2013-11-17 07:59:05 +08:00
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//===-- LoopReroll.cpp - Loop rerolling pass ------------------------------===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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//
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// This pass implements a simple loop reroller.
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//
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//===----------------------------------------------------------------------===//
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#include "llvm/Transforms/Scalar.h"
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2015-01-30 05:52:03 +08:00
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#include "llvm/ADT/MapVector.h"
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2014-01-07 19:48:04 +08:00
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#include "llvm/ADT/STLExtras.h"
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2015-01-30 05:52:03 +08:00
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#include "llvm/ADT/SmallBitVector.h"
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2013-11-17 07:59:05 +08:00
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#include "llvm/ADT/SmallSet.h"
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#include "llvm/ADT/Statistic.h"
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#include "llvm/Analysis/AliasAnalysis.h"
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#include "llvm/Analysis/AliasSetTracker.h"
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#include "llvm/Analysis/LoopPass.h"
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#include "llvm/Analysis/ScalarEvolution.h"
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#include "llvm/Analysis/ScalarEvolutionExpander.h"
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#include "llvm/Analysis/ScalarEvolutionExpressions.h"
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2015-03-24 03:32:43 +08:00
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#include "llvm/Analysis/TargetLibraryInfo.h"
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2013-11-17 07:59:05 +08:00
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#include "llvm/Analysis/ValueTracking.h"
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#include "llvm/IR/DataLayout.h"
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2014-01-13 17:26:24 +08:00
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#include "llvm/IR/Dominators.h"
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2013-11-17 07:59:05 +08:00
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#include "llvm/IR/IntrinsicInst.h"
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#include "llvm/Support/CommandLine.h"
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#include "llvm/Support/Debug.h"
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#include "llvm/Support/raw_ostream.h"
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#include "llvm/Transforms/Utils/BasicBlockUtils.h"
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#include "llvm/Transforms/Utils/Local.h"
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#include "llvm/Transforms/Utils/LoopUtils.h"
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using namespace llvm;
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2014-04-22 10:55:47 +08:00
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#define DEBUG_TYPE "loop-reroll"
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2013-11-17 07:59:05 +08:00
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STATISTIC(NumRerolledLoops, "Number of rerolled loops");
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static cl::opt<unsigned>
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MaxInc("max-reroll-increment", cl::init(2048), cl::Hidden,
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cl::desc("The maximum increment for loop rerolling"));
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2015-02-12 23:54:14 +08:00
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static cl::opt<unsigned>
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NumToleratedFailedMatches("reroll-num-tolerated-failed-matches", cl::init(400),
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cl::Hidden,
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cl::desc("The maximum number of failures to tolerate"
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" during fuzzy matching. (default: 400)"));
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2013-11-17 07:59:05 +08:00
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// This loop re-rolling transformation aims to transform loops like this:
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//
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// int foo(int a);
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// void bar(int *x) {
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// for (int i = 0; i < 500; i += 3) {
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// foo(i);
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// foo(i+1);
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// foo(i+2);
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// }
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// }
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//
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// into a loop like this:
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//
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// void bar(int *x) {
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// for (int i = 0; i < 500; ++i)
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// foo(i);
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// }
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//
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// It does this by looking for loops that, besides the latch code, are composed
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// of isomorphic DAGs of instructions, with each DAG rooted at some increment
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// to the induction variable, and where each DAG is isomorphic to the DAG
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// rooted at the induction variable (excepting the sub-DAGs which root the
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// other induction-variable increments). In other words, we're looking for loop
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// bodies of the form:
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//
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// %iv = phi [ (preheader, ...), (body, %iv.next) ]
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// f(%iv)
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// %iv.1 = add %iv, 1 <-- a root increment
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// f(%iv.1)
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// %iv.2 = add %iv, 2 <-- a root increment
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// f(%iv.2)
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// %iv.scale_m_1 = add %iv, scale-1 <-- a root increment
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// f(%iv.scale_m_1)
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// ...
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// %iv.next = add %iv, scale
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// %cmp = icmp(%iv, ...)
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// br %cmp, header, exit
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//
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// where each f(i) is a set of instructions that, collectively, are a function
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// only of i (and other loop-invariant values).
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//
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// As a special case, we can also reroll loops like this:
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//
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// int foo(int);
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// void bar(int *x) {
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// for (int i = 0; i < 500; ++i) {
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// x[3*i] = foo(0);
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// x[3*i+1] = foo(0);
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// x[3*i+2] = foo(0);
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// }
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// }
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//
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// into this:
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//
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// void bar(int *x) {
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// for (int i = 0; i < 1500; ++i)
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// x[i] = foo(0);
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// }
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//
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// in which case, we're looking for inputs like this:
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//
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// %iv = phi [ (preheader, ...), (body, %iv.next) ]
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// %scaled.iv = mul %iv, scale
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// f(%scaled.iv)
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// %scaled.iv.1 = add %scaled.iv, 1
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// f(%scaled.iv.1)
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// %scaled.iv.2 = add %scaled.iv, 2
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// f(%scaled.iv.2)
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// %scaled.iv.scale_m_1 = add %scaled.iv, scale-1
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// f(%scaled.iv.scale_m_1)
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// ...
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// %iv.next = add %iv, 1
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// %cmp = icmp(%iv, ...)
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// br %cmp, header, exit
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namespace {
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2015-01-30 05:52:03 +08:00
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enum IterationLimits {
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/// The maximum number of iterations that we'll try and reroll. This
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/// has to be less than 25 in order to fit into a SmallBitVector.
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IL_MaxRerollIterations = 16,
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/// The bitvector index used by loop induction variables and other
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2015-02-11 17:19:47 +08:00
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/// instructions that belong to all iterations.
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IL_All,
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2015-01-30 05:52:03 +08:00
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IL_End
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};
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2013-11-17 07:59:05 +08:00
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class LoopReroll : public LoopPass {
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public:
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static char ID; // Pass ID, replacement for typeid
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LoopReroll() : LoopPass(ID) {
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initializeLoopRerollPass(*PassRegistry::getPassRegistry());
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}
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2014-03-05 17:10:37 +08:00
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bool runOnLoop(Loop *L, LPPassManager &LPM) override;
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2013-11-17 07:59:05 +08:00
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2014-03-05 17:10:37 +08:00
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void getAnalysisUsage(AnalysisUsage &AU) const override {
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[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
2015-09-10 01:55:00 +08:00
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AU.addRequired<AAResultsWrapperPass>();
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2015-01-17 22:16:18 +08:00
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AU.addRequired<LoopInfoWrapperPass>();
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AU.addPreserved<LoopInfoWrapperPass>();
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2014-01-13 21:07:17 +08:00
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AU.addRequired<DominatorTreeWrapperPass>();
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AU.addPreserved<DominatorTreeWrapperPass>();
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[PM] Port ScalarEvolution to the new pass manager.
This change makes ScalarEvolution a stand-alone object and just produces
one from a pass as needed. Making this work well requires making the
object movable, using references instead of overwritten pointers in
a number of places, and other refactorings.
I've also wired it up to the new pass manager and added a RUN line to
a test to exercise it under the new pass manager. This includes basic
printing support much like with other analyses.
But there is a big and somewhat scary change here. Prior to this patch
ScalarEvolution was never *actually* invalidated!!! Re-running the pass
just re-wired up the various other analyses and didn't remove any of the
existing entries in the SCEV caches or clear out anything at all. This
might seem OK as everything in SCEV that can uses ValueHandles to track
updates to the values that serve as SCEV keys. However, this still means
that as we ran SCEV over each function in the module, we kept
accumulating more and more SCEVs into the cache. At the end, we would
have a SCEV cache with every value that we ever needed a SCEV for in the
entire module!!! Yowzers. The releaseMemory routine would dump all of
this, but that isn't realy called during normal runs of the pipeline as
far as I can see.
To make matters worse, there *is* actually a key that we don't update
with value handles -- there is a map keyed off of Loop*s. Because
LoopInfo *does* release its memory from run to run, it is entirely
possible to run SCEV over one function, then over another function, and
then lookup a Loop* from the second function but find an entry inserted
for the first function! Ouch.
To make matters still worse, there are plenty of updates that *don't*
trip a value handle. It seems incredibly unlikely that today GVN or
another pass that invalidates SCEV can update values in *just* such
a way that a subsequent run of SCEV will incorrectly find lookups in
a cache, but it is theoretically possible and would be a nightmare to
debug.
With this refactoring, I've fixed all this by actually destroying and
recreating the ScalarEvolution object from run to run. Technically, this
could increase the amount of malloc traffic we see, but then again it is
also technically correct. ;] I don't actually think we're suffering from
tons of malloc traffic from SCEV because if we were, the fact that we
never clear the memory would seem more likely to have come up as an
actual problem before now. So, I've made the simple fix here. If in fact
there are serious issues with too much allocation and deallocation,
I can work on a clever fix that preserves the allocations (while
clearing the data) between each run, but I'd prefer to do that kind of
optimization with a test case / benchmark that shows why we need such
cleverness (and that can test that we actually make it faster). It's
possible that this will make some things faster by making the SCEV
caches have higher locality (due to being significantly smaller) so
until there is a clear benchmark, I think the simple change is best.
Differential Revision: http://reviews.llvm.org/D12063
llvm-svn: 245193
2015-08-17 10:08:17 +08:00
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AU.addRequired<ScalarEvolutionWrapperPass>();
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2015-01-15 18:41:28 +08:00
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AU.addRequired<TargetLibraryInfoWrapperPass>();
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2013-11-17 07:59:05 +08:00
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}
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2015-01-30 05:52:03 +08:00
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protected:
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2013-11-17 07:59:05 +08:00
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AliasAnalysis *AA;
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LoopInfo *LI;
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ScalarEvolution *SE;
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TargetLibraryInfo *TLI;
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DominatorTree *DT;
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2015-12-16 03:40:57 +08:00
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bool PreserveLCSSA;
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2013-11-17 07:59:05 +08:00
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typedef SmallVector<Instruction *, 16> SmallInstructionVector;
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typedef SmallSet<Instruction *, 16> SmallInstructionSet;
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2015-07-25 06:01:49 +08:00
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// Map between induction variable and its increment
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DenseMap<Instruction *, int64_t> IVToIncMap;
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// A chain of isomorphic instructions, identified by a single-use PHI
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2013-11-17 07:59:05 +08:00
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// representing a reduction. Only the last value may be used outside the
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// loop.
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struct SimpleLoopReduction {
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SimpleLoopReduction(Instruction *P, Loop *L)
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: Valid(false), Instructions(1, P) {
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assert(isa<PHINode>(P) && "First reduction instruction must be a PHI");
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add(L);
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}
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bool valid() const {
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return Valid;
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}
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Instruction *getPHI() const {
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assert(Valid && "Using invalid reduction");
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return Instructions.front();
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}
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Instruction *getReducedValue() const {
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assert(Valid && "Using invalid reduction");
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return Instructions.back();
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}
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Instruction *get(size_t i) const {
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assert(Valid && "Using invalid reduction");
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return Instructions[i+1];
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}
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Instruction *operator [] (size_t i) const { return get(i); }
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// The size, ignoring the initial PHI.
