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llvm-mirror/lib/Transforms/IPO/Inliner.cpp

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//===- Inliner.cpp - Code common to all inliners --------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// This file implements the mechanics required to implement inlining without
// missing any calls and updating the call graph. The decisions of which calls
// are profitable to inline are implemented elsewhere.
//
//===----------------------------------------------------------------------===//
#include "llvm/Transforms/IPO/InlinerPass.h"
#include "llvm/ADT/SmallPtrSet.h"
#include "llvm/ADT/Statistic.h"
#include "llvm/Analysis/AliasAnalysis.h"
#include "llvm/Analysis/AssumptionCache.h"
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-09 19:55:00 +02:00
#include "llvm/Analysis/BasicAliasAnalysis.h"
#include "llvm/Analysis/BlockFrequencyInfo.h"
#include "llvm/Analysis/CallGraph.h"
#include "llvm/Analysis/InlineCost.h"
#include "llvm/Analysis/TargetLibraryInfo.h"
#include "llvm/IR/CallSite.h"
#include "llvm/IR/DataLayout.h"
#include "llvm/IR/DiagnosticInfo.h"
#include "llvm/IR/Instructions.h"
#include "llvm/IR/IntrinsicInst.h"
#include "llvm/IR/Module.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Transforms/Utils/Cloning.h"
#include "llvm/Transforms/Utils/Local.h"
using namespace llvm;
#define DEBUG_TYPE "inline"
STATISTIC(NumInlined, "Number of functions inlined");
STATISTIC(NumCallsDeleted, "Number of call sites deleted, not inlined");
STATISTIC(NumDeleted, "Number of functions deleted because all callers found");
STATISTIC(NumMergedAllocas, "Number of allocas merged together");
// This weirdly named statistic tracks the number of times that, when attempting
// to inline a function A into B, we analyze the callers of B in order to see
// if those would be more profitable and blocked inline steps.
STATISTIC(NumCallerCallersAnalyzed, "Number of caller-callers analyzed");
Inliner::Inliner(char &ID)
: CallGraphSCCPass(ID), InsertLifetime(true),
BFA(new BlockFrequencyAnalysis()) {}
Inliner::Inliner(char &ID, bool InsertLifetime)
: CallGraphSCCPass(ID), InsertLifetime(InsertLifetime),
BFA(new BlockFrequencyAnalysis()) {}
/// For this class, we declare that we require and preserve the call graph.
/// If the derived class implements this method, it should
/// always explicitly call the implementation here.
void Inliner::getAnalysisUsage(AnalysisUsage &AU) const {
AU.addRequired<AssumptionCacheTracker>();
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-09 19:55:00 +02:00
AU.addRequired<TargetLibraryInfoWrapperPass>();
[AA] Hoist the logic to reformulate various AA queries in terms of other parts of the AA interface out of the base class of every single AA result object. Because this logic reformulates the query in terms of some other aspect of the API, it would easily cause O(n^2) query patterns in alias analysis. These could in turn be magnified further based on the number of call arguments, and then further based on the number of AA queries made for a particular call. This ended up causing problems for Rust that were actually noticable enough to get a bug (PR26564) and probably other places as well. When originally re-working the AA infrastructure, the desire was to regularize the pattern of refinement without losing any generality. While I think it was successful, that is clearly proving to be too costly. And the cost is needless: we gain no actual improvement for this generality of making a direct query to tbaa actually be able to re-use some other alias analysis's refinement logic for one of the other APIs, or some such. In short, this is entirely wasted work. To the extent possible, delegation to other API surfaces should be done at the aggregation layer so that we can avoid re-walking the aggregation. In fact, this significantly simplifies the logic as we no longer need to smuggle the aggregation layer into each alias analysis (or the TargetLibraryInfo into each alias analysis just so we can form argument memory locations!). However, we also have some delegation logic inside of BasicAA and some of it even makes sense. When the delegation logic is baking in specific knowledge of aliasing properties of the LLVM IR, as opposed to simply reformulating the query to utilize a different alias analysis interface entry point, it makes a lot of sense to restrict that logic to a different layer such as BasicAA. So one aspect of the delegation that was in every AA base class is that when we don't have operand bundles, we re-use function AA results as a fallback for callsite alias results. This relies on the IR properties of calls and functions w.r.t. aliasing, and so seems a better fit to BasicAA. I've lifted the logic up to that point where it seems to be a natural fit. This still does a bit of redundant work (we query function attributes twice, once via the callsite and once via the function AA query) but it is *exactly* twice here, no more. The end result is that all of the delegation logic is hoisted out of the base class and into either the aggregation layer when it is a pure retargeting to a different API surface, or into BasicAA when it relies on the IR's aliasing properties. This should fix the quadratic query pattern reported in PR26564, although I don't have a stand-alone test case to reproduce it. It also seems general goodness. Now the numerous AAs that don't need target library info don't carry it around and depend on it. I think I can even rip out the general access to the aggregation layer and only expose that in BasicAA as it is the only place where we re-query in that manner. However, this is a non-trivial change to the AA infrastructure so I want to get some additional eyes on this before it lands. Sadly, it can't wait long because we should really cherry pick this into 3.8 if we're going to go this route. Differential Revision: http://reviews.llvm.org/D17329 llvm-svn: 262490
2016-03-02 16:56:53 +01:00
getAAResultsAnalysisUsage(AU);
CallGraphSCCPass::getAnalysisUsage(AU);
}
typedef DenseMap<ArrayType*, std::vector<AllocaInst*> >
InlinedArrayAllocasTy;
/// If it is possible to inline the specified call site,
/// do so and update the CallGraph for this operation.
///
/// This function also does some basic book-keeping to update the IR. The
/// InlinedArrayAllocas map keeps track of any allocas that are already
/// available from other functions inlined into the caller. If we are able to
/// inline this call site we attempt to reuse already available allocas or add
/// any new allocas to the set if not possible.
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-09 19:55:00 +02:00
static bool InlineCallIfPossible(Pass &P, CallSite CS, InlineFunctionInfo &IFI,
InlinedArrayAllocasTy &InlinedArrayAllocas,
int InlineHistory, bool InsertLifetime) {
Function *Callee = CS.getCalledFunction();
Function *Caller = CS.getCaller();
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-09 19:55:00 +02:00
// We need to manually construct BasicAA directly in order to disable
// its use of other function analyses.
BasicAAResult BAR(createLegacyPMBasicAAResult(P, *Callee));
// Construct our own AA results for this function. We do this manually to
// work around the limitations of the legacy pass manager.
AAResults AAR(createLegacyPMAAResults(P, *Callee, BAR));
// Try to inline the function. Get the list of static allocas that were
// inlined.
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-09 19:55:00 +02:00
if (!InlineFunction(CS, IFI, &AAR, InsertLifetime))
return false;
AttributeFuncs::mergeAttributesForInlining(*Caller, *Callee);
// Look at all of the allocas that we inlined through this call site. If we
// have already inlined other allocas through other calls into this function,
// then we know that they have disjoint lifetimes and that we can merge them.
//
// There are many heuristics possible for merging these allocas, and the
// different options have different tradeoffs. One thing that we *really*
// don't want to hurt is SRoA: once inlining happens, often allocas are no
// longer address taken and so they can be promoted.
//
// Our "solution" for that is to only merge allocas whose outermost type is an
// array type. These are usually not promoted because someone is using a
// variable index into them. These are also often the most important ones to
// merge.
//
// A better solution would be to have real memory lifetime markers in the IR
// and not have the inliner do any merging of allocas at all. This would
// allow the backend to do proper stack slot coloring of all allocas that
// *actually make it to the backend*, which is really what we want.
//
// Because we don't have this information, we do this simple and useful hack.
//
SmallPtrSet<AllocaInst*, 16> UsedAllocas;
// When processing our SCC, check to see if CS was inlined from some other
// call site. For example, if we're processing "A" in this code:
// A() { B() }
// B() { x = alloca ... C() }
// C() { y = alloca ... }
// Assume that C was not inlined into B initially, and so we're processing A
// and decide to inline B into A. Doing this makes an alloca available for
// reuse and makes a callsite (C) available for inlining. When we process
// the C call site we don't want to do any alloca merging between X and Y
// because their scopes are not disjoint. We could make this smarter by
// keeping track of the inline history for each alloca in the
// InlinedArrayAllocas but this isn't likely to be a significant win.
if (InlineHistory != -1) // Only do merging for top-level call sites in SCC.
return true;
// Loop over all the allocas we have so far and see if they can be merged with
// a previously inlined alloca. If not, remember that we had it.
for (unsigned AllocaNo = 0, e = IFI.StaticAllocas.size();
AllocaNo != e; ++AllocaNo) {
AllocaInst *AI = IFI.StaticAllocas[AllocaNo];
// Don't bother trying to merge array allocations (they will usually be
// canonicalized to be an allocation *of* an array), or allocations whose
// type is not itself an array (because we're afraid of pessimizing SRoA).
ArrayType *ATy = dyn_cast<ArrayType>(AI->getAllocatedType());
if (!ATy || AI->isArrayAllocation())
continue;
// Get the list of all available allocas for this array type.
std::vector<AllocaInst*> &AllocasForType = InlinedArrayAllocas[ATy];
// Loop over the allocas in AllocasForType to see if we can reuse one. Note
// that we have to be careful not to reuse the same "available" alloca for
// multiple different allocas that we just inlined, we use the 'UsedAllocas'
// set to keep track of which "available" allocas are being used by this
// function. Also, AllocasForType can be empty of course!
bool MergedAwayAlloca = false;
for (AllocaInst *AvailableAlloca : AllocasForType) {
unsigned Align1 = AI->getAlignment(),
Align2 = AvailableAlloca->getAlignment();
// The available alloca has to be in the right function, not in some other
// function in this SCC.
if (AvailableAlloca->getParent() != AI->getParent())
continue;
// If the inlined function already uses this alloca then we can't reuse
// it.
if (!UsedAllocas.insert(AvailableAlloca).second)
continue;
// Otherwise, we *can* reuse it, RAUW AI into AvailableAlloca and declare
// success!
DEBUG(dbgs() << " ***MERGED ALLOCA: " << *AI << "\n\t\tINTO: "
<< *AvailableAlloca << '\n');
// Move affected dbg.declare calls immediately after the new alloca to
// avoid the situation when a dbg.declare preceeds its alloca.
if (auto *L = LocalAsMetadata::getIfExists(AI))
if (auto *MDV = MetadataAsValue::getIfExists(AI->getContext(), L))
for (User *U : MDV->users())
if (DbgDeclareInst *DDI = dyn_cast<DbgDeclareInst>(U))
DDI->moveBefore(AvailableAlloca->getNextNode());
AI->replaceAllUsesWith(AvailableAlloca);
if (Align1 != Align2) {
if (!Align1 || !Align2) {
const DataLayout &DL = Caller->getParent()->getDataLayout();
unsigned TypeAlign = DL.getABITypeAlignment(AI->getAllocatedType());
Align1 = Align1 ? Align1 : TypeAlign;
Align2 = Align2 ? Align2 : TypeAlign;
}
if (Align1 > Align2)
AvailableAlloca->setAlignment(AI->getAlignment());
}
AI->eraseFromParent();
MergedAwayAlloca = true;
++NumMergedAllocas;
IFI.StaticAllocas[AllocaNo] = nullptr;
break;
}
// If we already nuked the alloca, we're done with it.
if (MergedAwayAlloca)
continue;
// If we were unable to merge away the alloca either because there are no
// allocas of the right type available or because we reused them all
// already, remember that this alloca came from an inlined function and mark
// it used so we don't reuse it for other allocas from this inline
// operation.
