaps(std::vector<Candidate> &CandidateList,
1027 std::vector<OutlinedFunction> &FunctionList,
1028 unsigned MaxCandidateLen,
1029 const TargetInstrInfo &TII);
1030
1031 /// Construct a suffix tree on the instructions in \p M and outline repeated
1032 /// strings from that tree.
1033 bool runOnModule(Module &M) override;
1034};
1035
1036} // Anonymous namespace.
1037
1038char MachineOutliner::ID = 0;
1039
1040namespace llvm {
1041ModulePass *createMachineOutlinerPass() { return new MachineOutliner(); }
1042}
1043
1044INITIALIZE_PASS(MachineOutliner, "machine-outliner",
1045 "Machine Function Outliner", false, false)
1046
1047void MachineOutliner::pruneOverlaps(std::vector<Candidate> &CandidateList,
1048 std::vector<OutlinedFunction> &FunctionList,
1049 unsigned MaxCandidateLen,
1050 const TargetInstrInfo &TII) {
1051
1052 // Check for overlaps in the range. This is O(n^2) worst case, but we can
1053 // alleviate that somewhat by bounding our search space using the start
1054 // index of our first candidate and the maximum distance an overlapping
1055 // candidate could have from the first candidate.
1056 for (auto It = CandidateList.begin(), Et = CandidateList.end(); It != Et;
1057 It++) {
1058 Candidate &C1 = *It;
1059 OutlinedFunction &F1 = FunctionList[C1.FunctionIdx];
1060
1061 // If we removed this candidate, skip it.
1062 if (!C1.InCandidateList)
1063 continue;
1064
1065 // If the candidate's function isn't good to outline anymore, then
1066 // remove the candidate and skip it.
1067 if (F1.OccurrenceCount < 2 || F1.Benefit < 1) {
1068 C1.InCandidateList = false;
1069 continue;
1070 }
1071
1072 // The minimum start index of any candidate that could overlap with this
1073 // one.
1074 unsigned FarthestPossibleIdx = 0;
1075
1076 // Either the index is 0, or it's at most MaxCandidateLen indices away.
1077 if (C1.StartIdx > MaxCandidateLen)
1078 FarthestPossibleIdx = C1.StartIdx - MaxCandidateLen;
1079
1080 // Compare against the other candidates in the list.
1081 // This is at most MaxCandidateLen/2 other candidates.
1082 // This is because each candidate has to be at least 2 indices away.
1083 // = O(n * MaxCandidateLen/2) comparisons
1084 //
1085 // On average, the maximum length of a candidate is quite small; a fraction
1086 // of the total module length in terms of instructions. If the maximum
1087 // candidate length is large, then there are fewer possible candidates to
1088 // compare against in the first place.
1089 for (auto Sit = It + 1; Sit != Et; Sit++) {
1090 Candidate &C2 = *Sit;
1091 OutlinedFunction &F2 = FunctionList[C2.FunctionIdx];
1092
1093 // Is this candidate too far away to overlap?
1094 // NOTE: This will be true in
1095 // O(max(FarthestPossibleIdx/2, #Candidates remaining)) steps
1096 // for every candidate.
1097 if (C2.StartIdx < FarthestPossibleIdx)
1098 break;
1099
1100 // Did we already remove this candidate in a previous step?
1101 if (!C2.InCandidateList)
1102 continue;
1103
1104 // Is the function beneficial to outline?
1105 if (F2.OccurrenceCount < 2 || F2.Benefit < 1) {
1106 // If not, remove this candidate and move to the next one.
1107 C2.InCandidateList = false;
1108 continue;
1109 }
1110
1111 size_t C2End = C2.StartIdx + C2.Len - 1;
1112
1113 // Do C1 and C2 overlap?
1114 //
1115 // Not overlapping:
1116 // High indices... [C1End ... C1Start][C2End ... C2Start] ...Low indices
1117 //
1118 // We sorted our candidate list so C2Start <= C1Start. We know that
1119 // C2End > C2Start since each candidate has length >= 2. Therefore, all we
1120 // have to check is C2End < C2Start to see if we overlap.