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size_t size() const {
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assert(Valid && "Using invalid reduction");
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return Instructions.size()-1;
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}
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typedef SmallInstructionVector::iterator iterator;
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typedef SmallInstructionVector::const_iterator const_iterator;
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iterator begin() {
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assert(Valid && "Using invalid reduction");
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2014-03-02 20:27:27 +08:00
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return std::next(Instructions.begin());
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2013-11-17 07:59:05 +08:00
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}
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const_iterator begin() const {
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assert(Valid && "Using invalid reduction");
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2014-03-02 20:27:27 +08:00
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return std::next(Instructions.begin());
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2013-11-17 07:59:05 +08:00
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}
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iterator end() { return Instructions.end(); }
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const_iterator end() const { return Instructions.end(); }
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protected:
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bool Valid;
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SmallInstructionVector Instructions;
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void add(Loop *L);
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};
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// The set of all reductions, and state tracking of possible reductions
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// during loop instruction processing.
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struct ReductionTracker {
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typedef SmallVector<SimpleLoopReduction, 16> SmallReductionVector;
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// Add a new possible reduction.
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2014-10-28 19:54:52 +08:00
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void addSLR(SimpleLoopReduction &SLR) { PossibleReds.push_back(SLR); }
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2013-11-17 07:59:05 +08:00
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// Setup to track possible reductions corresponding to the provided
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// rerolling scale. Only reductions with a number of non-PHI instructions
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// that is divisible by the scale are considered. Three instructions sets
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// are filled in:
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// - A set of all possible instructions in eligible reductions.
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// - A set of all PHIs in eligible reductions
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2014-10-28 19:54:52 +08:00
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// - A set of all reduced values (last instructions) in eligible
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// reductions.
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2013-11-17 07:59:05 +08:00
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void restrictToScale(uint64_t Scale,
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SmallInstructionSet &PossibleRedSet,
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SmallInstructionSet &PossibleRedPHISet,
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SmallInstructionSet &PossibleRedLastSet) {
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|
|
PossibleRedIdx.clear();
|
|
|
|
PossibleRedIter.clear();
|
|
|
|
Reds.clear();
|
|
|
|
|
|
|
|
for (unsigned i = 0, e = PossibleReds.size(); i != e; ++i)
|
|
|
|
if (PossibleReds[i].size() % Scale == 0) {
|
|
|
|
PossibleRedLastSet.insert(PossibleReds[i].getReducedValue());
|
|
|
|
PossibleRedPHISet.insert(PossibleReds[i].getPHI());
|
2014-10-28 19:53:30 +08:00
|
|
|
|
2013-11-17 07:59:05 +08:00
|
|
|
PossibleRedSet.insert(PossibleReds[i].getPHI());
|
|
|
|
PossibleRedIdx[PossibleReds[i].getPHI()] = i;
|
2014-10-28 19:54:05 +08:00
|
|
|
for (Instruction *J : PossibleReds[i]) {
|
|
|
|
PossibleRedSet.insert(J);
|
|
|
|
PossibleRedIdx[J] = i;
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// The functions below are used while processing the loop instructions.
|
|
|
|
|
|
|
|
// Are the two instructions both from reductions, and furthermore, from
|
|
|
|
// the same reduction?
|
|
|
|
bool isPairInSame(Instruction *J1, Instruction *J2) {
|
|
|
|
DenseMap<Instruction *, int>::iterator J1I = PossibleRedIdx.find(J1);
|
|
|
|
if (J1I != PossibleRedIdx.end()) {
|
|
|
|
DenseMap<Instruction *, int>::iterator J2I = PossibleRedIdx.find(J2);
|
|
|
|
if (J2I != PossibleRedIdx.end() && J1I->second == J2I->second)
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
// The two provided instructions, the first from the base iteration, and
|
|
|
|
// the second from iteration i, form a matched pair. If these are part of
|
|
|
|
// a reduction, record that fact.
|
|
|
|
void recordPair(Instruction *J1, Instruction *J2, unsigned i) {
|
|
|
|
if (PossibleRedIdx.count(J1)) {
|
|
|
|
assert(PossibleRedIdx.count(J2) &&
|
|
|
|
"Recording reduction vs. non-reduction instruction?");
|
|
|
|
|
|
|
|
PossibleRedIter[J1] = 0;
|
|
|
|
PossibleRedIter[J2] = i;
|
|
|
|
|
|
|
|
int Idx = PossibleRedIdx[J1];
|
|
|
|
assert(Idx == PossibleRedIdx[J2] &&
|
|
|
|
"Recording pair from different reductions?");
|
2013-11-17 09:21:54 +08:00
|
|
|
Reds.insert(Idx);
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// The functions below can be called after we've finished processing all
|
|
|
|
// instructions in the loop, and we know which reductions were selected.
|
|
|
|
|
|
|
|
bool validateSelected();
|
|
|
|
void replaceSelected();
|
|
|
|
|
|
|
|
protected:
|
|
|
|
// The vector of all possible reductions (for any scale).
|
|
|
|
SmallReductionVector PossibleReds;
|
|
|
|
|
|
|
|
DenseMap<Instruction *, int> PossibleRedIdx;
|
|
|
|
DenseMap<Instruction *, int> PossibleRedIter;
|
|
|
|
DenseSet<int> Reds;
|
|
|
|
};
|
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
// A DAGRootSet models an induction variable being used in a rerollable
|
|
|
|
// loop. For example,
|
|
|
|
//
|
|
|
|
// x[i*3+0] = y1
|
|
|
|
// x[i*3+1] = y2
|
|
|
|
// x[i*3+2] = y3
|
|
|
|
//
|
2015-07-25 06:01:49 +08:00
|
|
|
// Base instruction -> i*3
|
2015-02-11 17:19:47 +08:00
|
|
|
// +---+----+
|
|
|
|
// / | \
|
|
|
|
// ST[y1] +1 +2 <-- Roots
|
|
|
|
// | |
|
|
|
|
// ST[y2] ST[y3]
|
|
|
|
//
|
|
|
|
// There may be multiple DAGRoots, for example:
|
|
|
|
//
|
|
|
|
// x[i*2+0] = ... (1)
|
|
|
|
// x[i*2+1] = ... (1)
|
|
|
|
// x[i*2+4] = ... (2)
|
|
|
|
// x[i*2+5] = ... (2)
|
|
|
|
// x[(i+1234)*2+5678] = ... (3)
|
|
|
|
// x[(i+1234)*2+5679] = ... (3)
|
|
|
|
//
|
|
|
|
// The loop will be rerolled by adding a new loop induction variable,
|
|
|
|
// one for the Base instruction in each DAGRootSet.
|
|
|
|
//
|
|
|
|
struct DAGRootSet {
|
|
|
|
Instruction *BaseInst;
|
|
|
|
SmallInstructionVector Roots;
|
|
|
|
// The instructions between IV and BaseInst (but not including BaseInst).
|
|
|
|
SmallInstructionSet SubsumedInsts;
|
|
|
|
};
|
|
|
|
|
2015-01-29 21:48:05 +08:00
|
|
|
// The set of all DAG roots, and state tracking of all roots
|
|
|
|
// for a particular induction variable.
|
|
|
|
struct DAGRootTracker {
|
|
|
|
DAGRootTracker(LoopReroll *Parent, Loop *L, Instruction *IV,
|
|
|
|
ScalarEvolution *SE, AliasAnalysis *AA,
|
2015-12-16 03:40:57 +08:00
|
|
|
TargetLibraryInfo *TLI, DominatorTree *DT, LoopInfo *LI,
|
|
|
|
bool PreserveLCSSA,
|
2015-07-25 06:01:49 +08:00
|
|
|
DenseMap<Instruction *, int64_t> &IncrMap)
|
2015-12-16 03:40:57 +08:00
|
|
|
: Parent(Parent), L(L), SE(SE), AA(AA), TLI(TLI), DT(DT), LI(LI),
|
|
|
|
PreserveLCSSA(PreserveLCSSA), IV(IV), IVToIncMap(IncrMap) {}
|
2015-01-29 21:48:05 +08:00
|
|
|
|
|
|
|
/// Stage 1: Find all the DAG roots for the induction variable.
|
|
|
|
bool findRoots();
|
|
|
|
/// Stage 2: Validate if the found roots are valid.
|
|
|
|
bool validate(ReductionTracker &Reductions);
|
|
|
|
/// Stage 3: Assuming validate() returned true, perform the
|
|
|
|
/// replacement.
|
|
|
|
/// @param IterCount The maximum iteration count of L.
|
|
|
|
void replace(const SCEV *IterCount);
|
|
|
|
|
|
|
|
protected:
|
2015-01-30 05:52:03 +08:00
|
|
|
typedef MapVector<Instruction*, SmallBitVector> UsesTy;
|
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
bool findRootsRecursive(Instruction *IVU,
|
|
|
|
SmallInstructionSet SubsumedInsts);
|
|
|
|
bool findRootsBase(Instruction *IVU, SmallInstructionSet SubsumedInsts);
|
|
|
|
bool collectPossibleRoots(Instruction *Base,
|
|
|
|
std::map<int64_t,Instruction*> &Roots);
|
2015-01-29 21:48:05 +08:00
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
bool collectUsedInstructions(SmallInstructionSet &PossibleRedSet);
|
2015-01-29 21:48:05 +08:00
|
|
|
void collectInLoopUserSet(const SmallInstructionVector &Roots,
|
|
|
|
const SmallInstructionSet &Exclude,
|
|
|
|
const SmallInstructionSet &Final,
|
|
|
|
DenseSet<Instruction *> &Users);
|
|
|
|
void collectInLoopUserSet(Instruction *Root,
|
|
|
|
const SmallInstructionSet &Exclude,
|
|
|
|
const SmallInstructionSet &Final,
|
|
|
|
DenseSet<Instruction *> &Users);
|
|
|
|
|
2015-02-12 23:54:14 +08:00
|
|
|
UsesTy::iterator nextInstr(int Val, UsesTy &In,
|
|
|
|
const SmallInstructionSet &Exclude,
|
|
|
|
UsesTy::iterator *StartI=nullptr);
|
2015-02-11 17:19:47 +08:00
|
|
|
bool isBaseInst(Instruction *I);
|
|
|
|
bool isRootInst(Instruction *I);
|
2015-02-12 23:54:14 +08:00
|
|
|
bool instrDependsOn(Instruction *I,
|
|
|
|
UsesTy::iterator Start,
|
|
|
|
UsesTy::iterator End);
|
2015-01-30 05:52:03 +08:00
|
|
|
|
2015-01-29 21:48:05 +08:00
|
|
|
LoopReroll *Parent;
|
|
|
|
|
|
|
|
// Members of Parent, replicated here for brevity.
|
|
|
|
Loop *L;
|
|
|
|
ScalarEvolution *SE;
|
|
|
|
AliasAnalysis *AA;
|
|
|
|
TargetLibraryInfo *TLI;
|
2015-12-16 03:40:57 +08:00
|
|
|
DominatorTree *DT;
|
|
|
|
LoopInfo *LI;
|
|
|
|
bool PreserveLCSSA;
|
2015-01-29 21:48:05 +08:00
|
|
|
|
|
|
|
// The loop induction variable.
|
|
|
|
Instruction *IV;
|
|
|
|
// Loop step amount.
|
2015-07-25 06:01:49 +08:00
|
|
|
int64_t Inc;
|
2015-01-29 21:48:05 +08:00
|
|
|
// Loop reroll count; if Inc == 1, this records the scaling applied
|
|
|
|
// to the indvar: a[i*2+0] = ...; a[i*2+1] = ... ;
|
|
|
|
// If Inc is not 1, Scale = Inc.
|
|
|
|
uint64_t Scale;
|
|
|
|
// The roots themselves.
|
2015-02-11 17:19:47 +08:00
|
|
|
SmallVector<DAGRootSet,16> RootSets;
|
2015-01-29 21:48:05 +08:00
|
|
|
// All increment instructions for IV.