AllocasForType.push_back(AI);
UsedAllocas.insert(AI);
}
return true;
}
static void emitAnalysis(CallSite CS, const Twine &Msg) {
Function *Caller = CS.getCaller();
LLVMContext &Ctx = Caller->getContext();
DebugLoc DLoc = CS.getInstruction()->getDebugLoc();
emitOptimizationRemarkAnalysis(Ctx, DEBUG_TYPE, *Caller, DLoc, Msg);
}
/// Return true if the inliner should attempt to inline at the given CallSite.
bool Inliner::shouldInline(CallSite CS) {
InlineCost IC = getInlineCost(CS);
if (IC.isAlways()) {
DEBUG(dbgs() << " Inlining: cost=always"
<< ", Call: " << *CS.getInstruction() << "\n");
emitAnalysis(CS, Twine(CS.getCalledFunction()->getName()) +
" should always be inlined (cost=always)");
return true;
}
if (IC.isNever()) {
DEBUG(dbgs() << " NOT Inlining: cost=never"
<< ", Call: " << *CS.getInstruction() << "\n");
emitAnalysis(CS, Twine(CS.getCalledFunction()->getName() +
" should never be inlined (cost=never)"));
return false;
}
Function *Caller = CS.getCaller();
Initial commit for the rewrite of the inline cost analysis to operate on a per-callsite walk of the called function's instructions, in breadth-first order over the potentially reachable set of basic blocks. This is a major shift in how inline cost analysis works to improve the accuracy and rationality of inlining decisions. A brief outline of the algorithm this moves to: - Build a simplification mapping based on the callsite arguments to the function arguments. - Push the entry block onto a worklist of potentially-live basic blocks. - Pop the first block off of the *front* of the worklist (for breadth-first ordering) and walk its instructions using a custom InstVisitor. - For each instruction's operands, re-map them based on the simplification mappings available for the given callsite. - Compute any simplification possible of the instruction after re-mapping, and store that back int othe simplification mapping. - Compute any bonuses, costs, or other impacts of the instruction on the cost metric. - When the terminator is reached, replace any conditional value in the terminator with any simplifications from the mapping we have, and add any successors which are not proven to be dead from these simplifications to the worklist. - Pop the next block off of the front of the worklist, and repeat. - As soon as the cost of inlining exceeds the threshold for the callsite, stop analyzing the function in order to bound cost. The primary goal of this algorithm is to perfectly handle dead code paths. We do not want any code in trivially dead code paths to impact inlining decisions. The previous metric was *extremely* flawed here, and would always subtract the average cost of two successors of a conditional branch when it was proven to become an unconditional branch at the callsite. There was no handling of wildly different costs between the two successors, which would cause inlining when the path actually taken was too large, and no inlining when the path actually taken was trivially simple. There was also no handling of the code *path*, only the immediate successors. These problems vanish completely now. See the added regression tests for the shiny new features -- we skip recursive function calls, SROA-killing instructions, and high cost complex CFG structures when dead at the callsite being analyzed. Switching to this algorithm required refactoring the inline cost interface to accept the actual threshold rather than simply returning a single cost. The resulting interface is pretty bad, and I'm planning to do lots of interface cleanup after this patch. Several other refactorings fell out of this, but I've tried to minimize them for this patch. =/ There is still more cleanup that can be done here. Please point out anything that you see in review. I've worked really hard to try to mirror at least the spirit of all of the previous heuristics in the new model. It's not clear that they are all correct any more, but I wanted to minimize the change in this single patch, it's already a bit ridiculous. One heuristic that is *not* yet mirrored is to allow inlining of functions with a dynamic alloca *if* the caller has a dynamic alloca. I will add this back, but I think the most reasonable way requires changes to the inliner itself rather than just the cost metric, and so I've deferred this for a subsequent patch. The test case is XFAIL-ed until then. As mentioned in the review mail, this seems to make Clang run about 1% to 2% faster in -O0, but makes its binary size grow by just under 4%. I've looked into the 4% growth, and it can be fixed, but requires changes to other parts of the inliner. llvm-svn: 153812
2012-03-31 14:42:41 +02:00
if (!IC) {
DEBUG(dbgs() << " NOT Inlining: cost=" << IC.getCost()
<< ", thres=" << (IC.getCostDelta() + IC.getCost())
<< ", Call: " << *CS.getInstruction() << "\n");
emitAnalysis(CS, Twine(CS.getCalledFunction()->getName() +
" too costly to inline (cost=") +
Twine(IC.getCost()) + ", threshold=" +
Twine(IC.getCostDelta() + IC.getCost()) + ")");
return false;
}
// Try to detect the case where the current inlining candidate caller (call
// it B) is a static or linkonce-ODR function and is an inlining candidate
// elsewhere, and the current candidate callee (call it C) is large enough
// that inlining it into B would make B too big to inline later. In these
// circumstances it may be best not to inline C into B, but to inline B into
// its callers.
//
// This only applies to static and linkonce-ODR functions because those are
// expected to be available for inlining in the translation units where they
// are used. Thus we will always have the opportunity to make local inlining
// decisions. Importantly the linkonce-ODR linkage covers inline functions
// and templates in C++.
Initial commit for the rewrite of the inline cost analysis to operate on a per-callsite walk of the called function's instructions, in breadth-first order over the potentially reachable set of basic blocks. This is a major shift in how inline cost analysis works to improve the accuracy and rationality of inlining decisions. A brief outline of the algorithm this moves to: - Build a simplification mapping based on the callsite arguments to the function arguments. - Push the entry block onto a worklist of potentially-live basic blocks. - Pop the first block off of the *front* of the worklist (for breadth-first ordering) and walk its instructions using a custom InstVisitor. - For each instruction's operands, re-map them based on the simplification mappings available for the given callsite. - Compute any simplification possible of the instruction after re-mapping, and store that back int othe simplification mapping. - Compute any bonuses, costs, or other impacts of the instruction on the cost metric. - When the terminator is reached, replace any conditional value in the terminator with any simplifications from the mapping we have, and add any successors which are not proven to be dead from these simplifications to the worklist. - Pop the next block off of the front of the worklist, and repeat. - As soon as the cost of inlining exceeds the threshold for the callsite, stop analyzing the function in order to bound cost. The primary goal of this algorithm is to perfectly handle dead code paths. We do not want any code in trivially dead code paths to impact inlining decisions. The previous metric was *extremely* flawed here, and would always subtract the average cost of two successors of a conditional branch when it was proven to become an unconditional branch at the callsite. There was no handling of wildly different costs between the two successors, which would cause inlining when the path actually taken was too large, and no inlining when the path actually taken was trivially simple. There was also no handling of the code *path*, only the immediate successors. These problems vanish completely now. See the added regression tests for the shiny new features -- we skip recursive function calls, SROA-killing instructions, and high cost complex CFG structures when dead at the callsite being analyzed. Switching to this algorithm required refactoring the inline cost interface to accept the actual threshold rather than simply returning a single cost. The resulting interface is pretty bad, and I'm planning to do lots of interface cleanup after this patch. Several other refactorings fell out of this, but I've tried to minimize them for this patch. =/ There is still more cleanup that can be done here. Please point out anything that you see in review. I've worked really hard to try to mirror at least the spirit of all of the previous heuristics in the new model. It's not clear that they are all correct any more, but I wanted to minimize the change in this single patch, it's already a bit ridiculous. One heuristic that is *not* yet mirrored is to allow inlining of functions with a dynamic alloca *if* the caller has a dynamic alloca. I will add this back, but I think the most reasonable way requires changes to the inliner itself rather than just the cost metric, and so I've deferred this for a subsequent patch. The test case is XFAIL-ed until then. As mentioned in the review mail, this seems to make Clang run about 1% to 2% faster in -O0, but makes its binary size grow by just under 4%. I've looked into the 4% growth, and it can be fixed, but requires changes to other parts of the inliner. llvm-svn: 153812
2012-03-31 14:42:41 +02:00
//
// FIXME: All of this logic should be sunk into getInlineCost. It relies on
// the internal implementation of the inline cost metrics rather than
// treating them as truly abstract units etc.
if (Caller->hasLocalLinkage() || Caller->hasLinkOnceODRLinkage()) {
int TotalSecondaryCost = 0;
Initial commit for the rewrite of the inline cost analysis to operate on a per-callsite walk of the called function's instructions, in breadth-first order over the potentially reachable set of basic blocks. This is a major shift in how inline cost analysis works to improve the accuracy and rationality of inlining decisions. A brief outline of the algorithm this moves to: - Build a simplification mapping based on the callsite arguments to the function arguments. - Push the entry block onto a worklist of potentially-live basic blocks. - Pop the first block off of the *front* of the worklist (for breadth-first ordering) and walk its instructions using a custom InstVisitor. - For each instruction's operands, re-map them based on the simplification mappings available for the given callsite. - Compute any simplification possible of the instruction after re-mapping, and store that back int othe simplification mapping. - Compute any bonuses, costs, or other impacts of the instruction on the cost metric. - When the terminator is reached, replace any conditional value in the terminator with any simplifications from the mapping we have, and add any successors which are not proven to be dead from these simplifications to the worklist. - Pop the next block off of the front of the worklist, and repeat. - As soon as the cost of inlining exceeds the threshold for the callsite, stop analyzing the function in order to bound cost. The primary goal of this algorithm is to perfectly handle dead code paths. We do not want any code in trivially dead code paths to impact inlining decisions. The previous metric was *extremely* flawed here, and would always subtract the average cost of two successors of a conditional branch when it was proven to become an unconditional branch at the callsite. There was no handling of wildly different costs between the two successors, which would cause inlining when the path actually taken was too large, and no inlining when the path actually taken was trivially simple. There was also no handling of the code *path*, only the immediate successors. These problems vanish completely now. See the added regression tests for the shiny new features -- we skip recursive function calls, SROA-killing instructions, and high cost complex CFG structures when dead at the callsite being analyzed. Switching to this algorithm required refactoring the inline cost interface to accept the actual threshold rather than simply returning a single cost. The resulting interface is pretty bad, and I'm planning to do lots of interface cleanup after this patch. Several other refactorings fell out of this, but I've tried to minimize them for this patch. =/ There is still more cleanup that can be done here. Please point out anything that you see in review. I've worked really hard to try to mirror at least the spirit of all of the previous heuristics in the new model. It's not clear that they are all correct any more, but I wanted to minimize the change in this single patch, it's already a bit ridiculous. One heuristic that is *not* yet mirrored is to allow inlining of functions with a dynamic alloca *if* the caller has a dynamic alloca. I will add this back, but I think the most reasonable way requires changes to the inliner itself rather than just the cost metric, and so I've deferred this for a subsequent patch. The test case is XFAIL-ed until then. As mentioned in the review mail, this seems to make Clang run about 1% to 2% faster in -O0, but makes its binary size grow by just under 4%. I've looked into the 4% growth, and it can be fixed, but requires changes to other parts of the inliner. llvm-svn: 153812
2012-03-31 14:42:41 +02:00
// The candidate cost to be imposed upon the current function.
int CandidateCost = IC.getCost() - (InlineConstants::CallPenalty + 1);
// This bool tracks what happens if we do NOT inline C into B.