1121 if (C2End < C1.StartIdx)
1122 continue;
1123
1124 // C2 overlaps with C1. Because we pruned the tree already, the only way
1125 // this can happen is if C1 is a proper suffix of C2. Thus, we must have
1126 // found C1 first during our query, so it must have benefit greater or
1127 // equal to C2. Greedily pick C1 as the candidate to keep and toss out C2.
1128 DEBUG (
1129 size_t C1End = C1.StartIdx + C1.Len - 1;
1130 dbgs() << "- Found an overlap to purge.\n";
1131 dbgs() << "--- C1 :[" << C1.StartIdx << ", " << C1End << "]\n";
1132 dbgs() << "--- C2 :[" << C2.StartIdx << ", " << C2End << "]\n";
1133 );
1134
1135 // Update the function's occurrence count and benefit to reflec that C2
1136 // is being removed.
1137 F2.OccurrenceCount--;
1138 F2.Benefit = TII.getOutliningBenefit(F2.Sequence.size(),
1139 F2.OccurrenceCount
1140 );
1141
1142 // Mark C2 as not in the list.
1143 C2.InCandidateList = false;
1144
1145 DEBUG (
1146 dbgs() << "- Removed C2. \n";
1147 dbgs() << "--- Num fns left for C2: " << F2.OccurrenceCount << "\n";
1148 dbgs() << "--- C2's benefit: " << F2.Benefit << "\n";
1149 );
1150 }
1151 }
1152}
1153
1154unsigned
1155MachineOutliner::buildCandidateList(std::vector<Candidate> &CandidateList,
1156 std::vector<OutlinedFunction> &FunctionList,
1157 SuffixTree &ST,
1158 const TargetInstrInfo &TII) {
1159
1160 std::vector<unsigned> CandidateSequence; // Current outlining candidate.
1161 unsigned MaxCandidateLen = 0; // Length of the longest candidate.
1162
1163 // Function for maximizing query in the suffix tree.
1164 // This allows us to define more fine-grained types of things to outline in
1165 // the target without putting target-specific info in the suffix tree.
1166 auto BenefitFn = [&TII](const SuffixTreeNode &Curr, size_t StringLen) {
1167
1168 // Any leaf whose parent is the root only has one occurrence.
1169 if (Curr.Parent->isRoot())
1170 return 0u;
1171
1172 // Anything with length < 2 will never be beneficial on any target.
1173 if (StringLen < 2)
1174 return 0u;
1175
1176 size_t Occurrences = Curr.Parent->OccurrenceCount;
1177
1178 // Anything with fewer than 2 occurrences will never be beneficial on any
1179 // target.
1180 if (Occurrences < 2)
1181 return 0u;
1182
1183 return TII.getOutliningBenefit(StringLen, Occurrences);
1184 };
1185
1186 // Repeatedly query the suffix tree for the substring that maximizes
1187 // BenefitFn. Find the occurrences of that string, prune the tree, and store
1188 // each occurrence as a candidate.
1189 for (ST.bestRepeatedSubstring(CandidateSequence, BenefitFn);
1190 CandidateSequence.size() > 1;
1191 ST.bestRepeatedSubstring(CandidateSequence, BenefitFn)) {
1192
1193 std::vector<size_t> Occurrences;
1194
1195 bool GotNonOverlappingCandidate =
1196 ST.findOccurrencesAndPrune(CandidateSequence, Occurrences);
1197
1198 // Is the candidate we found known to overlap with something we already
1199 // outlined?
1200 if (!GotNonOverlappingCandidate)
1201 continue;
1202
1203 // Is this candidate the longest so far?
1204 if (CandidateSequence.size() > MaxCandidateLen)
1205 MaxCandidateLen = CandidateSequence.size();
1206
1207 // Keep track of the benefit of outlining this candidate in its
1208 // OutlinedFunction.
1209 unsigned FnBenefit = TII.getOutliningBenefit(CandidateSequence.size(),
1210 Occurrences.size()
1211 );
1212
1213 assert(FnBenefit > 0 && "Function cannot be unbeneficial!");
1214
1215 // Save an OutlinedFunction for this candidate.