|
|
|
|
SmallInstructionVector LoopIncs;
|
2015-01-30 05:52:03 +08:00
|
|
|
// Map of all instructions in the loop (in order) to the iterations
|
2015-02-11 17:19:47 +08:00
|
|
|
// they are used in (or specially, IL_All for instructions
|
2015-01-30 05:52:03 +08:00
|
|
|
// used in the loop increment mechanism).
|
|
|
|
UsesTy Uses;
|
2015-07-25 06:01:49 +08:00
|
|
|
// Map between induction variable and its increment
|
|
|
|
DenseMap<Instruction *, int64_t> &IVToIncMap;
|
2015-01-29 21:48:05 +08:00
|
|
|
};
|
|
|
|
|
2013-11-17 07:59:05 +08:00
|
|
|
void collectPossibleIVs(Loop *L, SmallInstructionVector &PossibleIVs);
|
|
|
|
void collectPossibleReductions(Loop *L,
|
|
|
|
ReductionTracker &Reductions);
|
|
|
|
bool reroll(Instruction *IV, Loop *L, BasicBlock *Header, const SCEV *IterCount,
|
|
|
|
ReductionTracker &Reductions);
|
|
|
|
};
|
2015-06-23 17:49:53 +08:00
|
|
|
}
|
2013-11-17 07:59:05 +08:00
|
|
|
|
|
|
|
char LoopReroll::ID = 0;
|
|
|
|
INITIALIZE_PASS_BEGIN(LoopReroll, "loop-reroll", "Reroll loops", false, false)
|
[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
2015-09-10 01:55:00 +08:00
|
|
|
INITIALIZE_PASS_DEPENDENCY(AAResultsWrapperPass)
|
2015-01-17 22:16:18 +08:00
|
|
|
INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)
|
2014-01-13 21:07:17 +08:00
|
|
|
INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
|
[PM] Port ScalarEvolution to the new pass manager.
This change makes ScalarEvolution a stand-alone object and just produces
one from a pass as needed. Making this work well requires making the
object movable, using references instead of overwritten pointers in
a number of places, and other refactorings.
I've also wired it up to the new pass manager and added a RUN line to
a test to exercise it under the new pass manager. This includes basic
printing support much like with other analyses.
But there is a big and somewhat scary change here. Prior to this patch
ScalarEvolution was never *actually* invalidated!!! Re-running the pass
just re-wired up the various other analyses and didn't remove any of the
existing entries in the SCEV caches or clear out anything at all. This
might seem OK as everything in SCEV that can uses ValueHandles to track
updates to the values that serve as SCEV keys. However, this still means
that as we ran SCEV over each function in the module, we kept
accumulating more and more SCEVs into the cache. At the end, we would
have a SCEV cache with every value that we ever needed a SCEV for in the
entire module!!! Yowzers. The releaseMemory routine would dump all of
this, but that isn't realy called during normal runs of the pipeline as
far as I can see.
To make matters worse, there *is* actually a key that we don't update
with value handles -- there is a map keyed off of Loop*s. Because
LoopInfo *does* release its memory from run to run, it is entirely
possible to run SCEV over one function, then over another function, and
then lookup a Loop* from the second function but find an entry inserted
for the first function! Ouch.
To make matters still worse, there are plenty of updates that *don't*
trip a value handle. It seems incredibly unlikely that today GVN or
another pass that invalidates SCEV can update values in *just* such
a way that a subsequent run of SCEV will incorrectly find lookups in
a cache, but it is theoretically possible and would be a nightmare to
debug.
With this refactoring, I've fixed all this by actually destroying and
recreating the ScalarEvolution object from run to run. Technically, this
could increase the amount of malloc traffic we see, but then again it is
also technically correct. ;] I don't actually think we're suffering from
tons of malloc traffic from SCEV because if we were, the fact that we
never clear the memory would seem more likely to have come up as an
actual problem before now. So, I've made the simple fix here. If in fact
there are serious issues with too much allocation and deallocation,
I can work on a clever fix that preserves the allocations (while
clearing the data) between each run, but I'd prefer to do that kind of
optimization with a test case / benchmark that shows why we need such
cleverness (and that can test that we actually make it faster). It's
possible that this will make some things faster by making the SCEV
caches have higher locality (due to being significantly smaller) so
until there is a clear benchmark, I think the simple change is best.
Differential Revision: http://reviews.llvm.org/D12063
llvm-svn: 245193
2015-08-17 10:08:17 +08:00
|
|
|
INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass)
|
2015-01-15 18:41:28 +08:00
|
|
|
INITIALIZE_PASS_DEPENDENCY(TargetLibraryInfoWrapperPass)
|
2013-11-17 07:59:05 +08:00
|
|
|
INITIALIZE_PASS_END(LoopReroll, "loop-reroll", "Reroll loops", false, false)
|
|
|
|
|
|
|
|
Pass *llvm::createLoopRerollPass() {
|
|
|
|
return new LoopReroll;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Returns true if the provided instruction is used outside the given loop.
|
|
|
|
// This operates like Instruction::isUsedOutsideOfBlock, but considers PHIs in
|
|
|
|
// non-loop blocks to be outside the loop.
|
|
|
|
static bool hasUsesOutsideLoop(Instruction *I, Loop *L) {
|
2015-01-30 05:52:03 +08:00
|
|
|
for (User *U : I->users()) {
|
2014-03-09 11:16:01 +08:00
|
|
|
if (!L->contains(cast<Instruction>(U)))
|
2013-11-17 07:59:05 +08:00
|
|
|
return true;
|
2015-01-30 05:52:03 +08:00
|
|
|
}
|
2013-11-17 07:59:05 +08:00
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Collect the list of loop induction variables with respect to which it might
|
|
|
|
// be possible to reroll the loop.
|
|
|
|
void LoopReroll::collectPossibleIVs(Loop *L,
|
|
|
|
SmallInstructionVector &PossibleIVs) {
|
|
|
|
BasicBlock *Header = L->getHeader();
|
|
|
|
for (BasicBlock::iterator I = Header->begin(),
|
|
|
|
IE = Header->getFirstInsertionPt(); I != IE; ++I) {
|
|
|
|
if (!isa<PHINode>(I))
|
|
|
|
continue;
|
2016-01-26 03:36:30 +08:00
|
|
|
if (!I->getType()->isIntegerTy())
|
2013-11-17 07:59:05 +08:00
|
|
|
continue;
|
|
|
|
|
|
|
|
if (const SCEVAddRecExpr *PHISCEV =
|
2015-10-14 03:26:58 +08:00
|
|
|
dyn_cast<SCEVAddRecExpr>(SE->getSCEV(&*I))) {
|
2013-11-17 07:59:05 +08:00
|
|
|
if (PHISCEV->getLoop() != L)
|
|
|
|
continue;
|
|
|
|
if (!PHISCEV->isAffine())
|
|
|
|
continue;
|
2016-01-26 03:36:30 +08:00
|
|
|
if (const SCEVConstant *IncSCEV =
|
|
|
|
dyn_cast<SCEVConstant>(PHISCEV->getStepRecurrence(*SE))) {
|
|
|
|
const APInt &AInt = IncSCEV->getAPInt().abs();
|
2015-07-25 06:01:49 +08:00
|
|
|
if (IncSCEV->getValue()->isZero() || AInt.uge(MaxInc))
|
2013-11-17 07:59:05 +08:00
|
|
|
continue;
|
2015-10-14 03:26:58 +08:00
|
|
|
IVToIncMap[&*I] = IncSCEV->getValue()->getSExtValue();
|
2015-07-25 06:01:49 +08:00
|
|
|
DEBUG(dbgs() << "LRR: Possible IV: " << *I << " = " << *PHISCEV
|
|
|
|
<< "\n");
|
2015-10-14 03:26:58 +08:00
|
|
|
PossibleIVs.push_back(&*I);
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Add the remainder of the reduction-variable chain to the instruction vector
|
|
|
|
// (the initial PHINode has already been added). If successful, the object is
|
|
|
|
// marked as valid.
|
|
|
|
void LoopReroll::SimpleLoopReduction::add(Loop *L) {
|
|
|
|
assert(!Valid && "Cannot add to an already-valid chain");
|
|
|
|
|
|
|
|
// The reduction variable must be a chain of single-use instructions
|
|
|
|
// (including the PHI), except for the last value (which is used by the PHI
|
|
|
|
// and also outside the loop).
|
|
|
|
Instruction *C = Instructions.front();
|
2015-02-17 01:01:52 +08:00
|
|
|
if (C->user_empty())
|
|
|
|
return;
|
2013-11-17 07:59:05 +08:00
|
|
|
|
|
|
|
do {
|
2014-03-09 11:16:01 +08:00
|
|
|
C = cast<Instruction>(*C->user_begin());
|
2013-11-17 07:59:05 +08:00
|
|
|
if (C->hasOneUse()) {
|
|
|
|
if (!C->isBinaryOp())
|
|
|
|
return;
|
|
|
|
|
|
|
|
if (!(isa<PHINode>(Instructions.back()) ||
|
|
|
|
C->isSameOperationAs(Instructions.back())))
|
|
|
|
return;
|
|
|
|
|
|
|
|
Instructions.push_back(C);
|
|
|
|
}
|
|
|
|
} while (C->hasOneUse());
|
|
|
|
|
|
|
|
if (Instructions.size() < 2 ||
|
|
|
|
!C->isSameOperationAs(Instructions.back()) ||
|
2014-03-09 11:16:01 +08:00
|
|
|
C->use_empty())
|
2013-11-17 07:59:05 +08:00
|
|
|
return;
|
|
|
|
|
|
|
|
// C is now the (potential) last instruction in the reduction chain.
|
2015-01-30 05:52:03 +08:00
|
|
|
for (User *U : C->users()) {
|
2013-11-17 07:59:05 +08:00
|
|
|
// The only in-loop user can be the initial PHI.
|
2014-03-09 11:16:01 +08:00
|
|
|
if (L->contains(cast<Instruction>(U)))
|
|
|
|
if (cast<Instruction>(U) != Instructions.front())
|
2013-11-17 07:59:05 +08:00
|
|
|
return;
|
2015-01-30 05:52:03 +08:00
|
|
|
}
|
2013-11-17 07:59:05 +08:00
|
|
|
|
|
|
|
Instructions.push_back(C);
|
|
|
|
Valid = true;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Collect the vector of possible reduction variables.
|
|
|
|
void LoopReroll::collectPossibleReductions(Loop *L,
|
|
|
|
ReductionTracker &Reductions) {
|
|
|
|
BasicBlock *Header = L->getHeader();
|
|
|
|
for (BasicBlock::iterator I = Header->begin(),
|
|
|
|
IE = Header->getFirstInsertionPt(); I != IE; ++I) {
|
|
|
|
if (!isa<PHINode>(I))
|
|
|
|
continue;
|
|
|
|
if (!I->getType()->isSingleValueType())
|
|
|
|
continue;
|
|
|
|
|
2015-10-14 03:26:58 +08:00
|
|
|
SimpleLoopReduction SLR(&*I, L);
|
2013-11-17 07:59:05 +08:00
|
|
|
if (!SLR.valid())
|
|
|
|
continue;
|
|
|
|
|
|
|
|
DEBUG(dbgs() << "LRR: Possible reduction: " << *I << " (with " <<
|
|
|
|
SLR.size() << " chained instructions)\n");
|
|
|
|
Reductions.addSLR(SLR);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Collect the set of all users of the provided root instruction. This set of
|
|
|
|
// users contains not only the direct users of the root instruction, but also
|
|
|
|
// all users of those users, and so on. There are two exceptions:
|
|
|
|
//
|
|
|
|
// 1. Instructions in the set of excluded instructions are never added to the
|
|
|
|
// use set (even if they are users). This is used, for example, to exclude
|
|
|
|
// including root increments in the use set of the primary IV.