Make a seemingly tiny change to the inliner and fix the generated code size bloat. Unfortunately, I expect this to disable the majority of the benefit from r152737. I'm hopeful at least that it will fix PR12345. To explain this requires... quite a bit of backstory I'm afraid. TL;DR: The change in r152737 actually did The Wrong Thing for linkonce-odr functions. This change makes it do the right thing. The benefits we saw were simple luck, not any actual strategy. Benchmark numbers after a mini-blog-post so that I've written down my thoughts on why all of this works and doesn't work... To understand what's going on here, you have to understand how the "bottom-up" inliner actually works. There are two fundamental modes to the inliner: 1) Standard fixed-cost bottom-up inlining. This is the mode we usually think about. It walks from the bottom of the CFG up to the top, looking at callsites, taking information about the callsite and the called function and computing th expected cost of inlining into that callsite. If the cost is under a fixed threshold, it inlines. It's a touch more complicated than that due to all the bonuses, weights, etc. Inlining the last callsite to an internal function gets higher weighth, etc. But essentially, this is the mode of operation. 2) Deferred bottom-up inlining (a term I just made up). This is the interesting mode for this patch an r152737. Initially, this works just like mode #1, but once we have the cost of inlining into the callsite, we don't just compare it with a fixed threshold. First, we check something else. Let's give some names to the entities at this point, or we'll end up hopelessly confused. We're considering inlining a function 'A' into its callsite within a function 'B'. We want to check whether 'B' has any callers, and whether it might be inlined into those callers. If so, we also check whether inlining 'A' into 'B' would block any of the opportunities for inlining 'B' into its callers. We take the sum of the costs of inlining 'B' into its callers where that inlining would be blocked by inlining 'A' into 'B', and if that cost is less than the cost of inlining 'A' into 'B', then we skip inlining 'A' into 'B'. Now, in order for #2 to make sense, we have to have some confidence that we will actually have the opportunity to inline 'B' into its callers when cheaper, *and* that we'll be able to revisit the decision and inline 'A' into 'B' if that ever becomes the correct tradeoff. This often isn't true for external functions -- we can see very few of their callers, and we won't be able to re-consider inlining 'A' into 'B' if 'B' is external when we finally see more callers of 'B'. There are two cases where we believe this to be true for C/C++ code: functions local to a translation unit, and functions with an inline definition in every translation unit which uses them. These are represented as internal linkage and linkonce-odr (resp.) in LLVM. I enabled this logic for linkonce-odr in r152737. Unfortunately, when I did that, I also introduced a subtle bug. There was an implicit assumption that the last caller of the function within the TU was the last caller of the function in the program. We want to bonus the last caller of the function in the program by a huge amount for inlining because inlining that callsite has very little cost. Unfortunately, the last caller in the TU of a linkonce-odr function is *not* the last caller in the program, and so we don't want to apply this bonus. If we do, we can apply it to one callsite *per-TU*. Because of the way deferred inlining works, when it sees this bonus applied to one callsite in the TU for 'B', it decides that inlining 'B' is of the *utmost* importance just so we can get that final bonus. It then proceeds to essentially force deferred inlining regardless of the actual cost tradeoff. The result? PR12345: code bloat, code bloat, code bloat. Another result is getting *damn* lucky on a few benchmarks, and the over-inlining exposing critically important optimizations. I would very much like a list of benchmarks that regress after this change goes in, with bitcode before and after. This will help me greatly understand what opportunities the current cost analysis is missing. Initial benchmark numbers look very good. WebKit files that exhibited the worst of PR12345 went from growing to shrinking compared to Clang with r152737 reverted. - Bootstrapped Clang is 3% smaller with this change. - Bootstrapped Clang -O0 over a single-source-file of lib/Lex is 4% faster with this change. Please let me know about any other performance impact you see. Thanks to Nico for reporting and urging me to actually fix, Richard Smith, Duncan Sands, Manuel Klimek, and Benjamin Kramer for talking through the issues today. llvm-svn: 153506
2012-03-27 12:48:28 +02:00
bool callerWillBeRemoved = Caller->hasLocalLinkage();
// This bool tracks what happens if we DO inline C into B.
bool inliningPreventsSomeOuterInline = false;
[C++11] Add range based accessors for the Use-Def chain of a Value. This requires a number of steps. 1) Move value_use_iterator into the Value class as an implementation detail 2) Change it to actually be a *Use* iterator rather than a *User* iterator. 3) Add an adaptor which is a User iterator that always looks through the Use to the User. 4) Wrap these in Value::use_iterator and Value::user_iterator typedefs. 5) Add the range adaptors as Value::uses() and Value::users(). 6) Update *all* of the callers to correctly distinguish between whether they wanted a use_iterator (and to explicitly dig out the User when needed), or a user_iterator which makes the Use itself totally opaque. Because #6 requires churning essentially everything that walked the Use-Def chains, I went ahead and added all of the range adaptors and switched them to range-based loops where appropriate. Also because the renaming requires at least churning every line of code, it didn't make any sense to split these up into multiple commits -- all of which would touch all of the same lies of code. The result is still not quite optimal. The Value::use_iterator is a nice regular iterator, but Value::user_iterator is an iterator over User*s rather than over the User objects themselves. As a consequence, it fits a bit awkwardly into the range-based world and it has the weird extra-dereferencing 'operator->' that so many of our iterators have. I think this could be fixed by providing something which transforms a range of T&s into a range of T*s, but that *can* be separated into another patch, and it isn't yet 100% clear whether this is the right move. However, this change gets us most of the benefit and cleans up a substantial amount of code around Use and User. =] llvm-svn: 203364
2014-03-09 04:16:01 +01:00
for (User *U : Caller->users()) {
CallSite CS2(U);
// If this isn't a call to Caller (it could be some other sort
// of reference) skip it. Such references will prevent the caller
// from being removed.
if (!CS2 || CS2.getCalledFunction() != Caller) {
callerWillBeRemoved = false;
continue;
}
InlineCost IC2 = getInlineCost(CS2);
++NumCallerCallersAnalyzed;
Initial commit for the rewrite of the inline cost analysis to operate on a per-callsite walk of the called function's instructions, in breadth-first order over the potentially reachable set of basic blocks. This is a major shift in how inline cost analysis works to improve the accuracy and rationality of inlining decisions. A brief outline of the algorithm this moves to: - Build a simplification mapping based on the callsite arguments to the function arguments. - Push the entry block onto a worklist of potentially-live basic blocks. - Pop the first block off of the *front* of the worklist (for breadth-first ordering) and walk its instructions using a custom InstVisitor. - For each instruction's operands, re-map them based on the simplification mappings available for the given callsite. - Compute any simplification possible of the instruction after re-mapping, and store that back int othe simplification mapping. - Compute any bonuses, costs, or other impacts of the instruction on the cost metric. - When the terminator is reached, replace any conditional value in the terminator with any simplifications from the mapping we have, and add any successors which are not proven to be dead from these simplifications to the worklist. - Pop the next block off of the front of the worklist, and repeat. - As soon as the cost of inlining exceeds the threshold for the callsite, stop analyzing the function in order to bound cost. The primary goal of this algorithm is to perfectly handle dead code paths. We do not want any code in trivially dead code paths to impact inlining decisions. The previous metric was *extremely* flawed here, and would always subtract the average cost of two successors of a conditional branch when it was proven to become an unconditional branch at the callsite. There was no handling of wildly different costs between the two successors, which would cause inlining when the path actually taken was too large, and no inlining when the path actually taken was trivially simple. There was also no handling of the code *path*, only the immediate successors. These problems vanish completely now. See the added regression tests for the shiny new features -- we skip recursive function calls, SROA-killing instructions, and high cost complex CFG structures when dead at the callsite being analyzed. Switching to this algorithm required refactoring the inline cost interface to accept the actual threshold rather than simply returning a single cost. The resulting interface is pretty bad, and I'm planning to do lots of interface cleanup after this patch. Several other refactorings fell out of this, but I've tried to minimize them for this patch. =/ There is still more cleanup that can be done here. Please point out anything that you see in review. I've worked really hard to try to mirror at least the spirit of all of the previous heuristics in the new model. It's not clear that they are all correct any more, but I wanted to minimize the change in this single patch, it's already a bit ridiculous. One heuristic that is *not* yet mirrored is to allow inlining of functions with a dynamic alloca *if* the caller has a dynamic alloca. I will add this back, but I think the most reasonable way requires changes to the inliner itself rather than just the cost metric, and so I've deferred this for a subsequent patch. The test case is XFAIL-ed until then. As mentioned in the review mail, this seems to make Clang run about 1% to 2% faster in -O0, but makes its binary size grow by just under 4%. I've looked into the 4% growth, and it can be fixed, but requires changes to other parts of the inliner. llvm-svn: 153812
2012-03-31 14:42:41 +02:00
if (!IC2) {
callerWillBeRemoved = false;
Initial commit for the rewrite of the inline cost analysis to operate on a per-callsite walk of the called function's instructions, in breadth-first order over the potentially reachable set of basic blocks. This is a major shift in how inline cost analysis works to improve the accuracy and rationality of inlining decisions. A brief outline of the algorithm this moves to: - Build a simplification mapping based on the callsite arguments to the function arguments. - Push the entry block onto a worklist of potentially-live basic blocks. - Pop the first block off of the *front* of the worklist (for breadth-first ordering) and walk its instructions using a custom InstVisitor. - For each instruction's operands, re-map them based on the simplification mappings available for the given callsite. - Compute any simplification possible of the instruction after re-mapping, and store that back int othe simplification mapping. - Compute any bonuses, costs, or other impacts of the instruction on the cost metric. - When the terminator is reached, replace any conditional value in the terminator with any simplifications from the mapping we have, and add any successors which are not proven to be dead from these simplifications to the worklist. - Pop the next block off of the front of the worklist, and repeat. - As soon as the cost of inlining exceeds the threshold for the callsite, stop analyzing the function in order to bound cost. The primary goal of this algorithm is to perfectly handle dead code paths. We do not want any code in trivially dead code paths to impact inlining decisions. The previous metric was *extremely* flawed here, and would always subtract the average cost of two successors of a conditional branch when it was proven to become an unconditional branch at the callsite. There was no handling of wildly different costs between the two successors, which would cause inlining when the path actually taken was too large, and no inlining when the path actually taken was trivially simple. There was also no handling of the code *path*, only the immediate successors. These problems vanish completely now. See the added regression tests for the shiny new features -- we skip recursive function calls, SROA-killing instructions, and high cost complex CFG structures when dead at the callsite being analyzed. Switching to this algorithm required refactoring the inline cost interface to accept the actual threshold rather than simply returning a single cost. The resulting interface is pretty bad, and I'm planning to do lots of interface cleanup after this patch. Several other refactorings fell out of this, but I've tried to minimize them for this patch. =/ There is still more cleanup that can be done here. Please point out anything that you see in review. I've worked really hard to try to mirror at least the spirit of all of the previous heuristics in the new model. It's not clear that they are all correct any more, but I wanted to minimize the change in this single patch, it's already a bit ridiculous. One heuristic that is *not* yet mirrored is to allow inlining of functions with a dynamic alloca *if* the caller has a dynamic alloca. I will add this back, but I think the most reasonable way requires changes to the inliner itself rather than just the cost metric, and so I've deferred this for a subsequent patch. The test case is XFAIL-ed until then. As mentioned in the review mail, this seems to make Clang run about 1% to 2% faster in -O0, but makes its binary size grow by just under 4%. I've looked into the 4% growth, and it can be fixed, but requires changes to other parts of the inliner. llvm-svn: 153812