1216 FunctionList.emplace_back(
1217 FunctionList.size(), // Number of this function.
1218 Occurrences.size(), // Number of occurrences.
1219 CandidateSequence, // Sequence to outline.
1220 FnBenefit // Instructions saved by outlining this function.
1221 );
1222
1223 // Save each of the occurrences of the candidate so we can outline them.
1224 for (size_t &Occ : Occurrences)
1225 CandidateList.emplace_back(
1226 Occ, // Starting idx in that MBB.
1227 CandidateSequence.size(), // Candidate length.
1228 FunctionList.size() - 1 // Idx of the corresponding function.
1229 );
1230
1231 FunctionsCreated++;
1232 }
1233
1234 // Sort the candidates in decending order. This will simplify the outlining
1235 // process when we have to remove the candidates from the mapping by
1236 // allowing us to cut them out without keeping track of an offset.
1237 std::stable_sort(CandidateList.begin(), CandidateList.end());
1238
1239 return MaxCandidateLen;
1240}
1241
1242MachineFunction *
1243MachineOutliner::createOutlinedFunction(Module &M, const OutlinedFunction &OF,
1244 InstructionMapper &Mapper) {
1245
1246 // Create the function name. This should be unique. For now, just hash the
1247 // module name and include it in the function name plus the number of this
1248 // function.
1249 std::ostringstream NameStream;
1250 NameStream << "OUTLINED_FUNCTION" << "_" << OF.Name;
1251
1252 // Create the function using an IR-level function.
1253 LLVMContext &C = M.getContext();
1254 Function *F = dyn_cast<Function>(
1255 M.getOrInsertFunction(NameStream.str(), Type::getVoidTy(C), NULL));
1256 assert(F && "Function was null!");
1257
1258 // NOTE: If this is linkonceodr, then we can take advantage of linker deduping
1259 // which gives us better results when we outline from linkonceodr functions.
1260 F->setLinkage(GlobalValue::PrivateLinkage);
1261 F->setUnnamedAddr(GlobalValue::UnnamedAddr::Global);
1262
1263 BasicBlock *EntryBB = BasicBlock::Create(C, "entry", F);
1264 IRBuilder<> Builder(EntryBB);
1265 Builder.CreateRetVoid();
1266
1267 MachineModuleInfo &MMI = getAnalysis<MachineModuleInfo>();
1268 MachineFunction &MF = MMI.getMachineFunction(*F);
1269 MachineBasicBlock &MBB = *MF.CreateMachineBasicBlock();
1270 const TargetSubtargetInfo &STI = MF.getSubtarget();
1271 const TargetInstrInfo &TII = *STI.getInstrInfo();
1272
1273 // Insert the new function into the module.
1274 MF.insert(MF.begin(), &MBB);
1275
1276 TII.insertOutlinerPrologue(MBB, MF);
1277
1278 // Copy over the instructions for the function using the integer mappings in
1279 // its sequence.
1280 for (unsigned Str : OF.Sequence) {
1281 MachineInstr *NewMI =
1282 MF.CloneMachineInstr(Mapper.IntegerInstructionMap.find(Str)->second);
1283 NewMI->dropMemRefs();
1284
1285 // Don't keep debug information for outlined instructions.
1286 // FIXME: This means outlined functions are currently undebuggable.
1287 NewMI->setDebugLoc(DebugLoc());
1288 MBB.insert(MBB.end(), NewMI);
1289 }
1290
1291 TII.insertOutlinerEpilogue(MBB, MF);
1292
1293 return &MF;
1294}
1295
1296bool MachineOutliner::outline(Module &M,
1297 const ArrayRef<Candidate> &CandidateList,
1298 std::vector<OutlinedFunction> &FunctionList,
1299 InstructionMapper &Mapper) {
1300
1301 bool OutlinedSomething = false;
1302
1303 // Replace the candidates with calls to their respective outlined functions.