|
|
|
|
//
|
|
|
|
// 2. Instructions in the set of final instructions are added to the use set
|
|
|
|
// if they are users, but their users are not added. This is used, for
|
|
|
|
// example, to prevent a reduction update from forcing all later reduction
|
|
|
|
// updates into the use set.
|
2015-01-29 21:48:05 +08:00
|
|
|
void LoopReroll::DAGRootTracker::collectInLoopUserSet(
|
2013-11-17 07:59:05 +08:00
|
|
|
Instruction *Root, const SmallInstructionSet &Exclude,
|
|
|
|
const SmallInstructionSet &Final,
|
|
|
|
DenseSet<Instruction *> &Users) {
|
|
|
|
SmallInstructionVector Queue(1, Root);
|
|
|
|
while (!Queue.empty()) {
|
|
|
|
Instruction *I = Queue.pop_back_val();
|
|
|
|
if (!Users.insert(I).second)
|
|
|
|
continue;
|
|
|
|
|
|
|
|
if (!Final.count(I))
|
2014-03-09 11:16:01 +08:00
|
|
|
for (Use &U : I->uses()) {
|
|
|
|
Instruction *User = cast<Instruction>(U.getUser());
|
2013-11-17 07:59:05 +08:00
|
|
|
if (PHINode *PN = dyn_cast<PHINode>(User)) {
|
|
|
|
// Ignore "wrap-around" uses to PHIs of this loop's header.
|
2014-03-09 11:16:01 +08:00
|
|
|
if (PN->getIncomingBlock(U) == L->getHeader())
|
2013-11-17 07:59:05 +08:00
|
|
|
continue;
|
|
|
|
}
|
2014-10-28 19:53:30 +08:00
|
|
|
|
2013-11-17 07:59:05 +08:00
|
|
|
if (L->contains(User) && !Exclude.count(User)) {
|
|
|
|
Queue.push_back(User);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// We also want to collect single-user "feeder" values.
|
|
|
|
for (User::op_iterator OI = I->op_begin(),
|
|
|
|
OIE = I->op_end(); OI != OIE; ++OI) {
|
|
|
|
if (Instruction *Op = dyn_cast<Instruction>(*OI))
|
|
|
|
if (Op->hasOneUse() && L->contains(Op) && !Exclude.count(Op) &&
|
|
|
|
!Final.count(Op))
|
|
|
|
Queue.push_back(Op);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Collect all of the users of all of the provided root instructions (combined
|
|
|
|
// into a single set).
|
2015-01-29 21:48:05 +08:00
|
|
|
void LoopReroll::DAGRootTracker::collectInLoopUserSet(
|
2013-11-17 07:59:05 +08:00
|
|
|
const SmallInstructionVector &Roots,
|
|
|
|
const SmallInstructionSet &Exclude,
|
|
|
|
const SmallInstructionSet &Final,
|
|
|
|
DenseSet<Instruction *> &Users) {
|
|
|
|
for (SmallInstructionVector::const_iterator I = Roots.begin(),
|
|
|
|
IE = Roots.end(); I != IE; ++I)
|
2015-01-29 21:48:05 +08:00
|
|
|
collectInLoopUserSet(*I, Exclude, Final, Users);
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
static bool isSimpleLoadStore(Instruction *I) {
|
|
|
|
if (LoadInst *LI = dyn_cast<LoadInst>(I))
|
|
|
|
return LI->isSimple();
|
|
|
|
if (StoreInst *SI = dyn_cast<StoreInst>(I))
|
|
|
|
return SI->isSimple();
|
|
|
|
if (MemIntrinsic *MI = dyn_cast<MemIntrinsic>(I))
|
|
|
|
return !MI->isVolatile();
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
/// Return true if IVU is a "simple" arithmetic operation.
|
|
|
|
/// This is used for narrowing the search space for DAGRoots; only arithmetic
|
|
|
|
/// and GEPs can be part of a DAGRoot.
|
|
|
|
static bool isSimpleArithmeticOp(User *IVU) {
|
|
|
|
if (Instruction *I = dyn_cast<Instruction>(IVU)) {
|
|
|
|
switch (I->getOpcode()) {
|
|
|
|
default: return false;
|
|
|
|
case Instruction::Add:
|
|
|
|
case Instruction::Sub:
|
|
|
|
case Instruction::Mul:
|
|
|
|
case Instruction::Shl:
|
|
|
|
case Instruction::AShr:
|
|
|
|
case Instruction::LShr:
|
|
|
|
case Instruction::GetElementPtr:
|
|
|
|
case Instruction::Trunc:
|
|
|
|
case Instruction::ZExt:
|
|
|
|
case Instruction::SExt:
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
return false;
|
|
|
|
}
|
2015-01-29 21:48:05 +08:00
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
static bool isLoopIncrement(User *U, Instruction *IV) {
|
|
|
|
BinaryOperator *BO = dyn_cast<BinaryOperator>(U);
|
2016-01-26 03:36:30 +08:00
|
|
|
if (!BO || BO->getOpcode() != Instruction::Add)
|
2015-01-29 21:48:05 +08:00
|
|
|
return false;
|
|
|
|
|
2016-01-26 03:36:30 +08:00
|
|
|
for (auto *UU : BO->users()) {
|
2015-02-11 17:19:47 +08:00
|
|
|
PHINode *PN = dyn_cast<PHINode>(UU);
|
|
|
|
if (PN && PN == IV)
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
return false;
|
|
|
|
}
|
2015-01-29 21:48:05 +08:00
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
bool LoopReroll::DAGRootTracker::
|
|
|
|
collectPossibleRoots(Instruction *Base, std::map<int64_t,Instruction*> &Roots) {
|
|
|
|
SmallInstructionVector BaseUsers;
|
|
|
|
|
|
|
|
for (auto *I : Base->users()) {
|
|
|
|
ConstantInt *CI = nullptr;
|
|
|
|
|
|
|
|
if (isLoopIncrement(I, IV)) {
|
|
|
|
LoopIncs.push_back(cast<Instruction>(I));
|
|
|
|
continue;
|
|
|
|
}
|
|
|
|
|
|
|
|
// The root nodes must be either GEPs, ORs or ADDs.
|
|
|
|
if (auto *BO = dyn_cast<BinaryOperator>(I)) {
|
|
|
|
if (BO->getOpcode() == Instruction::Add ||
|
|
|
|
BO->getOpcode() == Instruction::Or)
|
|
|
|
CI = dyn_cast<ConstantInt>(BO->getOperand(1));
|
|
|
|
} else if (auto *GEP = dyn_cast<GetElementPtrInst>(I)) {
|
|
|
|
Value *LastOperand = GEP->getOperand(GEP->getNumOperands()-1);
|
|
|
|
CI = dyn_cast<ConstantInt>(LastOperand);
|
|
|
|
}
|
|
|
|
|
|
|
|
if (!CI) {
|
|
|
|
if (Instruction *II = dyn_cast<Instruction>(I)) {
|
|
|
|
BaseUsers.push_back(II);
|
|
|
|
continue;
|
|
|
|
} else {
|
|
|
|
DEBUG(dbgs() << "LRR: Aborting due to non-instruction: " << *I << "\n");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2015-07-25 06:01:49 +08:00
|
|
|
int64_t V = std::abs(CI->getValue().getSExtValue());
|
2015-02-11 17:19:47 +08:00
|
|
|
if (Roots.find(V) != Roots.end())
|
|
|
|
// No duplicates, please.
|
|
|
|
return false;
|
|
|
|
|
|
|
|
Roots[V] = cast<Instruction>(I);
|
|
|
|
}
|
|
|
|
|
|
|
|
if (Roots.empty())
|
2015-01-30 05:52:03 +08:00
|
|
|
return false;
|
2015-02-11 17:19:47 +08:00
|
|
|
|
|
|
|
// If we found non-loop-inc, non-root users of Base, assume they are
|
|
|
|
// for the zeroth root index. This is because "add %a, 0" gets optimized
|
|
|
|
// away.
|
2015-02-17 01:02:00 +08:00
|
|
|
if (BaseUsers.size()) {
|
|
|
|
if (Roots.find(0) != Roots.end()) {
|
|
|
|
DEBUG(dbgs() << "LRR: Multiple roots found for base - aborting!\n");
|
|
|
|
return false;
|
|
|
|
}
|
2015-02-11 17:19:47 +08:00
|
|
|
Roots[0] = Base;
|
2015-02-17 01:02:00 +08:00
|
|
|
}
|
2015-02-11 17:19:47 +08:00
|
|
|
|
|
|
|
// Calculate the number of users of the base, or lowest indexed, iteration.
|
|
|
|
unsigned NumBaseUses = BaseUsers.size();
|
|
|
|
if (NumBaseUses == 0)
|
|
|
|
NumBaseUses = Roots.begin()->second->getNumUses();
|
2015-07-25 06:01:49 +08:00
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
// Check that every node has the same number of users.
|
|
|
|
for (auto &KV : Roots) {
|
|
|
|
if (KV.first == 0)
|
|
|
|
continue;
|
|
|
|
if (KV.second->getNumUses() != NumBaseUses) {
|
|
|
|
DEBUG(dbgs() << "LRR: Aborting - Root and Base #users not the same: "
|
|
|
|
<< "#Base=" << NumBaseUses << ", #Root=" <<
|
|
|
|
KV.second->getNumUses() << "\n");
|
|
|
|
return false;
|
|
|
|
}
|
2015-01-30 05:52:03 +08:00
|
|
|
}
|
|
|
|
|
2015-07-25 06:01:49 +08:00
|
|
|
return true;
|
2015-01-29 21:48:05 +08:00
|
|
|
}
|
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
bool LoopReroll::DAGRootTracker::
|
|
|
|
findRootsRecursive(Instruction *I, SmallInstructionSet SubsumedInsts) {
|
|
|
|
// Does the user look like it could be part of a root set?
|
|
|
|
// All its users must be simple arithmetic ops.
|
|
|
|
if (I->getNumUses() > IL_MaxRerollIterations)
|
2013-11-17 07:59:05 +08:00
|
|
|
return false;
|
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
if ((I->getOpcode() == Instruction::Mul ||
|
|
|
|
I->getOpcode() == Instruction::PHI) &&
|
|
|
|
I != IV &&
|
|
|
|
findRootsBase(I, SubsumedInsts))
|
|
|
|
return true;
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
SubsumedInsts.insert(I);
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
for (User *V : I->users()) {
|
|
|
|
Instruction *I = dyn_cast<Instruction>(V);
|
|
|
|
if (std::find(LoopIncs.begin(), LoopIncs.end(), I) != LoopIncs.end())
|
|
|
|
continue;
|
|
|
|
|
|
|
|
if (!I || !isSimpleArithmeticOp(I) ||
|
|
|
|
!findRootsRecursive(I, SubsumedInsts))
|
2013-11-17 07:59:05 +08:00
|
|
|
return false;
|
2015-02-11 17:19:47 +08:00
|
|
|
}
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
bool LoopReroll::DAGRootTracker::
|
|
|
|
findRootsBase(Instruction *IVU, SmallInstructionSet SubsumedInsts) {
|
|
|
|
|
|
|
|
// The base instruction needs to be a multiply so
|
|
|
|
// that we can erase it.