2012-03-31 14:42:41 +02:00
continue;
}
if (IC2.isAlways())
continue;
Initial commit for the rewrite of the inline cost analysis to operate on a per-callsite walk of the called function's instructions, in breadth-first order over the potentially reachable set of basic blocks. This is a major shift in how inline cost analysis works to improve the accuracy and rationality of inlining decisions. A brief outline of the algorithm this moves to: - Build a simplification mapping based on the callsite arguments to the function arguments. - Push the entry block onto a worklist of potentially-live basic blocks. - Pop the first block off of the *front* of the worklist (for breadth-first ordering) and walk its instructions using a custom InstVisitor. - For each instruction's operands, re-map them based on the simplification mappings available for the given callsite. - Compute any simplification possible of the instruction after re-mapping, and store that back int othe simplification mapping. - Compute any bonuses, costs, or other impacts of the instruction on the cost metric. - When the terminator is reached, replace any conditional value in the terminator with any simplifications from the mapping we have, and add any successors which are not proven to be dead from these simplifications to the worklist. - Pop the next block off of the front of the worklist, and repeat. - As soon as the cost of inlining exceeds the threshold for the callsite, stop analyzing the function in order to bound cost. The primary goal of this algorithm is to perfectly handle dead code paths. We do not want any code in trivially dead code paths to impact inlining decisions. The previous metric was *extremely* flawed here, and would always subtract the average cost of two successors of a conditional branch when it was proven to become an unconditional branch at the callsite. There was no handling of wildly different costs between the two successors, which would cause inlining when the path actually taken was too large, and no inlining when the path actually taken was trivially simple. There was also no handling of the code *path*, only the immediate successors. These problems vanish completely now. See the added regression tests for the shiny new features -- we skip recursive function calls, SROA-killing instructions, and high cost complex CFG structures when dead at the callsite being analyzed. Switching to this algorithm required refactoring the inline cost interface to accept the actual threshold rather than simply returning a single cost. The resulting interface is pretty bad, and I'm planning to do lots of interface cleanup after this patch. Several other refactorings fell out of this, but I've tried to minimize them for this patch. =/ There is still more cleanup that can be done here. Please point out anything that you see in review. I've worked really hard to try to mirror at least the spirit of all of the previous heuristics in the new model. It's not clear that they are all correct any more, but I wanted to minimize the change in this single patch, it's already a bit ridiculous. One heuristic that is *not* yet mirrored is to allow inlining of functions with a dynamic alloca *if* the caller has a dynamic alloca. I will add this back, but I think the most reasonable way requires changes to the inliner itself rather than just the cost metric, and so I've deferred this for a subsequent patch. The test case is XFAIL-ed until then. As mentioned in the review mail, this seems to make Clang run about 1% to 2% faster in -O0, but makes its binary size grow by just under 4%. I've looked into the 4% growth, and it can be fixed, but requires changes to other parts of the inliner. llvm-svn: 153812
2012-03-31 14:42:41 +02:00
// See if inlining or original callsite would erase the cost delta of
// this callsite. We subtract off the penalty for the call instruction,
// which we would be deleting.
if (IC2.getCostDelta() <= CandidateCost) {
inliningPreventsSomeOuterInline = true;
Initial commit for the rewrite of the inline cost analysis to operate on a per-callsite walk of the called function's instructions, in breadth-first order over the potentially reachable set of basic blocks. This is a major shift in how inline cost analysis works to improve the accuracy and rationality of inlining decisions. A brief outline of the algorithm this moves to: - Build a simplification mapping based on the callsite arguments to the function arguments. - Push the entry block onto a worklist of potentially-live basic blocks. - Pop the first block off of the *front* of the worklist (for breadth-first ordering) and walk its instructions using a custom InstVisitor. - For each instruction's operands, re-map them based on the simplification mappings available for the given callsite. - Compute any simplification possible of the instruction after re-mapping, and store that back int othe simplification mapping. - Compute any bonuses, costs, or other impacts of the instruction on the cost metric. - When the terminator is reached, replace any conditional value in the terminator with any simplifications from the mapping we have, and add any successors which are not proven to be dead from these simplifications to the worklist. - Pop the next block off of the front of the worklist, and repeat. - As soon as the cost of inlining exceeds the threshold for the callsite, stop analyzing the function in order to bound cost. The primary goal of this algorithm is to perfectly handle dead code paths. We do not want any code in trivially dead code paths to impact inlining decisions. The previous metric was *extremely* flawed here, and would always subtract the average cost of two successors of a conditional branch when it was proven to become an unconditional branch at the callsite. There was no handling of wildly different costs between the two successors, which would cause inlining when the path actually taken was too large, and no inlining when the path actually taken was trivially simple. There was also no handling of the code *path*, only the immediate successors. These problems vanish completely now. See the added regression tests for the shiny new features -- we skip recursive function calls, SROA-killing instructions, and high cost complex CFG structures when dead at the callsite being analyzed. Switching to this algorithm required refactoring the inline cost interface to accept the actual threshold rather than simply returning a single cost. The resulting interface is pretty bad, and I'm planning to do lots of interface cleanup after this patch. Several other refactorings fell out of this, but I've tried to minimize them for this patch. =/ There is still more cleanup that can be done here. Please point out anything that you see in review. I've worked really hard to try to mirror at least the spirit of all of the previous heuristics in the new model. It's not clear that they are all correct any more, but I wanted to minimize the change in this single patch, it's already a bit ridiculous. One heuristic that is *not* yet mirrored is to allow inlining of functions with a dynamic alloca *if* the caller has a dynamic alloca. I will add this back, but I think the most reasonable way requires changes to the inliner itself rather than just the cost metric, and so I've deferred this for a subsequent patch. The test case is XFAIL-ed until then. As mentioned in the review mail, this seems to make Clang run about 1% to 2% faster in -O0, but makes its binary size grow by just under 4%. I've looked into the 4% growth, and it can be fixed, but requires changes to other parts of the inliner. llvm-svn: 153812
2012-03-31 14:42:41 +02:00
TotalSecondaryCost += IC2.getCost();
}
}
// If all outer calls to Caller would get inlined, the cost for the last
// one is set very low by getInlineCost, in anticipation that Caller will
// be removed entirely. We did not account for this above unless there
// is only one caller of Caller.
[C++11] Add range based accessors for the Use-Def chain of a Value. This requires a number of steps. 1) Move value_use_iterator into the Value class as an implementation detail 2) Change it to actually be a *Use* iterator rather than a *User* iterator. 3) Add an adaptor which is a User iterator that always looks through the Use to the User. 4) Wrap these in Value::use_iterator and Value::user_iterator typedefs. 5) Add the range adaptors as Value::uses() and Value::users(). 6) Update *all* of the callers to correctly distinguish between whether they wanted a use_iterator (and to explicitly dig out the User when needed), or a user_iterator which makes the Use itself totally opaque. Because #6 requires churning essentially everything that walked the Use-Def chains, I went ahead and added all of the range adaptors and switched them to range-based loops where appropriate. Also because the renaming requires at least churning every line of code, it didn't make any sense to split these up into multiple commits -- all of which would touch all of the same lies of code. The result is still not quite optimal. The Value::use_iterator is a nice regular iterator, but Value::user_iterator is an iterator over User*s rather than over the User objects themselves. As a consequence, it fits a bit awkwardly into the range-based world and it has the weird extra-dereferencing 'operator->' that so many of our iterators have. I think this could be fixed by providing something which transforms a range of T&s into a range of T*s, but that *can* be separated into another patch, and it isn't yet 100% clear whether this is the right move. However, this change gets us most of the benefit and cleans up a substantial amount of code around Use and User. =] llvm-svn: 203364
2014-03-09 04:16:01 +01:00
if (callerWillBeRemoved && !Caller->use_empty())
TotalSecondaryCost += InlineConstants::LastCallToStaticBonus;