1304 for (const Candidate &C : CandidateList) {
1305
1306 // Was the candidate removed during pruneOverlaps?
1307 if (!C.InCandidateList)
1308 continue;
1309
1310 // If not, then look at its OutlinedFunction.
1311 OutlinedFunction &OF = FunctionList[C.FunctionIdx];
1312
1313 // Was its OutlinedFunction made unbeneficial during pruneOverlaps?
1314 if (OF.OccurrenceCount < 2 || OF.Benefit < 1)
1315 continue;
1316
1317 // If not, then outline it.
1318 assert(C.StartIdx < Mapper.InstrList.size() && "Candidate out of bounds!");
1319 MachineBasicBlock *MBB = (*Mapper.InstrList[C.StartIdx]).getParent();
1320 MachineBasicBlock::iterator StartIt = Mapper.InstrList[C.StartIdx];
1321 unsigned EndIdx = C.StartIdx + C.Len - 1;
1322
1323 assert(EndIdx < Mapper.InstrList.size() && "Candidate out of bounds!");
1324 MachineBasicBlock::iterator EndIt = Mapper.InstrList[EndIdx];
1325 assert(EndIt != MBB->end() && "EndIt out of bounds!");
1326
1327 EndIt++; // Erase needs one past the end index.
1328
1329 // Does this candidate have a function yet?
1330 if (!OF.MF)
1331 OF.MF = createOutlinedFunction(M, OF, Mapper);
1332
1333 MachineFunction *MF = OF.MF;
1334 const TargetSubtargetInfo &STI = MF->getSubtarget();
1335 const TargetInstrInfo &TII = *STI.getInstrInfo();
1336
1337 // Insert a call to the new function and erase the old sequence.
1338 TII.insertOutlinedCall(M, *MBB, StartIt, *MF);
1339 StartIt = Mapper.InstrList[C.StartIdx];
1340 MBB->erase(StartIt, EndIt);
1341
1342 OutlinedSomething = true;
1343
1344 // Statistics.
1345 NumOutlined++;
1346 }
1347
1348 DEBUG (
1349 dbgs() << "OutlinedSomething = " << OutlinedSomething << "\n";
1350 );
1351
1352 return OutlinedSomething;
1353}
1354
1355bool MachineOutliner::runOnModule(Module &M) {
1356
1357 // Is there anything in the module at all?
1358 if (M.empty())
1359 return false;
1360
1361 MachineModuleInfo &MMI = getAnalysis<MachineModuleInfo>();
1362 const TargetSubtargetInfo &STI = MMI.getMachineFunction(*M.begin())
1363 .getSubtarget();
1364 const TargetRegisterInfo *TRI = STI.getRegisterInfo();
1365 const TargetInstrInfo *TII = STI.getInstrInfo();
1366
1367 InstructionMapper Mapper;
1368
1369 // Build instruction mappings for each function in the module.
1370 for (Function &F : M) {
1371 MachineFunction &MF = MMI.getMachineFunction(F);
1372
1373 // Is the function empty? Safe to outline from?
1374 if (F.empty() || !TII->isFunctionSafeToOutlineFrom(MF))
1375 continue;
1376
1377 // If it is, look at each MachineBasicBlock in the function.
1378 for (MachineBasicBlock &MBB : MF) {
1379
1380 // Is there anything in MBB?
1381 if (MBB.empty())
1382 continue;
1383
1384 // If yes, map it.
1385 Mapper.convertToUnsignedVec(MBB, *TRI, *TII);
1386 }
1387 }
1388
1389 // Construct a suffix tree, use it to find candidates, and then outline them.
1390 SuffixTree ST(Mapper.UnsignedVec);
1391 std::vector<Candidate> CandidateList;
1392 std::vector<OutlinedFunction> FunctionList;
1393
1394 unsigned MaxCandidateLen =
1395 buildCandidateList(CandidateList, FunctionList, ST, *TII);
1396
1397 pruneOverlaps(CandidateList, FunctionList, MaxCandidateLen, *TII);
1398 return outline(M, CandidateList, FunctionList, Mapper);
1399}