|
|
|
|
if (IVU->getOpcode() != Instruction::Mul &&
|
|
|
|
IVU->getOpcode() != Instruction::PHI)
|
2013-11-17 07:59:05 +08:00
|
|
|
return false;
|
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
std::map<int64_t, Instruction*> V;
|
|
|
|
if (!collectPossibleRoots(IVU, V))
|
|
|
|
return false;
|
2015-01-29 21:48:05 +08:00
|
|
|
|
2015-07-25 06:01:49 +08:00
|
|
|
// If we didn't get a root for index zero, then IVU must be
|
2015-02-11 17:19:47 +08:00
|
|
|
// subsumed.
|
|
|
|
if (V.find(0) == V.end())
|
|
|
|
SubsumedInsts.insert(IVU);
|
|
|
|
|
|
|
|
// Partition the vector into monotonically increasing indexes.
|
|
|
|
DAGRootSet DRS;
|
|
|
|
DRS.BaseInst = nullptr;
|
|
|
|
|
|
|
|
for (auto &KV : V) {
|
|
|
|
if (!DRS.BaseInst) {
|
|
|
|
DRS.BaseInst = KV.second;
|
|
|
|
DRS.SubsumedInsts = SubsumedInsts;
|
|
|
|
} else if (DRS.Roots.empty()) {
|
|
|
|
DRS.Roots.push_back(KV.second);
|
|
|
|
} else if (V.find(KV.first - 1) != V.end()) {
|
|
|
|
DRS.Roots.push_back(KV.second);
|
|
|
|
} else {
|
|
|
|
// Linear sequence terminated.
|
|
|
|
RootSets.push_back(DRS);
|
|
|
|
DRS.BaseInst = KV.second;
|
|
|
|
DRS.SubsumedInsts = SubsumedInsts;
|
|
|
|
DRS.Roots.clear();
|
|
|
|
}
|
|
|
|
}
|
|
|
|
RootSets.push_back(DRS);
|
2015-01-29 21:48:05 +08:00
|
|
|
|
2013-11-17 07:59:05 +08:00
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
bool LoopReroll::DAGRootTracker::findRoots() {
|
2015-07-25 06:01:49 +08:00
|
|
|
Inc = IVToIncMap[IV];
|
2015-02-11 17:19:47 +08:00
|
|
|
|
|
|
|
assert(RootSets.empty() && "Unclean state!");
|
2015-07-25 06:01:49 +08:00
|
|
|
if (std::abs(Inc) == 1) {
|
2015-02-11 17:19:47 +08:00
|
|
|
for (auto *IVU : IV->users()) {
|
|
|
|
if (isLoopIncrement(IVU, IV))
|
|
|
|
LoopIncs.push_back(cast<Instruction>(IVU));
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
2015-02-11 17:19:47 +08:00
|
|
|
if (!findRootsRecursive(IV, SmallInstructionSet()))
|
|
|
|
return false;
|
|
|
|
LoopIncs.push_back(IV);
|
|
|
|
} else {
|
|
|
|
if (!findRootsBase(IV, SmallInstructionSet()))
|
|
|
|
return false;
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
// Ensure all sets have the same size.
|
|
|
|
if (RootSets.empty()) {
|
|
|
|
DEBUG(dbgs() << "LRR: Aborting because no root sets found!\n");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
for (auto &V : RootSets) {
|
|
|
|
if (V.Roots.empty() || V.Roots.size() != RootSets[0].Roots.size()) {
|
|
|
|
DEBUG(dbgs()
|
|
|
|
<< "LRR: Aborting because not all root sets have the same size\n");
|
2015-01-29 21:48:05 +08:00
|
|
|
return false;
|
2015-02-11 17:19:47 +08:00
|
|
|
}
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
// And ensure all loop iterations are consecutive. We rely on std::map
|
|
|
|
// providing ordered traversal.
|
|
|
|
for (auto &V : RootSets) {
|
|
|
|
const auto *ADR = dyn_cast<SCEVAddRecExpr>(SE->getSCEV(V.BaseInst));
|
|
|
|
if (!ADR)
|
|
|
|
return false;
|
|
|
|
|
|
|
|
// Consider a DAGRootSet with N-1 roots (so N different values including
|
|
|
|
// BaseInst).
|
|
|
|
// Define d = Roots[0] - BaseInst, which should be the same as
|
|
|
|
// Roots[I] - Roots[I-1] for all I in [1..N).
|
|
|
|
// Define D = BaseInst@J - BaseInst@J-1, where "@J" means the value at the
|
|
|
|
// loop iteration J.
|
|
|
|
//
|
|
|
|
// Now, For the loop iterations to be consecutive:
|
|
|
|
// D = d * N
|
|
|
|
|
|
|
|
unsigned N = V.Roots.size() + 1;
|
|
|
|
const SCEV *StepSCEV = SE->getMinusSCEV(SE->getSCEV(V.Roots[0]), ADR);
|
|
|
|
const SCEV *ScaleSCEV = SE->getConstant(StepSCEV->getType(), N);
|
|
|
|
if (ADR->getStepRecurrence(*SE) != SE->getMulExpr(StepSCEV, ScaleSCEV)) {
|
|
|
|
DEBUG(dbgs() << "LRR: Aborting because iterations are not consecutive\n");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
Scale = RootSets[0].Roots.size() + 1;
|
|
|
|
|
|
|
|
if (Scale > IL_MaxRerollIterations) {
|
|
|
|
DEBUG(dbgs() << "LRR: Aborting - too many iterations found. "
|
|
|
|
<< "#Found=" << Scale << ", #Max=" << IL_MaxRerollIterations
|
|
|
|
<< "\n");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
DEBUG(dbgs() << "LRR: Successfully found roots: Scale=" << Scale << "\n");
|
|
|
|
|
2013-11-17 07:59:05 +08:00
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
bool LoopReroll::DAGRootTracker::collectUsedInstructions(SmallInstructionSet &PossibleRedSet) {
|
|
|
|
// Populate the MapVector with all instructions in the block, in order first,
|
|
|
|
// so we can iterate over the contents later in perfect order.
|
|
|
|
for (auto &I : *L->getHeader()) {
|
|
|
|
Uses[&I].resize(IL_End);
|
|
|
|
}
|
|
|
|
|
|
|
|
SmallInstructionSet Exclude;
|
2015-02-11 17:19:47 +08:00
|
|
|
for (auto &DRS : RootSets) {
|
|
|
|
Exclude.insert(DRS.Roots.begin(), DRS.Roots.end());
|
|
|
|
Exclude.insert(DRS.SubsumedInsts.begin(), DRS.SubsumedInsts.end());
|
|
|
|
Exclude.insert(DRS.BaseInst);
|
|
|
|
}
|
2015-01-30 05:52:03 +08:00
|
|
|
Exclude.insert(LoopIncs.begin(), LoopIncs.end());
|
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
for (auto &DRS : RootSets) {
|
|
|
|
DenseSet<Instruction*> VBase;
|
|
|
|
collectInLoopUserSet(DRS.BaseInst, Exclude, PossibleRedSet, VBase);
|
|
|
|
for (auto *I : VBase) {
|
|
|
|
Uses[I].set(0);
|
|
|
|
}
|
2015-01-30 05:52:03 +08:00
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
unsigned Idx = 1;
|
|
|
|
for (auto *Root : DRS.Roots) {
|
|
|
|
DenseSet<Instruction*> V;
|
|
|
|
collectInLoopUserSet(Root, Exclude, PossibleRedSet, V);
|
2015-01-30 05:52:03 +08:00
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
// While we're here, check the use sets are the same size.
|
|
|
|
if (V.size() != VBase.size()) {
|
|
|
|
DEBUG(dbgs() << "LRR: Aborting - use sets are different sizes\n");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
for (auto *I : V) {
|
|
|
|
Uses[I].set(Idx);
|
|
|
|
}
|
|
|
|
++Idx;
|
2015-01-30 05:52:03 +08:00
|
|
|
}
|
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
// Make sure our subsumed instructions are remembered too.
|
|
|
|
for (auto *I : DRS.SubsumedInsts) {
|
|
|
|
Uses[I].set(IL_All);
|
2015-01-30 05:52:03 +08:00
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Make sure the loop increments are also accounted for.
|
2015-02-11 17:19:47 +08:00
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
Exclude.clear();
|
2015-02-11 17:19:47 +08:00
|
|
|
for (auto &DRS : RootSets) {
|
|
|
|
Exclude.insert(DRS.Roots.begin(), DRS.Roots.end());
|
|
|
|
Exclude.insert(DRS.SubsumedInsts.begin(), DRS.SubsumedInsts.end());
|
|
|
|
Exclude.insert(DRS.BaseInst);
|
|
|
|
}
|
2015-01-30 05:52:03 +08:00
|
|
|
|
|
|
|
DenseSet<Instruction*> V;
|
|
|
|
collectInLoopUserSet(LoopIncs, Exclude, PossibleRedSet, V);
|
|
|
|
for (auto *I : V) {
|
2015-02-11 17:19:47 +08:00
|
|
|
Uses[I].set(IL_All);
|
2015-01-30 05:52:03 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
return true;
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
}
|
|
|
|
|
2015-02-12 23:54:14 +08:00
|
|
|
/// Get the next instruction in "In" that is a member of set Val.
|
|
|
|
/// Start searching from StartI, and do not return anything in Exclude.
|
|
|
|
/// If StartI is not given, start from In.begin().
|
2015-01-30 05:52:03 +08:00
|
|
|
LoopReroll::DAGRootTracker::UsesTy::iterator
|
|
|
|
LoopReroll::DAGRootTracker::nextInstr(int Val, UsesTy &In,
|
2015-02-12 23:54:14 +08:00
|
|
|
const SmallInstructionSet &Exclude,
|
|
|
|
UsesTy::iterator *StartI) {
|
|
|
|
UsesTy::iterator I = StartI ? *StartI : In.begin();
|
|
|
|
while (I != In.end() && (I->second.test(Val) == 0 ||
|
|
|
|
Exclude.count(I->first) != 0))
|
2015-01-30 05:52:03 +08:00
|
|
|
++I;
|
|
|
|
return I;
|
|
|
|
}
|
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
bool LoopReroll::DAGRootTracker::isBaseInst(Instruction *I) {
|
|
|
|
for (auto &DRS : RootSets) {
|
|
|
|
if (DRS.BaseInst == I)
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
bool LoopReroll::DAGRootTracker::isRootInst(Instruction *I) {
|
|
|
|
for (auto &DRS : RootSets) {
|
|
|
|
if (std::find(DRS.Roots.begin(), DRS.Roots.end(), I) != DRS.Roots.end())
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
2015-02-12 23:54:14 +08:00
|
|
|
/// Return true if instruction I depends on any instruction between
|
|
|
|
/// Start and End.
|
|
|
|
bool LoopReroll::DAGRootTracker::instrDependsOn(Instruction *I,
|
|
|
|
UsesTy::iterator Start,
|
|
|
|
UsesTy::iterator End) {
|
|
|
|
for (auto *U : I->users()) {
|
|
|
|
for (auto It = Start; It != End; ++It)
|
|
|
|
if (U == It->first)
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
2015-09-29 01:03:23 +08:00
|
|
|
static bool isIgnorableInst(const Instruction *I) {
|
|
|
|
if (isa<DbgInfoIntrinsic>(I))
|
|
|
|
return true;
|
|
|
|
const IntrinsicInst* II = dyn_cast<IntrinsicInst>(I);
|
|
|
|
if (!II)
|
|
|
|
return false;
|
|
|
|
switch (II->getIntrinsicID()) {
|
|
|
|
default:
|
|
|
|
return false;
|
|
|
|
case llvm::Intrinsic::annotation:
|
|
|
|
case Intrinsic::ptr_annotation:
|
|
|
|
case Intrinsic::var_annotation:
|
|
|
|
// TODO: the following intrinsics may also be whitelisted:
|
|
|
|
// lifetime_start, lifetime_end, invariant_start, invariant_end
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
bool LoopReroll::DAGRootTracker::validate(ReductionTracker &Reductions) {
|
2013-11-17 07:59:05 +08:00
|
|
|
// We now need to check for equivalence of the use graph of each root with
|
|
|
|
// that of the primary induction variable (excluding the roots). Our goal
|
|
|
|
// here is not to solve the full graph isomorphism problem, but rather to
|
|
|
|
// catch common cases without a lot of work. As a result, we will assume
|
|
|
|
// that the relative order of the instructions in each unrolled iteration
|
|
|
|
// is the same (although we will not make an assumption about how the
|
|
|
|
// different iterations are intermixed). Note that while the order must be
|
|
|
|
// the same, the instructions may not be in the same basic block.