Initial commit for the rewrite of the inline cost analysis to operate on a per-callsite walk of the called function's instructions, in breadth-first order over the potentially reachable set of basic blocks. This is a major shift in how inline cost analysis works to improve the accuracy and rationality of inlining decisions. A brief outline of the algorithm this moves to: - Build a simplification mapping based on the callsite arguments to the function arguments. - Push the entry block onto a worklist of potentially-live basic blocks. - Pop the first block off of the *front* of the worklist (for breadth-first ordering) and walk its instructions using a custom InstVisitor. - For each instruction's operands, re-map them based on the simplification mappings available for the given callsite. - Compute any simplification possible of the instruction after re-mapping, and store that back int othe simplification mapping. - Compute any bonuses, costs, or other impacts of the instruction on the cost metric. - When the terminator is reached, replace any conditional value in the terminator with any simplifications from the mapping we have, and add any successors which are not proven to be dead from these simplifications to the worklist. - Pop the next block off of the front of the worklist, and repeat. - As soon as the cost of inlining exceeds the threshold for the callsite, stop analyzing the function in order to bound cost. The primary goal of this algorithm is to perfectly handle dead code paths. We do not want any code in trivially dead code paths to impact inlining decisions. The previous metric was *extremely* flawed here, and would always subtract the average cost of two successors of a conditional branch when it was proven to become an unconditional branch at the callsite. There was no handling of wildly different costs between the two successors, which would cause inlining when the path actually taken was too large, and no inlining when the path actually taken was trivially simple. There was also no handling of the code *path*, only the immediate successors. These problems vanish completely now. See the added regression tests for the shiny new features -- we skip recursive function calls, SROA-killing instructions, and high cost complex CFG structures when dead at the callsite being analyzed. Switching to this algorithm required refactoring the inline cost interface to accept the actual threshold rather than simply returning a single cost. The resulting interface is pretty bad, and I'm planning to do lots of interface cleanup after this patch. Several other refactorings fell out of this, but I've tried to minimize them for this patch. =/ There is still more cleanup that can be done here. Please point out anything that you see in review. I've worked really hard to try to mirror at least the spirit of all of the previous heuristics in the new model. It's not clear that they are all correct any more, but I wanted to minimize the change in this single patch, it's already a bit ridiculous. One heuristic that is *not* yet mirrored is to allow inlining of functions with a dynamic alloca *if* the caller has a dynamic alloca. I will add this back, but I think the most reasonable way requires changes to the inliner itself rather than just the cost metric, and so I've deferred this for a subsequent patch. The test case is XFAIL-ed until then. As mentioned in the review mail, this seems to make Clang run about 1% to 2% faster in -O0, but makes its binary size grow by just under 4%. I've looked into the 4% growth, and it can be fixed, but requires changes to other parts of the inliner. llvm-svn: 153812
2012-03-31 14:42:41 +02:00
if (inliningPreventsSomeOuterInline && TotalSecondaryCost < IC.getCost()) {
DEBUG(dbgs() << " NOT Inlining: " << *CS.getInstruction() <<
" Cost = " << IC.getCost() <<
", outer Cost = " << TotalSecondaryCost << '\n');
emitAnalysis(
CS, Twine("Not inlining. Cost of inlining " +
CS.getCalledFunction()->getName() +
" increases the cost of inlining " +
CS.getCaller()->getName() + " in other contexts"));
return false;
}
}
Initial commit for the rewrite of the inline cost analysis to operate on a per-callsite walk of the called function's instructions, in breadth-first order over the potentially reachable set of basic blocks. This is a major shift in how inline cost analysis works to improve the accuracy and rationality of inlining decisions. A brief outline of the algorithm this moves to: - Build a simplification mapping based on the callsite arguments to the function arguments. - Push the entry block onto a worklist of potentially-live basic blocks. - Pop the first block off of the *front* of the worklist (for breadth-first ordering) and walk its instructions using a custom InstVisitor. - For each instruction's operands, re-map them based on the simplification mappings available for the given callsite. - Compute any simplification possible of the instruction after re-mapping, and store that back int othe simplification mapping. - Compute any bonuses, costs, or other impacts of the instruction on the cost metric. - When the terminator is reached, replace any conditional value in the terminator with any simplifications from the mapping we have, and add any successors which are not proven to be dead from these simplifications to the worklist. - Pop the next block off of the front of the worklist, and repeat. - As soon as the cost of inlining exceeds the threshold for the callsite, stop analyzing the function in order to bound cost. The primary goal of this algorithm is to perfectly handle dead code paths. We do not want any code in trivially dead code paths to impact inlining decisions. The previous metric was *extremely* flawed here, and would always subtract the average cost of two successors of a conditional branch when it was proven to become an unconditional branch at the callsite. There was no handling of wildly different costs between the two successors, which would cause inlining when the path actually taken was too large, and no inlining when the path actually taken was trivially simple. There was also no handling of the code *path*, only the immediate successors. These problems vanish completely now. See the added regression tests for the shiny new features -- we skip recursive function calls, SROA-killing instructions, and high cost complex CFG structures when dead at the callsite being analyzed. Switching to this algorithm required refactoring the inline cost interface to accept the actual threshold rather than simply returning a single cost. The resulting interface is pretty bad, and I'm planning to do lots of interface cleanup after this patch. Several other refactorings fell out of this, but I've tried to minimize them for this patch. =/ There is still more cleanup that can be done here. Please point out anything that you see in review. I've worked really hard to try to mirror at least the spirit of all of the previous heuristics in the new model. It's not clear that they are all correct any more, but I wanted to minimize the change in this single patch, it's already a bit ridiculous. One heuristic that is *not* yet mirrored is to allow inlining of functions with a dynamic alloca *if* the caller has a dynamic alloca. I will add this back, but I think the most reasonable way requires changes to the inliner itself rather than just the cost metric, and so I've deferred this for a subsequent patch. The test case is XFAIL-ed until then. As mentioned in the review mail, this seems to make Clang run about 1% to 2% faster in -O0, but makes its binary size grow by just under 4%. I've looked into the 4% growth, and it can be fixed, but requires changes to other parts of the inliner. llvm-svn: 153812
2012-03-31 14:42:41 +02:00
DEBUG(dbgs() << " Inlining: cost=" << IC.getCost()
<< ", thres=" << (IC.getCostDelta() + IC.getCost())
<< ", Call: " << *CS.getInstruction() << '\n');
emitAnalysis(
CS, CS.getCalledFunction()->getName() + Twine(" can be inlined into ") +
CS.getCaller()->getName() + " with cost=" + Twine(IC.getCost()) +
" (threshold=" + Twine(IC.getCostDelta() + IC.getCost()) + ")");
return true;
}
/// Return true if the specified inline history ID
/// indicates an inline history that includes the specified function.
static bool InlineHistoryIncludes(Function *F, int InlineHistoryID,
const SmallVectorImpl<std::pair<Function*, int> > &InlineHistory) {
while (InlineHistoryID != -1) {
assert(unsigned(InlineHistoryID) < InlineHistory.size() &&
"Invalid inline history ID");
if (InlineHistory[InlineHistoryID].first == F)
return true;
InlineHistoryID = InlineHistory[InlineHistoryID].second;
}
return false;
}
/// \brief Update the frequency of a block that is cloned into the caller.
/// This is invoked when \p OrigBB from the callee is cloned into \p NewBB in
/// the caller.
void Inliner::updateBlockFreq(CallSite &CS, const BasicBlock *OrigBB,
const BasicBlock *NewBB) {
if (!HasProfileData)
return;
Instruction *Call = CS.getInstruction();
BasicBlock *CallBB = Call->getParent();
BlockFrequencyInfo *CalleeBFI =
BFA->getBlockFrequencyInfo(CS.getCalledFunction());
BlockFrequencyInfo *CallerBFI =
BFA->getBlockFrequencyInfo(CallBB->getParent());
// Find the number of times OrigBB is executed per invocation of the callee
// and multiply by the number of times callee is executed in the caller.
// Freq(NewBB) = Freq(OrigBB) * CallSiteFreq / CalleeEntryFreq.
uint64_t CallSiteFreq = CallerBFI->getBlockFreq(CallBB).getFrequency();
uint64_t CalleeEntryFreq = CalleeBFI->getEntryFreq();
// Frequency of OrigBB in the callee.
BlockFrequency OrigBBFreq = CalleeBFI->getBlockFreq(OrigBB);
CallerBFI->setBlockFreq(NewBB, (double)(OrigBBFreq.getFrequency()) /
CalleeEntryFreq * CallSiteFreq);
}
/// \brief Update entry count of \p Callee after it got inlined at a callsite
/// in block \p CallBB.
void Inliner::updateEntryCount(BasicBlock *CallBB, Function *Callee) {
if (!HasProfileData)
return;
// If the callee has a original count of N, and the estimated count of
// callsite is M, the new callee count is set to N - M. M is estimated from
// the caller's entry count, its entry block frequency and the block frequency
// of the callsite.
Optional<uint64_t> CalleeCount = Callee->getEntryCount();
if (!CalleeCount)
return;
Optional<uint64_t> CallSiteCount = llvm::getBlockCount(CallBB, BFA.get());
if (!CallSiteCount)
return;
// Since CallSiteCount is an estimate, it could exceed the original callee
// count and has to be set to 0.
if (CallSiteCount.getValue() > CalleeCount.getValue()) {
Callee->setEntryCount(0);
DEBUG(llvm::dbgs() << "Estimated count of block " << CallBB->getName()
<< " is " << CallSiteCount.getValue()
<< " which exceeds the entry count "
<< CalleeCount.getValue() << " of the callee "
<< Callee->getName() << "\n");
} else
Callee->setEntryCount(CalleeCount.getValue() - CallSiteCount.getValue());
}
void Inliner::invalidateBFI(Function *F) {
if (!HasProfileData)
return;
if (F)
BFA->invalidateBlockFrequencyInfo(F);
}
void Inliner::invalidateBFI(CallGraphSCC &SCC) {
if (!HasProfileData)
return;
for (CallGraphNode *Node : SCC) {
Function *F = Node->getFunction();
invalidateBFI(F);
}
}
void Inliner::copyBlockFrequency(BasicBlock *Src, BasicBlock *Dst) {
if (!HasProfileData)
return;
Function *F = Src->getParent();
BlockFrequencyInfo *BFI = BFA->getBlockFrequencyInfo(F);
BFI->setBlockFreq(Dst, BFI->getBlockFreq(Src).getFrequency());
}
static bool hasProfileData(Module &M) {
// We check for the presence of MaxFunctionCount in the module.
// FIXME: This now only works for frontend based instrumentation.
return M.getMaximumFunctionCount().hasValue();
}
bool Inliner::runOnSCC(CallGraphSCC &SCC) {
using namespace std::placeholders;
CallGraph &CG = getAnalysis<CallGraphWrapperPass>().getCallGraph();
HasProfileData = hasProfileData(CG.getModule());
ACT = &getAnalysis<AssumptionCacheTracker>();
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-09 19:55:00 +02:00
auto &TLI = getAnalysis<TargetLibraryInfoWrapperPass>().getTLI();
SmallPtrSet<Function*, 8> SCCFunctions;
DEBUG(dbgs() << "Inliner visiting SCC:");
for (CallGraphNode *Node : SCC) {
Function *F = Node->getFunction();
if (F) SCCFunctions.insert(F);
DEBUG(dbgs() << " " << (F ? F->getName() : "INDIRECTNODE"));
}
// Scan through and identify all call sites ahead of time so that we only
// inline call sites in the original functions, not call sites that result
// from inlining other functions.
SmallVector<std::pair<CallSite, int>, 16> CallSites;
// When inlining a callee produces new call sites, we want to keep track of
// the fact that they were inlined from the callee. This allows us to avoid
// infinite inlining in some obscure cases. To represent this, we use an
// index into the InlineHistory vector.
SmallVector<std::pair<Function*, int>, 8> InlineHistory;
for (CallGraphNode *Node : SCC) {
Function *F = Node->getFunction();
if (!F) continue;
for (BasicBlock &BB : *F)
for (Instruction &I : BB) {
CallSite CS(cast<Value>(&I));
// If this isn't a call, or it is a call to an intrinsic, it can
// never be inlined.
if (!CS || isa<IntrinsicInst>(I))
continue;
// If this is a direct call to an external function, we can never inline
// it. If it is an indirect call, inlining may resolve it to be a
// direct call, so we keep it.
if (Function *Callee = CS.getCalledFunction())
if (Callee->isDeclaration())
continue;
CallSites.push_back(std::make_pair(CS, -1));
}
}
DEBUG(dbgs() << ": " << CallSites.size() << " call sites.\n");
// If there are no calls in this function, exit early.
if (CallSites.empty())
return false;
// Now that we have all of the call sites, move the ones to functions in the
// current SCC to the end of the list.
unsigned FirstCallInSCC = CallSites.size();
for (unsigned i = 0; i < FirstCallInSCC; ++i)
if (Function *F = CallSites[i].first.getCalledFunction())
if (SCCFunctions.count(F))
std::swap(CallSites[i--], CallSites[--FirstCallInSCC]);
InlinedArrayAllocasTy InlinedArrayAllocas;
// Now that we have all of the call sites, loop over them and inline them if
// it looks profitable to do so.
bool Changed = false;
bool LocalChange;
do {
LocalChange = false;
// Iterate over the outer loop because inlining functions can cause indirect
// calls to become direct calls.