|
|
|
|
|
2015-01-29 21:48:05 +08:00
|
|
|
// An array of just the possible reductions for this scale factor. When we
|
|
|
|
// collect the set of all users of some root instructions, these reduction
|
|
|
|
// instructions are treated as 'final' (their uses are not considered).
|
|
|
|
// This is important because we don't want the root use set to search down
|
|
|
|
// the reduction chain.
|
|
|
|
SmallInstructionSet PossibleRedSet;
|
|
|
|
SmallInstructionSet PossibleRedLastSet;
|
|
|
|
SmallInstructionSet PossibleRedPHISet;
|
|
|
|
Reductions.restrictToScale(Scale, PossibleRedSet,
|
|
|
|
PossibleRedPHISet, PossibleRedLastSet);
|
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
// Populate "Uses" with where each instruction is used.
|
|
|
|
if (!collectUsedInstructions(PossibleRedSet))
|
|
|
|
return false;
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
// Make sure we mark the reduction PHIs as used in all iterations.
|
|
|
|
for (auto *I : PossibleRedPHISet) {
|
2015-02-11 17:19:47 +08:00
|
|
|
Uses[I].set(IL_All);
|
2015-01-30 05:52:03 +08:00
|
|
|
}
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
// Make sure all instructions in the loop are in one and only one
|
|
|
|
// set.
|
|
|
|
for (auto &KV : Uses) {
|
2015-09-29 01:03:23 +08:00
|
|
|
if (KV.second.count() != 1 && !isIgnorableInst(KV.first)) {
|
2015-01-30 05:52:03 +08:00
|
|
|
DEBUG(dbgs() << "LRR: Aborting - instruction is not used in 1 iteration: "
|
|
|
|
<< *KV.first << " (#uses=" << KV.second.count() << ")\n");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
}
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
DEBUG(
|
|
|
|
for (auto &KV : Uses) {
|
|
|
|
dbgs() << "LRR: " << KV.second.find_first() << "\t" << *KV.first << "\n";
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
2015-01-30 05:52:03 +08:00
|
|
|
);
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
for (unsigned Iter = 1; Iter < Scale; ++Iter) {
|
2013-11-17 07:59:05 +08:00
|
|
|
// In addition to regular aliasing information, we need to look for
|
|
|
|
// instructions from later (future) iterations that have side effects
|
|
|
|
// preventing us from reordering them past other instructions with side
|
|
|
|
// effects.
|
|
|
|
bool FutureSideEffects = false;
|
|
|
|
AliasSetTracker AST(*AA);
|
|
|
|
// The map between instructions in f(%iv.(i+1)) and f(%iv).
|
|
|
|
DenseMap<Value *, Value *> BaseMap;
|
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
// Compare iteration Iter to the base.
|
2015-02-12 23:54:14 +08:00
|
|
|
SmallInstructionSet Visited;
|
|
|
|
auto BaseIt = nextInstr(0, Uses, Visited);
|
|
|
|
auto RootIt = nextInstr(Iter, Uses, Visited);
|
2015-01-30 05:52:03 +08:00
|
|
|
auto LastRootIt = Uses.begin();
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
while (BaseIt != Uses.end() && RootIt != Uses.end()) {
|
|
|
|
Instruction *BaseInst = BaseIt->first;
|
|
|
|
Instruction *RootInst = RootIt->first;
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
// Skip over the IV or root instructions; only match their users.
|
|
|
|
bool Continue = false;
|
2015-02-11 17:19:47 +08:00
|
|
|
if (isBaseInst(BaseInst)) {
|
2015-02-12 23:54:14 +08:00
|
|
|
Visited.insert(BaseInst);
|
|
|
|
BaseIt = nextInstr(0, Uses, Visited);
|
2015-01-30 05:52:03 +08:00
|
|
|
Continue = true;
|
|
|
|
}
|
2015-02-11 17:19:47 +08:00
|
|
|
if (isRootInst(RootInst)) {
|
2015-01-30 05:52:03 +08:00
|
|
|
LastRootIt = RootIt;
|
2015-02-12 23:54:14 +08:00
|
|
|
Visited.insert(RootInst);
|
|
|
|
RootIt = nextInstr(Iter, Uses, Visited);
|
2015-01-30 05:52:03 +08:00
|
|
|
Continue = true;
|
|
|
|
}
|
|
|
|
if (Continue) continue;
|
|
|
|
|
2015-02-12 23:54:14 +08:00
|
|
|
if (!BaseInst->isSameOperationAs(RootInst)) {
|
|
|
|
// Last chance saloon. We don't try and solve the full isomorphism
|
|
|
|
// problem, but try and at least catch the case where two instructions
|
|
|
|
// *of different types* are round the wrong way. We won't be able to
|
|
|
|
// efficiently tell, given two ADD instructions, which way around we
|
|
|
|
// should match them, but given an ADD and a SUB, we can at least infer
|
|
|
|
// which one is which.
|
|
|
|
//
|
|
|
|
// This should allow us to deal with a greater subset of the isomorphism
|
|
|
|
// problem. It does however change a linear algorithm into a quadratic
|
|
|
|
// one, so limit the number of probes we do.
|
|
|
|
auto TryIt = RootIt;
|
|
|
|
unsigned N = NumToleratedFailedMatches;
|
|
|
|
while (TryIt != Uses.end() &&
|
|
|
|
!BaseInst->isSameOperationAs(TryIt->first) &&
|
|
|
|
N--) {
|
|
|
|
++TryIt;
|
|
|
|
TryIt = nextInstr(Iter, Uses, Visited, &TryIt);
|
|
|
|
}
|
|
|
|
|
|
|
|
if (TryIt == Uses.end() || TryIt == RootIt ||
|
|
|
|
instrDependsOn(TryIt->first, RootIt, TryIt)) {
|
|
|
|
DEBUG(dbgs() << "LRR: iteration root match failed at " << *BaseInst <<
|
|
|
|
" vs. " << *RootInst << "\n");
|
|
|
|
return false;
|
|
|
|
}
|
2015-07-25 06:01:49 +08:00
|
|
|
|
2015-02-12 23:54:14 +08:00
|
|
|
RootIt = TryIt;
|
|
|
|
RootInst = TryIt->first;
|
|
|
|
}
|
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
// All instructions between the last root and this root
|
2015-07-25 06:01:49 +08:00
|
|
|
// may belong to some other iteration. If they belong to a
|
2015-01-30 05:52:03 +08:00
|
|
|
// future iteration, then they're dangerous to alias with.
|
2015-07-25 06:01:49 +08:00
|
|
|
//
|
2015-02-12 23:54:14 +08:00
|
|
|
// Note that because we allow a limited amount of flexibility in the order
|
|
|
|
// that we visit nodes, LastRootIt might be *before* RootIt, in which
|
|
|
|
// case we've already checked this set of instructions so we shouldn't
|
|
|
|
// do anything.
|
|
|
|
for (; LastRootIt < RootIt; ++LastRootIt) {
|
2015-01-30 05:52:03 +08:00
|
|
|
Instruction *I = LastRootIt->first;
|
|
|
|
if (LastRootIt->second.find_first() < (int)Iter)
|
|
|
|
continue;
|
|
|
|
if (I->mayWriteToMemory())
|
|
|
|
AST.add(I);
|
|
|
|
// Note: This is specifically guarded by a check on isa<PHINode>,
|
|
|
|
// which while a valid (somewhat arbitrary) micro-optimization, is
|
|
|
|
// needed because otherwise isSafeToSpeculativelyExecute returns
|
|
|
|
// false on PHI nodes.
|
|
|
|
if (!isa<PHINode>(I) && !isSimpleLoadStore(I) &&
|
2015-03-10 10:37:25 +08:00
|
|
|
!isSafeToSpeculativelyExecute(I))
|
2015-01-30 05:52:03 +08:00
|
|
|
// Intervening instructions cause side effects.
|
|
|
|
FutureSideEffects = true;
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
// Make sure that this instruction, which is in the use set of this
|
|
|
|
// root instruction, does not also belong to the base set or the set of
|
2015-01-30 05:52:03 +08:00
|
|
|
// some other root instruction.
|
|
|
|
if (RootIt->second.count() > 1) {
|
|
|
|
DEBUG(dbgs() << "LRR: iteration root match failed at " << *BaseInst <<
|
|
|
|
" vs. " << *RootInst << " (prev. case overlap)\n");
|
|
|
|
return false;
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
// Make sure that we don't alias with any instruction in the alias set
|
|
|
|
// tracker. If we do, then we depend on a future iteration, and we
|
|
|
|
// can't reroll.
|
2015-01-30 05:52:03 +08:00
|
|
|
if (RootInst->mayReadFromMemory())
|
|
|
|
for (auto &K : AST) {
|
|
|
|
if (K.aliasesUnknownInst(RootInst, *AA)) {
|
|
|
|
DEBUG(dbgs() << "LRR: iteration root match failed at " << *BaseInst <<
|
|
|
|
" vs. " << *RootInst << " (depends on future store)\n");
|
|
|
|
return false;
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// If we've past an instruction from a future iteration that may have
|
|
|
|
// side effects, and this instruction might also, then we can't reorder
|
|
|
|
// them, and this matching fails. As an exception, we allow the alias
|
|
|
|
// set tracker to handle regular (simple) load/store dependencies.
|
2015-03-10 10:37:25 +08:00
|
|
|
if (FutureSideEffects && ((!isSimpleLoadStore(BaseInst) &&
|
|
|
|
!isSafeToSpeculativelyExecute(BaseInst)) ||
|
|
|
|
(!isSimpleLoadStore(RootInst) &&
|
|
|
|
!isSafeToSpeculativelyExecute(RootInst)))) {
|
2015-01-30 05:52:03 +08:00
|
|
|
DEBUG(dbgs() << "LRR: iteration root match failed at " << *BaseInst <<
|
|
|
|
" vs. " << *RootInst <<
|
2013-11-17 07:59:05 +08:00
|
|
|
" (side effects prevent reordering)\n");
|
2015-01-30 05:52:03 +08:00
|
|
|
return false;
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
// For instructions that are part of a reduction, if the operation is
|
|
|
|
// associative, then don't bother matching the operands (because we
|
|
|
|
// already know that the instructions are isomorphic, and the order
|
|
|
|
// within the iteration does not matter). For non-associative reductions,
|
|
|
|
// we do need to match the operands, because we need to reject
|
|
|
|
// out-of-order instructions within an iteration!
|
|
|
|
// For example (assume floating-point addition), we need to reject this:
|
|
|
|
// x += a[i]; x += b[i];
|
|
|
|
// x += a[i+1]; x += b[i+1];
|
|
|
|
// x += b[i+2]; x += a[i+2];
|
2015-01-30 05:52:03 +08:00
|
|
|
bool InReduction = Reductions.isPairInSame(BaseInst, RootInst);
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
if (!(InReduction && BaseInst->isAssociative())) {
|
2014-04-20 07:56:35 +08:00
|
|
|
bool Swapped = false, SomeOpMatched = false;
|
2015-01-30 05:52:03 +08:00
|
|
|
for (unsigned j = 0; j < BaseInst->getNumOperands(); ++j) {
|
|
|
|
Value *Op2 = RootInst->getOperand(j);
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2014-10-28 19:53:30 +08:00
|
|
|
// If this is part of a reduction (and the operation is not
|
|
|
|
// associatve), then we match all operands, but not those that are
|
|
|
|
// part of the reduction.
|
2013-11-17 07:59:05 +08:00
|
|
|
if (InReduction)
|
|
|
|
if (Instruction *Op2I = dyn_cast<Instruction>(Op2))
|
2015-01-30 05:52:03 +08:00
|
|
|
if (Reductions.isPairInSame(RootInst, Op2I))
|
2013-11-17 07:59:05 +08:00
|
|
|
continue;
|
|
|
|
|
|
|
|
DenseMap<Value *, Value *>::iterator BMI = BaseMap.find(Op2);
|
2015-02-11 17:19:47 +08:00
|
|
|
if (BMI != BaseMap.end()) {
|
2013-11-17 07:59:05 +08:00
|
|
|
Op2 = BMI->second;
|
2015-02-11 17:19:47 +08:00
|
|
|
} else {
|
|
|
|
for (auto &DRS : RootSets) {
|
|
|
|
if (DRS.Roots[Iter-1] == (Instruction*) Op2) {
|
|
|
|
Op2 = DRS.BaseInst;
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
if (BaseInst->getOperand(Swapped ? unsigned(!j) : j) != Op2) {
|
2014-10-28 19:53:30 +08:00
|
|
|
// If we've not already decided to swap the matched operands, and
|
|
|
|
// we've not already matched our first operand (note that we could
|
|
|
|
// have skipped matching the first operand because it is part of a
|
|
|
|
// reduction above), and the instruction is commutative, then try
|
|
|
|
// the swapped match.
|
2015-01-30 05:52:03 +08:00
|
|
|
if (!Swapped && BaseInst->isCommutative() && !SomeOpMatched &&
|
|
|
|
BaseInst->getOperand(!j) == Op2) {
|
2013-11-17 07:59:05 +08:00
|
|
|
Swapped = true;
|
|
|
|
} else {
|
2015-01-30 05:52:03 +08:00
|
|
|
DEBUG(dbgs() << "LRR: iteration root match failed at " << *BaseInst
|
|
|
|
<< " vs. " << *RootInst << " (operand " << j << ")\n");
|
|
|
|
return false;
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
SomeOpMatched = true;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
if ((!PossibleRedLastSet.count(BaseInst) &&
|
|
|
|
hasUsesOutsideLoop(BaseInst, L)) ||
|
|
|
|
(!PossibleRedLastSet.count(RootInst) &&
|
|
|
|
hasUsesOutsideLoop(RootInst, L))) {
|
|
|
|
DEBUG(dbgs() << "LRR: iteration root match failed at " << *BaseInst <<
|
|
|
|
" vs. " << *RootInst << " (uses outside loop)\n");
|
|
|
|
return false;
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
Reductions.recordPair(BaseInst, RootInst, Iter);
|
|
|
|
BaseMap.insert(std::make_pair(RootInst, BaseInst));
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-01-30 05:52:03 +08:00
|
|
|
LastRootIt = RootIt;
|
2015-02-12 23:54:14 +08:00
|
|
|
Visited.insert(BaseInst);
|
|
|
|
Visited.insert(RootInst);
|
|
|
|
BaseIt = nextInstr(0, Uses, Visited);
|
|
|
|
RootIt = nextInstr(Iter, Uses, Visited);
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
2015-01-30 05:52:03 +08:00
|
|
|
assert (BaseIt == Uses.end() && RootIt == Uses.end() &&
|
|
|
|
"Mismatched set sizes!");
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
DEBUG(dbgs() << "LRR: Matched all iteration increments for " <<
|
2015-02-11 17:19:47 +08:00
|
|
|
*IV << "\n");
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-01-29 21:48:05 +08:00
|
|
|
return true;
|
|
|
|
}
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-01-29 21:48:05 +08:00
|
|
|
void LoopReroll::DAGRootTracker::replace(const SCEV *IterCount) {
|
|
|
|
BasicBlock *Header = L->getHeader();
|
2013-11-17 07:59:05 +08:00
|
|
|
// Remove instructions associated with non-base iterations.
|
|
|
|
for (BasicBlock::reverse_iterator J = Header->rbegin();
|
|
|
|
J != Header->rend();) {
|
2015-01-30 05:52:03 +08:00
|
|
|
unsigned I = Uses[&*J].find_first();
|
2015-02-11 17:19:47 +08:00
|
|
|
if (I > 0 && I < IL_All) {
|
2013-11-17 07:59:05 +08:00
|
|
|
Instruction *D = &*J;
|
|
|
|
DEBUG(dbgs() << "LRR: removing: " << *D << "\n");
|
|
|
|
D->eraseFromParent();
|
|
|
|
continue;
|
|
|
|
}
|
|
|
|
|
2014-10-28 19:53:30 +08:00
|
|
|
++J;
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
2016-01-26 03:36:30 +08:00
|
|
|
bool Negative = IVToIncMap[IV] < 0;
|
|
|
|
const DataLayout &DL = Header->getModule()->getDataLayout();
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2015-02-11 17:19:47 +08:00
|
|
|
// We need to create a new induction variable for each different BaseInst.
|
2016-01-26 03:36:30 +08:00
|
|
|
for (auto &DRS : RootSets) {
|
2015-02-11 17:19:47 +08:00
|
|
|
// Insert the new induction variable.
|
2016-01-26 03:36:30 +08:00
|
|
|
const SCEVAddRecExpr *RealIVSCEV =
|
|
|
|
cast<SCEVAddRecExpr>(SE->getSCEV(DRS.BaseInst));
|
|
|
|
const SCEV *Start = RealIVSCEV->getStart();
|
|
|
|
const SCEVAddRecExpr *H = cast<SCEVAddRecExpr>(SE->getAddRecExpr(
|
|
|
|
Start, SE->getConstant(RealIVSCEV->getType(), Negative ? -1 : 1), L,
|
|
|
|
SCEV::FlagAnyWrap));
|
|
|
|
{ // Limit the lifetime of SCEVExpander.
|
|
|
|
SCEVExpander Expander(*SE, DL, "reroll");
|
|
|
|
Value *NewIV = Expander.expandCodeFor(H, IV->getType(), &Header->front());
|
|
|
|
|
|
|
|
for (auto &KV : Uses) {
|
|
|
|
if (KV.second.find_first() == 0)
|
|
|
|
KV.first->replaceUsesOfWith(DRS.BaseInst, NewIV);
|
|
|
|
}
|
2015-02-11 17:19:47 +08:00
|
|
|
|
2016-01-26 03:36:30 +08:00
|
|
|
if (BranchInst *BI = dyn_cast<BranchInst>(Header->getTerminator())) {
|
|
|
|
// FIXME: Why do we need this check?
|
|
|
|
if (Uses[BI].find_first() == IL_All) {
|
|
|
|
const SCEV *ICSCEV = RealIVSCEV->evaluateAtIteration(IterCount, *SE);
|
2015-02-11 17:19:47 +08:00
|
|
|
|
2016-01-26 03:36:30 +08:00
|
|
|
// Iteration count SCEV minus 1
|
|
|
|
const SCEV *ICMinus1SCEV = SE->getMinusSCEV(
|
|
|
|
ICSCEV, SE->getConstant(ICSCEV->getType(), Negative ? -1 : 1));
|
2015-02-11 17:19:47 +08:00
|
|
|
|
2016-01-26 03:36:30 +08:00
|
|
|
Value *ICMinus1; // Iteration count minus 1
|
|
|
|
if (isa<SCEVConstant>(ICMinus1SCEV)) {
|
|
|
|
ICMinus1 = Expander.expandCodeFor(ICMinus1SCEV, NewIV->getType(), BI);
|
|
|
|
} else {
|
|
|
|
BasicBlock *Preheader = L->getLoopPreheader();
|
|
|
|
if (!Preheader)
|
|
|
|
Preheader = InsertPreheaderForLoop(L, DT, LI, PreserveLCSSA);
|
2014-10-28 19:53:30 +08:00
|
|
|
|
2016-01-26 03:36:30 +08:00
|
|
|
ICMinus1 = Expander.expandCodeFor(ICMinus1SCEV, NewIV->getType(),
|
|
|
|
Preheader->getTerminator());
|
|
|
|
}
|
|
|
|
|
|
|
|
Value *Cond =
|
|
|
|
new ICmpInst(BI, CmpInst::ICMP_EQ, NewIV, ICMinus1, "exitcond");
|
|
|
|
BI->setCondition(Cond);
|
2013-11-17 07:59:05 +08:00
|
|
|
|
2016-01-26 03:36:30 +08:00
|
|
|
if (BI->getSuccessor(1) != Header)
|
|
|
|
BI->swapSuccessors();
|
|
|
|
}
|
2013-11-17 07:59:05 +08:00
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
2016-01-26 03:36:30 +08:00
|
|
|
|
|
|
|
SimplifyInstructionsInBlock(Header, TLI);
|
|
|
|
DeleteDeadPHIs(Header, TLI);
|
2015-01-29 21:48:05 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
// Validate the selected reductions. All iterations must have an isomorphic
|
|
|
|
// part of the reduction chain and, for non-associative reductions, the chain
|
|
|
|
// entries must appear in order.
|
|
|
|
bool LoopReroll::ReductionTracker::validateSelected() {
|
|
|
|
// For a non-associative reduction, the chain entries must appear in order.
|
|
|
|
for (DenseSet<int>::iterator RI = Reds.begin(), RIE = Reds.end();
|
|
|
|
RI != RIE; ++RI) {
|
|
|
|
int i = *RI;
|
|
|
|
int PrevIter = 0, BaseCount = 0, Count = 0;
|
|
|
|
for (Instruction *J : PossibleReds[i]) {
|
|
|
|
// Note that all instructions in the chain must have been found because
|
|
|
|
// all instructions in the function must have been assigned to some
|
|
|
|
// iteration.
|
|
|
|
int Iter = PossibleRedIter[J];
|
|
|
|
if (Iter != PrevIter && Iter != PrevIter + 1 &&
|
|
|
|
!PossibleReds[i].getReducedValue()->isAssociative()) {
|
|
|
|
DEBUG(dbgs() << "LRR: Out-of-order non-associative reduction: " <<
|
|
|
|
J << "\n");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
if (Iter != PrevIter) {
|
|
|
|
if (Count != BaseCount) {
|
|
|
|
DEBUG(dbgs() << "LRR: Iteration " << PrevIter <<
|
|
|
|
" reduction use count " << Count <<
|
|
|
|
" is not equal to the base use count " <<
|
|
|
|
BaseCount << "\n");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
Count = 0;
|
|
|
|
}
|
|
|
|
|
|
|
|
++Count;
|
|
|
|
if (Iter == 0)
|
|
|
|
++BaseCount;
|
|
|
|
|
|
|
|
PrevIter = Iter;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
// For all selected reductions, remove all parts except those in the first
|
|
|
|
// iteration (and the PHI). Replace outside uses of the reduced value with uses
|
|
|
|
// of the first-iteration reduced value (in other words, reroll the selected
|
|
|
|
// reductions).