// CallSites may be modified inside so ranged for loop can not be used.
for (unsigned CSi = 0; CSi != CallSites.size(); ++CSi) {
CallSite CS = CallSites[CSi].first;
implement a nice little efficiency hack in the inliner. Since we're now running IPSCCP early, and we run functionattrs interlaced with the inliner, we often (particularly for small or noop functions) completely propagate all of the information about a call to its call site in IPSSCP (making a call dead) and functionattrs is smart enough to realize that the function is readonly (because it is interlaced with inliner). To improve compile time and make the inliner threshold more accurate, realize that we don't have to inline dead readonly function calls. Instead, just delete the call. This happens all the time for C++ codes, here are some counters from opt/llvm-ld counting the number of times calls were deleted vs inlined on various apps: Tramp3d opt: 5033 inline - Number of call sites deleted, not inlined 24596 inline - Number of functions inlined llvm-ld: 667 inline - Number of functions deleted because all callers found 699 inline - Number of functions inlined 483.xalancbmk opt: 8096 inline - Number of call sites deleted, not inlined 62528 inline - Number of functions inlined llvm-ld: 217 inline - Number of allocas merged together 2158 inline - Number of functions inlined 471.omnetpp: 331 inline - Number of call sites deleted, not inlined 8981 inline - Number of functions inlined llvm-ld: 171 inline - Number of functions deleted because all callers found 629 inline - Number of functions inlined Deleting a call is much faster than inlining it, and is insensitive to the size of the callee. :) llvm-svn: 86975
2009-11-12 08:56:08 +01:00
Function *Caller = CS.getCaller();
Function *Callee = CS.getCalledFunction();
implement a nice little efficiency hack in the inliner. Since we're now running IPSCCP early, and we run functionattrs interlaced with the inliner, we often (particularly for small or noop functions) completely propagate all of the information about a call to its call site in IPSSCP (making a call dead) and functionattrs is smart enough to realize that the function is readonly (because it is interlaced with inliner). To improve compile time and make the inliner threshold more accurate, realize that we don't have to inline dead readonly function calls. Instead, just delete the call. This happens all the time for C++ codes, here are some counters from opt/llvm-ld counting the number of times calls were deleted vs inlined on various apps: Tramp3d opt: 5033 inline - Number of call sites deleted, not inlined 24596 inline - Number of functions inlined llvm-ld: 667 inline - Number of functions deleted because all callers found 699 inline - Number of functions inlined 483.xalancbmk opt: 8096 inline - Number of call sites deleted, not inlined 62528 inline - Number of functions inlined llvm-ld: 217 inline - Number of allocas merged together 2158 inline - Number of functions inlined 471.omnetpp: 331 inline - Number of call sites deleted, not inlined 8981 inline - Number of functions inlined llvm-ld: 171 inline - Number of functions deleted because all callers found 629 inline - Number of functions inlined Deleting a call is much faster than inlining it, and is insensitive to the size of the callee. :) llvm-svn: 86975
2009-11-12 08:56:08 +01:00
// If this call site is dead and it is to a readonly function, we should
// just delete the call instead of trying to inline it, regardless of
// size. This happens because IPSCCP propagates the result out of the
// call and then we're left with the dead call.
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-09 19:55:00 +02:00
if (isInstructionTriviallyDead(CS.getInstruction(), &TLI)) {
DEBUG(dbgs() << " -> Deleting dead call: "
implement a nice little efficiency hack in the inliner. Since we're now running IPSCCP early, and we run functionattrs interlaced with the inliner, we often (particularly for small or noop functions) completely propagate all of the information about a call to its call site in IPSSCP (making a call dead) and functionattrs is smart enough to realize that the function is readonly (because it is interlaced with inliner). To improve compile time and make the inliner threshold more accurate, realize that we don't have to inline dead readonly function calls. Instead, just delete the call. This happens all the time for C++ codes, here are some counters from opt/llvm-ld counting the number of times calls were deleted vs inlined on various apps: Tramp3d opt: 5033 inline - Number of call sites deleted, not inlined 24596 inline - Number of functions inlined llvm-ld: 667 inline - Number of functions deleted because all callers found 699 inline - Number of functions inlined 483.xalancbmk opt: 8096 inline - Number of call sites deleted, not inlined 62528 inline - Number of functions inlined llvm-ld: 217 inline - Number of allocas merged together 2158 inline - Number of functions inlined 471.omnetpp: 331 inline - Number of call sites deleted, not inlined 8981 inline - Number of functions inlined llvm-ld: 171 inline - Number of functions deleted because all callers found 629 inline - Number of functions inlined Deleting a call is much faster than inlining it, and is insensitive to the size of the callee. :) llvm-svn: 86975
2009-11-12 08:56:08 +01:00
<< *CS.getInstruction() << "\n");
// Update the call graph by deleting the edge from Callee to Caller.
CG[Caller]->removeCallEdgeFor(CS);
CS.getInstruction()->eraseFromParent();
++NumCallsDeleted;
} else {
Instruction *TheCall = CS.getInstruction();
BasicBlock *CallSiteBlock = TheCall->getParent();
Instruction *CallSuccessor = &*(++BasicBlock::iterator(TheCall));
implement a nice little efficiency hack in the inliner. Since we're now running IPSCCP early, and we run functionattrs interlaced with the inliner, we often (particularly for small or noop functions) completely propagate all of the information about a call to its call site in IPSSCP (making a call dead) and functionattrs is smart enough to realize that the function is readonly (because it is interlaced with inliner). To improve compile time and make the inliner threshold more accurate, realize that we don't have to inline dead readonly function calls. Instead, just delete the call. This happens all the time for C++ codes, here are some counters from opt/llvm-ld counting the number of times calls were deleted vs inlined on various apps: Tramp3d opt: 5033 inline - Number of call sites deleted, not inlined 24596 inline - Number of functions inlined llvm-ld: 667 inline - Number of functions deleted because all callers found 699 inline - Number of functions inlined 483.xalancbmk opt: 8096 inline - Number of call sites deleted, not inlined 62528 inline - Number of functions inlined llvm-ld: 217 inline - Number of allocas merged together 2158 inline - Number of functions inlined 471.omnetpp: 331 inline - Number of call sites deleted, not inlined 8981 inline - Number of functions inlined llvm-ld: 171 inline - Number of functions deleted because all callers found 629 inline - Number of functions inlined Deleting a call is much faster than inlining it, and is insensitive to the size of the callee. :) llvm-svn: 86975
2009-11-12 08:56:08 +01:00
// We can only inline direct calls to non-declarations.
if (!Callee || Callee->isDeclaration()) continue;
2010-07-13 20:27:13 +02:00
// If this call site was obtained by inlining another function, verify
// that the include path for the function did not include the callee
// itself. If so, we'd be recursively inlining the same function,
// which would provide the same callsites, which would cause us to
// infinitely inline.
int InlineHistoryID = CallSites[CSi].second;
if (InlineHistoryID != -1 &&
InlineHistoryIncludes(Callee, InlineHistoryID, InlineHistory))
continue;
LLVMContext &CallerCtx = Caller->getContext();
// Get DebugLoc to report. CS will be invalid after Inliner.
DebugLoc DLoc = CS.getInstruction()->getDebugLoc();
// If the policy determines that we should inline this function,
// try to do so.
if (!shouldInline(CS)) {
emitOptimizationRemarkMissed(CallerCtx, DEBUG_TYPE, *Caller, DLoc,
Twine(Callee->getName() +
" will not be inlined into " +
Caller->getName()));
continue;
}
BlockCloningFunctor BCF = nullptr;
if (HasProfileData)
BCF = std::bind(&Inliner::updateBlockFreq, this, CS, _1, _2);
InlineFunctionInfo InlineInfo(&CG, ACT, BCF);
// Attempt to inline the function.
[PM/AA] Rebuild LLVM's alias analysis infrastructure in a way compatible with the new pass manager, and no longer relying on analysis groups. This builds essentially a ground-up new AA infrastructure stack for LLVM. The core ideas are the same that are used throughout the new pass manager: type erased polymorphism and direct composition. The design is as follows: - FunctionAAResults is a type-erasing alias analysis results aggregation interface to walk a single query across a range of results from different alias analyses. Currently this is function-specific as we always assume that aliasing queries are *within* a function. - AAResultBase is a CRTP utility providing stub implementations of various parts of the alias analysis result concept, notably in several cases in terms of other more general parts of the interface. This can be used to implement only a narrow part of the interface rather than the entire interface. This isn't really ideal, this logic should be hoisted into FunctionAAResults as currently it will cause a significant amount of redundant work, but it faithfully models the behavior of the prior infrastructure. - All the alias analysis passes are ported to be wrapper passes for the legacy PM and new-style analysis passes for the new PM with a shared result object. In some cases (most notably CFL), this is an extremely naive approach that we should revisit when we can specialize for the new pass manager. - BasicAA has been restructured to reflect that it is much more fundamentally a function analysis because it uses dominator trees and loop info that need to be constructed for each function. All of the references to getting alias analysis results have been updated to use the new aggregation interface. All the preservation and other pass management code has been updated accordingly. The way the FunctionAAResultsWrapperPass works is to detect the available alias analyses when run, and add them to the results object. This means that we should be able to continue to respect when various passes are added to the pipeline, for example adding CFL or adding TBAA passes should just cause their results to be available and to get folded into this. The exception to this rule is BasicAA which really needs to be a function pass due to using dominator trees and loop info. As a consequence, the FunctionAAResultsWrapperPass directly depends on BasicAA and always includes it in the aggregation. This has significant implications for preserving analyses. Generally, most passes shouldn't bother preserving FunctionAAResultsWrapperPass because rebuilding the results just updates the set of known AA passes. The exception to this rule are LoopPass instances which need to preserve all the function analyses that the loop pass manager will end up needing. This means preserving both BasicAAWrapperPass and the aggregating FunctionAAResultsWrapperPass. Now, when preserving an alias analysis, you do so by directly preserving that analysis. This is only necessary for non-immutable-pass-provided alias analyses though, and there are only three of interest: BasicAA, GlobalsAA (formerly GlobalsModRef), and SCEVAA. Usually BasicAA is preserved when needed because it (like DominatorTree and LoopInfo) is marked as a CFG-only pass. I've expanded GlobalsAA into the preserved set everywhere we previously were preserving all of AliasAnalysis, and I've added SCEVAA in the intersection of that with where we preserve SCEV itself. One significant challenge to all of this is that the CGSCC passes were actually using the alias analysis implementations by taking advantage of a pretty amazing set of loop holes in the old pass manager's analysis management code which allowed analysis groups to slide through in many cases. Moving away from analysis groups makes this problem much more obvious. To fix it, I've leveraged the flexibility the design of the new PM components provides to just directly construct the relevant alias analyses for the relevant functions in the IPO passes that need them. This is a bit hacky, but should go away with the new pass manager, and is already in many ways cleaner than the prior state. Another significant challenge is that various facilities of the old alias analysis infrastructure just don't fit any more. The most significant of these is the alias analysis 'counter' pass. That pass relied on the ability to snoop on AA queries at different points in the analysis group chain. Instead, I'm planning to build printing functionality directly into the aggregation layer. I've not included that in this patch merely to keep it smaller. Note that all of this needs a nearly complete rewrite of the AA documentation. I'm planning to do that, but I'd like to make sure the new design settles, and to flesh out a bit more of what it looks like in the new pass manager first. Differential Revision: http://reviews.llvm.org/D12080 llvm-svn: 247167
2015-09-09 19:55:00 +02:00
if (!InlineCallIfPossible(*this, CS, InlineInfo, InlinedArrayAllocas,
InlineHistoryID, InsertLifetime)) {
emitOptimizationRemarkMissed(CallerCtx, DEBUG_TYPE, *Caller, DLoc,
Twine(Callee->getName() +
" will not be inlined into " +
Caller->getName()));
implement a nice little efficiency hack in the inliner. Since we're now running IPSCCP early, and we run functionattrs interlaced with the inliner, we often (particularly for small or noop functions) completely propagate all of the information about a call to its call site in IPSSCP (making a call dead) and functionattrs is smart enough to realize that the function is readonly (because it is interlaced with inliner). To improve compile time and make the inliner threshold more accurate, realize that we don't have to inline dead readonly function calls. Instead, just delete the call. This happens all the time for C++ codes, here are some counters from opt/llvm-ld counting the number of times calls were deleted vs inlined on various apps: Tramp3d opt: 5033 inline - Number of call sites deleted, not inlined 24596 inline - Number of functions inlined llvm-ld: 667 inline - Number of functions deleted because all callers found 699 inline - Number of functions inlined 483.xalancbmk opt: 8096 inline - Number of call sites deleted, not inlined 62528 inline - Number of functions inlined llvm-ld: 217 inline - Number of allocas merged together 2158 inline - Number of functions inlined 471.omnetpp: 331 inline - Number of call sites deleted, not inlined 8981 inline - Number of functions inlined llvm-ld: 171 inline - Number of functions deleted because all callers found 629 inline - Number of functions inlined Deleting a call is much faster than inlining it, and is insensitive to the size of the callee. :) llvm-svn: 86975
2009-11-12 08:56:08 +01:00
continue;
}
updateEntryCount(CallSiteBlock, Callee);
// The instruction following the call is part of a new basic block
// created during the inlining process. This does not have an entry in
// the BFI. We create an entry by copying the frequency of the original
// block containing the call.