|
|
|
|
void LoopReroll::ReductionTracker::replaceSelected() {
|
|
|
|
// Fixup reductions to refer to the last instruction associated with the
|
|
|
|
// first iteration (not the last).
|
|
|
|
for (DenseSet<int>::iterator RI = Reds.begin(), RIE = Reds.end();
|
|
|
|
RI != RIE; ++RI) {
|
|
|
|
int i = *RI;
|
|
|
|
int j = 0;
|
|
|
|
for (int e = PossibleReds[i].size(); j != e; ++j)
|
|
|
|
if (PossibleRedIter[PossibleReds[i][j]] != 0) {
|
|
|
|
--j;
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Replace users with the new end-of-chain value.
|
|
|
|
SmallInstructionVector Users;
|
2015-01-30 05:52:03 +08:00
|
|
|
for (User *U : PossibleReds[i].getReducedValue()->users()) {
|
2015-01-29 21:48:05 +08:00
|
|
|
Users.push_back(cast<Instruction>(U));
|
2015-01-30 05:52:03 +08:00
|
|
|
}
|
2015-01-29 21:48:05 +08:00
|
|
|
|
|
|
|
for (SmallInstructionVector::iterator J = Users.begin(),
|
|
|
|
JE = Users.end(); J != JE; ++J)
|
|
|
|
(*J)->replaceUsesOfWith(PossibleReds[i].getReducedValue(),
|
|
|
|
PossibleReds[i][j]);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Reroll the provided loop with respect to the provided induction variable.
|
|
|
|
// Generally, we're looking for a loop like this:
|
|
|
|
//
|
|
|
|
// %iv = phi [ (preheader, ...), (body, %iv.next) ]
|
|
|
|
// f(%iv)
|
|
|
|
// %iv.1 = add %iv, 1 <-- a root increment
|
|
|
|
// f(%iv.1)
|
|
|
|
// %iv.2 = add %iv, 2 <-- a root increment
|
|
|
|
// f(%iv.2)
|
|
|
|
// %iv.scale_m_1 = add %iv, scale-1 <-- a root increment
|
|
|
|
// f(%iv.scale_m_1)
|
|
|
|
// ...
|
|
|
|
// %iv.next = add %iv, scale
|
|
|
|
// %cmp = icmp(%iv, ...)
|
|
|
|
// br %cmp, header, exit
|
|
|
|
//
|
|
|
|
// Notably, we do not require that f(%iv), f(%iv.1), etc. be isolated groups of
|
|
|
|
// instructions. In other words, the instructions in f(%iv), f(%iv.1), etc. can
|
|
|
|
// be intermixed with eachother. The restriction imposed by this algorithm is
|
|
|
|
// that the relative order of the isomorphic instructions in f(%iv), f(%iv.1),
|
|
|
|
// etc. be the same.
|
|
|
|
//
|
|
|
|
// First, we collect the use set of %iv, excluding the other increment roots.
|
|
|
|
// This gives us f(%iv). Then we iterate over the loop instructions (scale-1)
|
|
|
|
// times, having collected the use set of f(%iv.(i+1)), during which we:
|
|
|
|
// - Ensure that the next unmatched instruction in f(%iv) is isomorphic to
|
|
|
|
// the next unmatched instruction in f(%iv.(i+1)).
|
|
|
|
// - Ensure that both matched instructions don't have any external users
|
|
|
|
// (with the exception of last-in-chain reduction instructions).
|
|
|
|
// - Track the (aliasing) write set, and other side effects, of all
|
|
|
|
// instructions that belong to future iterations that come before the matched
|
|
|
|
// instructions. If the matched instructions read from that write set, then
|
|
|
|
// f(%iv) or f(%iv.(i+1)) has some dependency on instructions in
|
|
|
|
// f(%iv.(j+1)) for some j > i, and we cannot reroll the loop. Similarly,
|
|
|
|
// if any of these future instructions had side effects (could not be
|
|
|
|
// speculatively executed), and so do the matched instructions, when we
|
|
|
|
// cannot reorder those side-effect-producing instructions, and rerolling
|
|
|
|
// fails.
|
|
|
|
//
|
|
|
|
// Finally, we make sure that all loop instructions are either loop increment
|
|
|
|
// roots, belong to simple latch code, parts of validated reductions, part of
|
|
|
|
// f(%iv) or part of some f(%iv.i). If all of that is true (and all reductions
|
|
|
|
// have been validated), then we reroll the loop.
|
|
|
|
bool LoopReroll::reroll(Instruction *IV, Loop *L, BasicBlock *Header,
|
|
|
|
const SCEV *IterCount,
|
|
|
|
ReductionTracker &Reductions) {
|
2015-12-16 03:40:57 +08:00
|
|
|
DAGRootTracker DAGRoots(this, L, IV, SE, AA, TLI, DT, LI, PreserveLCSSA,
|
|
|
|
IVToIncMap);
|
2015-01-29 21:48:05 +08:00
|
|
|
|
|
|
|
if (!DAGRoots.findRoots())
|
|
|
|
return false;
|
|
|
|
DEBUG(dbgs() << "LRR: Found all root induction increments for: " <<
|
|
|
|
*IV << "\n");
|
2015-07-25 06:01:49 +08:00
|
|
|
|
2015-01-29 21:48:05 +08:00
|
|
|
if (!DAGRoots.validate(Reductions))
|
|
|
|
return false;
|
|
|
|
if (!Reductions.validateSelected())
|
|
|
|
return false;
|
|
|
|
// At this point, we've validated the rerolling, and we're committed to
|
|
|
|
// making changes!
|
|
|
|
|
|
|
|
Reductions.replaceSelected();
|
|
|
|
DAGRoots.replace(IterCount);
|
|
|
|
|
2013-11-17 07:59:05 +08:00
|
|
|
++NumRerolledLoops;
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
bool LoopReroll::runOnLoop(Loop *L, LPPassManager &LPM) {
|
2014-02-06 08:07:05 +08:00
|
|
|
if (skipOptnoneFunction(L))
|
|
|
|
return false;
|
|
|
|
|
[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
2015-09-10 01:55:00 +08:00
|
|
|
AA = &getAnalysis<AAResultsWrapperPass>().getAAResults();
|
2015-01-17 22:16:18 +08:00
|
|
|
LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
|
[PM] Port ScalarEvolution to the new pass manager.
This change makes ScalarEvolution a stand-alone object and just produces
one from a pass as needed. Making this work well requires making the
object movable, using references instead of overwritten pointers in
a number of places, and other refactorings.
I've also wired it up to the new pass manager and added a RUN line to
a test to exercise it under the new pass manager. This includes basic
printing support much like with other analyses.
But there is a big and somewhat scary change here. Prior to this patch
ScalarEvolution was never *actually* invalidated!!! Re-running the pass
just re-wired up the various other analyses and didn't remove any of the
existing entries in the SCEV caches or clear out anything at all. This
might seem OK as everything in SCEV that can uses ValueHandles to track
updates to the values that serve as SCEV keys. However, this still means
that as we ran SCEV over each function in the module, we kept
accumulating more and more SCEVs into the cache. At the end, we would
have a SCEV cache with every value that we ever needed a SCEV for in the
entire module!!! Yowzers. The releaseMemory routine would dump all of
this, but that isn't realy called during normal runs of the pipeline as
far as I can see.
To make matters worse, there *is* actually a key that we don't update
with value handles -- there is a map keyed off of Loop*s. Because
LoopInfo *does* release its memory from run to run, it is entirely
possible to run SCEV over one function, then over another function, and
then lookup a Loop* from the second function but find an entry inserted
for the first function! Ouch.
To make matters still worse, there are plenty of updates that *don't*
trip a value handle. It seems incredibly unlikely that today GVN or
another pass that invalidates SCEV can update values in *just* such
a way that a subsequent run of SCEV will incorrectly find lookups in
a cache, but it is theoretically possible and would be a nightmare to
debug.
With this refactoring, I've fixed all this by actually destroying and
recreating the ScalarEvolution object from run to run. Technically, this
could increase the amount of malloc traffic we see, but then again it is
also technically correct. ;] I don't actually think we're suffering from
tons of malloc traffic from SCEV because if we were, the fact that we
never clear the memory would seem more likely to have come up as an
actual problem before now. So, I've made the simple fix here. If in fact
there are serious issues with too much allocation and deallocation,
I can work on a clever fix that preserves the allocations (while
clearing the data) between each run, but I'd prefer to do that kind of
optimization with a test case / benchmark that shows why we need such
cleverness (and that can test that we actually make it faster). It's
possible that this will make some things faster by making the SCEV
caches have higher locality (due to being significantly smaller) so
until there is a clear benchmark, I think the simple change is best.
Differential Revision: http://reviews.llvm.org/D12063
llvm-svn: 245193
2015-08-17 10:08:17 +08:00
|
|
|
SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE();
|
2015-01-15 18:41:28 +08:00
|
|
|
TLI = &getAnalysis<TargetLibraryInfoWrapperPass>().getTLI();
|
2014-01-13 21:07:17 +08:00
|
|
|
DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
|
2015-12-16 03:40:57 +08:00
|
|
|
PreserveLCSSA = mustPreserveAnalysisID(LCSSAID);
|
2013-11-17 07:59:05 +08:00
|
|
|
|
|
|
|
BasicBlock *Header = L->getHeader();
|
|
|
|
DEBUG(dbgs() << "LRR: F[" << Header->getParent()->getName() <<
|
|
|
|
"] Loop %" << Header->getName() << " (" <<
|
|
|
|
L->getNumBlocks() << " block(s))\n");
|
|
|
|
|
|
|
|
bool Changed = false;
|
|
|
|
|
|
|
|
// For now, we'll handle only single BB loops.
|
|
|
|
if (L->getNumBlocks() > 1)
|
|
|
|
return Changed;
|
|
|
|
|
|
|
|
if (!SE->hasLoopInvariantBackedgeTakenCount(L))
|
|
|
|
return Changed;
|
|
|
|
|
|
|
|
const SCEV *LIBETC = SE->getBackedgeTakenCount(L);
|
2015-09-23 09:59:04 +08:00
|
|
|
const SCEV *IterCount = SE->getAddExpr(LIBETC, SE->getOne(LIBETC->getType()));
|
2013-11-17 07:59:05 +08:00
|
|
|
DEBUG(dbgs() << "LRR: iteration count = " << *IterCount << "\n");
|
|
|
|
|
|
|
|
// First, we need to find the induction variable with respect to which we can
|
|
|
|
// reroll (there may be several possible options).
|
|
|
|
SmallInstructionVector PossibleIVs;
|
2015-07-25 06:01:49 +08:00
|
|
|
IVToIncMap.clear();
|
2013-11-17 07:59:05 +08:00
|
|
|
collectPossibleIVs(L, PossibleIVs);
|
|
|
|
|
|
|
|
if (PossibleIVs.empty()) {
|
|
|
|
DEBUG(dbgs() << "LRR: No possible IVs found\n");
|
|
|
|
return Changed;
|
|
|
|
}
|
|
|
|
|
|
|
|
ReductionTracker Reductions;
|
|
|
|
collectPossibleReductions(L, Reductions);
|
|
|
|
|
|
|
|
// For each possible IV, collect the associated possible set of 'root' nodes
|
|
|
|
// (i+1, i+2, etc.).
|
|
|
|
for (SmallInstructionVector::iterator I = PossibleIVs.begin(),
|
|
|
|
IE = PossibleIVs.end(); I != IE; ++I)
|
|
|
|
if (reroll(*I, L, Header, IterCount, Reductions)) {
|
|
|
|
Changed = true;
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
|
|
|
|
return Changed;
|
|
|
|
}
|