copyBlockFrequency(CallSiteBlock, CallSuccessor->getParent());
implement a nice little efficiency hack in the inliner. Since we're now running IPSCCP early, and we run functionattrs interlaced with the inliner, we often (particularly for small or noop functions) completely propagate all of the information about a call to its call site in IPSSCP (making a call dead) and functionattrs is smart enough to realize that the function is readonly (because it is interlaced with inliner). To improve compile time and make the inliner threshold more accurate, realize that we don't have to inline dead readonly function calls. Instead, just delete the call. This happens all the time for C++ codes, here are some counters from opt/llvm-ld counting the number of times calls were deleted vs inlined on various apps: Tramp3d opt: 5033 inline - Number of call sites deleted, not inlined 24596 inline - Number of functions inlined llvm-ld: 667 inline - Number of functions deleted because all callers found 699 inline - Number of functions inlined 483.xalancbmk opt: 8096 inline - Number of call sites deleted, not inlined 62528 inline - Number of functions inlined llvm-ld: 217 inline - Number of allocas merged together 2158 inline - Number of functions inlined 471.omnetpp: 331 inline - Number of call sites deleted, not inlined 8981 inline - Number of functions inlined llvm-ld: 171 inline - Number of functions deleted because all callers found 629 inline - Number of functions inlined Deleting a call is much faster than inlining it, and is insensitive to the size of the callee. :) llvm-svn: 86975
2009-11-12 08:56:08 +01:00
++NumInlined;
// Report the inline decision.
emitOptimizationRemark(
CallerCtx, DEBUG_TYPE, *Caller, DLoc,
Twine(Callee->getName() + " inlined into " + Caller->getName()));
// If inlining this function gave us any new call sites, throw them
// onto our worklist to process. They are useful inline candidates.
if (!InlineInfo.InlinedCalls.empty()) {
// Create a new inline history entry for this, so that we remember
// that these new callsites came about due to inlining Callee.
int NewHistoryID = InlineHistory.size();
InlineHistory.push_back(std::make_pair(Callee, InlineHistoryID));
for (Value *Ptr : InlineInfo.InlinedCalls)
CallSites.push_back(std::make_pair(CallSite(Ptr), NewHistoryID));
}
implement a nice little efficiency hack in the inliner. Since we're now running IPSCCP early, and we run functionattrs interlaced with the inliner, we often (particularly for small or noop functions) completely propagate all of the information about a call to its call site in IPSSCP (making a call dead) and functionattrs is smart enough to realize that the function is readonly (because it is interlaced with inliner). To improve compile time and make the inliner threshold more accurate, realize that we don't have to inline dead readonly function calls. Instead, just delete the call. This happens all the time for C++ codes, here are some counters from opt/llvm-ld counting the number of times calls were deleted vs inlined on various apps: Tramp3d opt: 5033 inline - Number of call sites deleted, not inlined 24596 inline - Number of functions inlined llvm-ld: 667 inline - Number of functions deleted because all callers found 699 inline - Number of functions inlined 483.xalancbmk opt: 8096 inline - Number of call sites deleted, not inlined 62528 inline - Number of functions inlined llvm-ld: 217 inline - Number of allocas merged together 2158 inline - Number of functions inlined 471.omnetpp: 331 inline - Number of call sites deleted, not inlined 8981 inline - Number of functions inlined llvm-ld: 171 inline - Number of functions deleted because all callers found 629 inline - Number of functions inlined Deleting a call is much faster than inlining it, and is insensitive to the size of the callee. :) llvm-svn: 86975
2009-11-12 08:56:08 +01:00
}
implement a nice little efficiency hack in the inliner. Since we're now running IPSCCP early, and we run functionattrs interlaced with the inliner, we often (particularly for small or noop functions) completely propagate all of the information about a call to its call site in IPSSCP (making a call dead) and functionattrs is smart enough to realize that the function is readonly (because it is interlaced with inliner). To improve compile time and make the inliner threshold more accurate, realize that we don't have to inline dead readonly function calls. Instead, just delete the call. This happens all the time for C++ codes, here are some counters from opt/llvm-ld counting the number of times calls were deleted vs inlined on various apps: Tramp3d opt: 5033 inline - Number of call sites deleted, not inlined 24596 inline - Number of functions inlined llvm-ld: 667 inline - Number of functions deleted because all callers found 699 inline - Number of functions inlined 483.xalancbmk opt: 8096 inline - Number of call sites deleted, not inlined 62528 inline - Number of functions inlined llvm-ld: 217 inline - Number of allocas merged together 2158 inline - Number of functions inlined 471.omnetpp: 331 inline - Number of call sites deleted, not inlined 8981 inline - Number of functions inlined llvm-ld: 171 inline - Number of functions deleted because all callers found 629 inline - Number of functions inlined Deleting a call is much faster than inlining it, and is insensitive to the size of the callee. :) llvm-svn: 86975
2009-11-12 08:56:08 +01:00
// If we inlined or deleted the last possible call site to the function,
// delete the function body now.
if (Callee && Callee->use_empty() && Callee->hasLocalLinkage() &&
// TODO: Can remove if in SCC now.
!SCCFunctions.count(Callee) &&
// The function may be apparently dead, but if there are indirect
// callgraph references to the node, we cannot delete it yet, this
// could invalidate the CGSCC iterator.
CG[Callee]->getNumReferences() == 0) {
DEBUG(dbgs() << " -> Deleting dead function: "
<< Callee->getName() << "\n");
CallGraphNode *CalleeNode = CG[Callee];
// Remove any call graph edges from the callee to its callees.
CalleeNode->removeAllCalledFunctions();
// Removing the node for callee from the call graph and delete it.
Function *F = CG.removeFunctionFromModule(CalleeNode);
invalidateBFI(F);
delete F;
++NumDeleted;
}
// Remove this call site from the list. If possible, use
// swap/pop_back for efficiency, but do not use it if doing so would
// move a call site to a function in this SCC before the
// 'FirstCallInSCC' barrier.
if (SCC.isSingular()) {
CallSites[CSi] = CallSites.back();
CallSites.pop_back();
} else {
CallSites.erase(CallSites.begin()+CSi);
}
--CSi;
Changed = true;
LocalChange = true;
}
} while (LocalChange);
invalidateBFI(SCC);
return Changed;
}
/// Remove now-dead linkonce functions at the end of
/// processing to avoid breaking the SCC traversal.
bool Inliner::doFinalization(CallGraph &CG) {
return removeDeadFunctions(CG);
}
/// Remove dead functions that are not included in DNR (Do Not Remove) list.
Start removing the use of an ad-hoc 'never inline' set and instead directly query the function information which this set was representing. This simplifies the interface of the inline cost analysis, and makes the always-inline pass significantly more efficient. Previously, always-inline would first make a single set of every function in the module *except* those marked with the always-inline attribute. It would then query this set at every call site to see if the function was a member of the set, and if so, refuse to inline it. This is quite wasteful. Instead, simply check the function attribute directly when looking at the callsite. The normal inliner also had similar redundancy. It added every function in the module with the noinline attribute to its set to ignore, even though inside the cost analysis function we *already tested* the noinline attribute and produced the same result. The only tricky part of removing this is that we have to be able to correctly remove only the functions inlined by the always-inline pass when finalizing, which requires a bit of a hack. Still, much less of a hack than the set of all non-always-inline functions was. While I was touching this function, I switched a heavy-weight set to a vector with sort+unique. The algorithm already had a two-phase insert and removal pattern, we were just needlessly paying the uniquing cost on every insert. This probably speeds up some compiles by a small amount (-O0 compiles with lots of always-inline, so potentially heavy libc++ users), but I've not tried to measure it. I believe there is no functional change here, but yell if you spot one. None are intended. Finally, the direction this is going in is to greatly simplify the inline cost query interface so that we can replace its implementation with a much more clever one. Along the way, all the APIs get simplified, so it seems incrementally good. llvm-svn: 152903
2012-03-16 07:10:13 +01:00
bool Inliner::removeDeadFunctions(CallGraph &CG, bool AlwaysInlineOnly) {
SmallVector<CallGraphNode*, 16> FunctionsToRemove;
SmallVector<CallGraphNode *, 16> DeadFunctionsInComdats;
SmallDenseMap<const Comdat *, int, 16> ComdatEntriesAlive;
auto RemoveCGN = [&](CallGraphNode *CGN) {
// Remove any call graph edges from the function to its callees.
CGN->removeAllCalledFunctions();
// Remove any edges from the external node to the function's call graph
// node. These edges might have been made irrelegant due to
// optimization of the program.
CG.getExternalCallingNode()->removeAnyCallEdgeTo(CGN);
// Removing the node for callee from the call graph and delete it.
FunctionsToRemove.push_back(CGN);
};
// Scan for all of the functions, looking for ones that should now be removed
// from the program. Insert the dead ones in the FunctionsToRemove set.
for (const auto &I : CG) {
CallGraphNode *CGN = I.second.get();
Function *F = CGN->getFunction();
Start removing the use of an ad-hoc 'never inline' set and instead directly query the function information which this set was representing. This simplifies the interface of the inline cost analysis, and makes the always-inline pass significantly more efficient. Previously, always-inline would first make a single set of every function in the module *except* those marked with the always-inline attribute. It would then query this set at every call site to see if the function was a member of the set, and if so, refuse to inline it. This is quite wasteful. Instead, simply check the function attribute directly when looking at the callsite. The normal inliner also had similar redundancy. It added every function in the module with the noinline attribute to its set to ignore, even though inside the cost analysis function we *already tested* the noinline attribute and produced the same result. The only tricky part of removing this is that we have to be able to correctly remove only the functions inlined by the always-inline pass when finalizing, which requires a bit of a hack. Still, much less of a hack than the set of all non-always-inline functions was. While I was touching this function, I switched a heavy-weight set to a vector with sort+unique. The algorithm already had a two-phase insert and removal pattern, we were just needlessly paying the uniquing cost on every insert. This probably speeds up some compiles by a small amount (-O0 compiles with lots of always-inline, so potentially heavy libc++ users), but I've not tried to measure it. I believe there is no functional change here, but yell if you spot one. None are intended. Finally, the direction this is going in is to greatly simplify the inline cost query interface so that we can replace its implementation with a much more clever one. Along the way, all the APIs get simplified, so it seems incrementally good. llvm-svn: 152903
2012-03-16 07:10:13 +01:00
if (!F || F->isDeclaration())
continue;
// Handle the case when this function is called and we only want to care
// about always-inline functions. This is a bit of a hack to share code
// between here and the InlineAlways pass.
if (AlwaysInlineOnly && !F->hasFnAttribute(Attribute::AlwaysInline))
Start removing the use of an ad-hoc 'never inline' set and instead directly query the function information which this set was representing. This simplifies the interface of the inline cost analysis, and makes the always-inline pass significantly more efficient. Previously, always-inline would first make a single set of every function in the module *except* those marked with the always-inline attribute. It would then query this set at every call site to see if the function was a member of the set, and if so, refuse to inline it. This is quite wasteful. Instead, simply check the function attribute directly when looking at the callsite. The normal inliner also had similar redundancy. It added every function in the module with the noinline attribute to its set to ignore, even though inside the cost analysis function we *already tested* the noinline attribute and produced the same result. The only tricky part of removing this is that we have to be able to correctly remove only the functions inlined by the always-inline pass when finalizing, which requires a bit of a hack. Still, much less of a hack than the set of all non-always-inline functions was. While I was touching this function, I switched a heavy-weight set to a vector with sort+unique. The algorithm already had a two-phase insert and removal pattern, we were just needlessly paying the uniquing cost on every insert. This probably speeds up some compiles by a small amount (-O0 compiles with lots of always-inline, so potentially heavy libc++ users), but I've not tried to measure it. I believe there is no functional change here, but yell if you spot one. None are intended. Finally, the direction this is going in is to greatly simplify the inline cost query interface so that we can replace its implementation with a much more clever one. Along the way, all the APIs get simplified, so it seems incrementally good. llvm-svn: 152903
2012-03-16 07:10:13 +01:00
continue;
// If the only remaining users of the function are dead constants, remove
// them.
F->removeDeadConstantUsers();
if (!F->isDefTriviallyDead())
continue;
// It is unsafe to drop a function with discardable linkage from a COMDAT
// without also dropping the other members of the COMDAT.
// The inliner doesn't visit non-function entities which are in COMDAT
// groups so it is unsafe to do so *unless* the linkage is local.
if (!F->hasLocalLinkage()) {
if (const Comdat *C = F->getComdat()) {
--ComdatEntriesAlive[C];
DeadFunctionsInComdats.push_back(CGN);
continue;
}
}
RemoveCGN(CGN);
}
if (!DeadFunctionsInComdats.empty()) {
// Count up all the entities in COMDAT groups
auto ComdatGroupReferenced = [&](const Comdat *C) {
auto I = ComdatEntriesAlive.find(C);
if (I != ComdatEntriesAlive.end())
++(I->getSecond());
};
for (const Function &F : CG.getModule())
if (const Comdat *C = F.getComdat())
ComdatGroupReferenced(C);
for (const GlobalVariable &GV : CG.getModule().globals())
if (const Comdat *C = GV.getComdat())
ComdatGroupReferenced(C);
for (const GlobalAlias &GA : CG.getModule().aliases())
if (const Comdat *C = GA.getComdat())
ComdatGroupReferenced(C);
for (CallGraphNode *CGN : DeadFunctionsInComdats) {
Function *F = CGN->getFunction();
const Comdat *C = F->getComdat();
int NumAlive = ComdatEntriesAlive[C];
// We can remove functions in a COMDAT group if the entire group is dead.
assert(NumAlive >= 0);
if (NumAlive > 0)
continue;
RemoveCGN(CGN);
}
}
Start removing the use of an ad-hoc 'never inline' set and instead directly query the function information which this set was representing. This simplifies the interface of the inline cost analysis, and makes the always-inline pass significantly more efficient. Previously, always-inline would first make a single set of every function in the module *except* those marked with the always-inline attribute. It would then query this set at every call site to see if the function was a member of the set, and if so, refuse to inline it. This is quite wasteful. Instead, simply check the function attribute directly when looking at the callsite. The normal inliner also had similar redundancy. It added every function in the module with the noinline attribute to its set to ignore, even though inside the cost analysis function we *already tested* the noinline attribute and produced the same result. The only tricky part of removing this is that we have to be able to correctly remove only the functions inlined by the always-inline pass when finalizing, which requires a bit of a hack. Still, much less of a hack than the set of all non-always-inline functions was. While I was touching this function, I switched a heavy-weight set to a vector with sort+unique. The algorithm already had a two-phase insert and removal pattern, we were just needlessly paying the uniquing cost on every insert. This probably speeds up some compiles by a small amount (-O0 compiles with lots of always-inline, so potentially heavy libc++ users), but I've not tried to measure it. I believe there is no functional change here, but yell if you spot one. None are intended. Finally, the direction this is going in is to greatly simplify the inline cost query interface so that we can replace its implementation with a much more clever one. Along the way, all the APIs get simplified, so it seems incrementally good. llvm-svn: 152903
2012-03-16 07:10:13 +01:00
if (FunctionsToRemove.empty())
return false;
// Now that we know which functions to delete, do so. We didn't want to do
// this inline, because that would invalidate our CallGraph::iterator
// objects. :(
//
Start removing the use of an ad-hoc 'never inline' set and instead directly query the function information which this set was representing. This simplifies the interface of the inline cost analysis, and makes the always-inline pass significantly more efficient. Previously, always-inline would first make a single set of every function in the module *except* those marked with the always-inline attribute. It would then query this set at every call site to see if the function was a member of the set, and if so, refuse to inline it. This is quite wasteful. Instead, simply check the function attribute directly when looking at the callsite. The normal inliner also had similar redundancy. It added every function in the module with the noinline attribute to its set to ignore, even though inside the cost analysis function we *already tested* the noinline attribute and produced the same result. The only tricky part of removing this is that we have to be able to correctly remove only the functions inlined by the always-inline pass when finalizing, which requires a bit of a hack. Still, much less of a hack than the set of all non-always-inline functions was. While I was touching this function, I switched a heavy-weight set to a vector with sort+unique. The algorithm already had a two-phase insert and removal pattern, we were just needlessly paying the uniquing cost on every insert. This probably speeds up some compiles by a small amount (-O0 compiles with lots of always-inline, so potentially heavy libc++ users), but I've not tried to measure it. I believe there is no functional change here, but yell if you spot one. None are intended. Finally, the direction this is going in is to greatly simplify the inline cost query interface so that we can replace its implementation with a much more clever one. Along the way, all the APIs get simplified, so it seems incrementally good. llvm-svn: 152903
2012-03-16 07:10:13 +01:00
// Note that it doesn't matter that we are iterating over a non-stable order
// here to do this, it doesn't matter which order the functions are deleted
// in.
array_pod_sort(FunctionsToRemove.begin(), FunctionsToRemove.end());
Start removing the use of an ad-hoc 'never inline' set and instead directly query the function information which this set was representing. This simplifies the interface of the inline cost analysis, and makes the always-inline pass significantly more efficient. Previously, always-inline would first make a single set of every function in the module *except* those marked with the always-inline attribute. It would then query this set at every call site to see if the function was a member of the set, and if so, refuse to inline it. This is quite wasteful. Instead, simply check the function attribute directly when looking at the callsite. The normal inliner also had similar redundancy. It added every function in the module with the noinline attribute to its set to ignore, even though inside the cost analysis function we *already tested* the noinline attribute and produced the same result. The only tricky part of removing this is that we have to be able to correctly remove only the functions inlined by the always-inline pass when finalizing, which requires a bit of a hack. Still, much less of a hack than the set of all non-always-inline functions was. While I was touching this function, I switched a heavy-weight set to a vector with sort+unique. The algorithm already had a two-phase insert and removal pattern, we were just needlessly paying the uniquing cost on every insert. This probably speeds up some compiles by a small amount (-O0 compiles with lots of always-inline, so potentially heavy libc++ users), but I've not tried to measure it. I believe there is no functional change here, but yell if you spot one. None are intended. Finally, the direction this is going in is to greatly simplify the inline cost query interface so that we can replace its implementation with a much more clever one. Along the way, all the APIs get simplified, so it seems incrementally good. llvm-svn: 152903
2012-03-16 07:10:13 +01:00
FunctionsToRemove.erase(std::unique(FunctionsToRemove.begin(),
FunctionsToRemove.end()),
FunctionsToRemove.end());
for (CallGraphNode *CGN : FunctionsToRemove) {
Function *F = CG.removeFunctionFromModule(CGN);
invalidateBFI(F);
delete F;
++NumDeleted;
}
Start removing the use of an ad-hoc 'never inline' set and instead directly query the function information which this set was representing. This simplifies the interface of the inline cost analysis, and makes the always-inline pass significantly more efficient. Previously, always-inline would first make a single set of every function in the module *except* those marked with the always-inline attribute. It would then query this set at every call site to see if the function was a member of the set, and if so, refuse to inline it. This is quite wasteful. Instead, simply check the function attribute directly when looking at the callsite. The normal inliner also had similar redundancy. It added every function in the module with the noinline attribute to its set to ignore, even though inside the cost analysis function we *already tested* the noinline attribute and produced the same result. The only tricky part of removing this is that we have to be able to correctly remove only the functions inlined by the always-inline pass when finalizing, which requires a bit of a hack. Still, much less of a hack than the set of all non-always-inline functions was. While I was touching this function, I switched a heavy-weight set to a vector with sort+unique. The algorithm already had a two-phase insert and removal pattern, we were just needlessly paying the uniquing cost on every insert. This probably speeds up some compiles by a small amount (-O0 compiles with lots of always-inline, so potentially heavy libc++ users), but I've not tried to measure it. I believe there is no functional change here, but yell if you spot one. None are intended. Finally, the direction this is going in is to greatly simplify the inline cost query interface so that we can replace its implementation with a much more clever one. Along the way, all the APIs get simplified, so it seems incrementally good. llvm-svn: 152903
2012-03-16 07:10:13 +01:00
return true;
}