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llvm-mirror/lib/Transforms/Scalar/LoopUnrollPass.cpp

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//===-- LoopUnroll.cpp - Loop unroller pass -------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
//
// This pass implements a simple loop unroller. It works best when loops have
// been canonicalized by the -indvars pass, allowing it to determine the trip
// counts of loops easily.
//===----------------------------------------------------------------------===//
#include "llvm/Transforms/Scalar/LoopUnrollPass.h"
#include "llvm/ADT/SetVector.h"
#include "llvm/Analysis/AssumptionCache.h"
#include "llvm/Analysis/CodeMetrics.h"
#include "llvm/Analysis/GlobalsModRef.h"
#include "llvm/Analysis/InstructionSimplify.h"
#include "llvm/Analysis/LoopPass.h"
#include "llvm/Analysis/LoopPassManager.h"
#include "llvm/Analysis/LoopUnrollAnalyzer.h"
#include "llvm/Analysis/OptimizationDiagnosticInfo.h"
#include "llvm/Analysis/ScalarEvolution.h"
#include "llvm/Analysis/ScalarEvolutionExpressions.h"
#include "llvm/Analysis/TargetTransformInfo.h"
#include "llvm/IR/DataLayout.h"
#include "llvm/IR/Dominators.h"
#include "llvm/IR/InstVisitor.h"
#include "llvm/IR/IntrinsicInst.h"
#include "llvm/IR/Metadata.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
#include "llvm/Transforms/Scalar.h"
[LPM] Factor all of the loop analysis usage updates into a common helper routine. We were getting this wrong in small ways and generally being very inconsistent about it across loop passes. Instead, let's have a common place where we do this. One minor downside is that this will require some analyses like SCEV in more places than they are strictly needed. However, this seems benign as these analyses are complete no-ops, and without this consistency we can in many cases end up with the legacy pass manager scheduling deciding to split up a loop pass pipeline in order to run the function analysis half-way through. It is very, very annoying to fix these without just being very pedantic across the board. The only loop passes I've not updated here are ones that use AU.setPreservesAll() such as IVUsers (an analysis) and the pass printer. They seemed less relevant. With this patch, almost all of the problems in PR24804 around loop pass pipelines are fixed. The one remaining issue is that we run simplify-cfg and instcombine in the middle of the loop pass pipeline. We've recently added some loop variants of these passes that would seem substantially cleaner to use, but this at least gets us much closer to the previous state. Notably, the seven loop pass managers is down to three. I've not updated the loop passes using LoopAccessAnalysis because that analysis hasn't been fully wired into LoopSimplify/LCSSA, and it isn't clear that those transforms want to support those forms anyways. They all run late anyways, so this is harmless. Similarly, LSR is left alone because it already carefully manages its forms and doesn't need to get fused into a single loop pass manager with a bunch of other loop passes. LoopReroll didn't use loop simplified form previously, and I've updated the test case to match the trivially different output. Finally, I've also factored all the pass initialization for the passes that use this technique as well, so that should be done regularly and reliably. Thanks to James for the help reviewing and thinking about this stuff, and Ben for help thinking about it as well! Differential Revision: http://reviews.llvm.org/D17435 llvm-svn: 261316
2016-02-19 11:45:18 +01:00
#include "llvm/Transforms/Utils/LoopUtils.h"
#include "llvm/Transforms/Utils/UnrollLoop.h"
#include <climits>
#include <utility>
using namespace llvm;
#define DEBUG_TYPE "loop-unroll"
static cl::opt<unsigned>
UnrollThreshold("unroll-threshold", cl::Hidden,
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
cl::desc("The baseline cost threshold for loop unrolling"));
static cl::opt<unsigned> UnrollPercentDynamicCostSavedThreshold(
"unroll-percent-dynamic-cost-saved-threshold", cl::init(50), cl::Hidden,
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
cl::desc("The percentage of estimated dynamic cost which must be saved by "
"unrolling to allow unrolling up to the max threshold."));
static cl::opt<unsigned> UnrollDynamicCostSavingsDiscount(
"unroll-dynamic-cost-savings-discount", cl::init(100), cl::Hidden,
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
cl::desc("This is the amount discounted from the total unroll cost when "
"the unrolled form has a high dynamic cost savings (triggered by "
"the '-unroll-perecent-dynamic-cost-saved-threshold' flag)."));
static cl::opt<unsigned> UnrollMaxIterationsCountToAnalyze(
"unroll-max-iteration-count-to-analyze", cl::init(10), cl::Hidden,
cl::desc("Don't allow loop unrolling to simulate more than this number of"
"iterations when checking full unroll profitability"));
static cl::opt<unsigned> UnrollCount(
"unroll-count", cl::Hidden,
cl::desc("Use this unroll count for all loops including those with "
"unroll_count pragma values, for testing purposes"));
static cl::opt<unsigned> UnrollMaxCount(
"unroll-max-count", cl::Hidden,
cl::desc("Set the max unroll count for partial and runtime unrolling, for"
"testing purposes"));
static cl::opt<unsigned> UnrollFullMaxCount(
"unroll-full-max-count", cl::Hidden,
cl::desc(
"Set the max unroll count for full unrolling, for testing purposes"));
static cl::opt<bool>
UnrollAllowPartial("unroll-allow-partial", cl::Hidden,
cl::desc("Allows loops to be partially unrolled until "
"-unroll-threshold loop size is reached."));
static cl::opt<bool> UnrollAllowRemainder(
"unroll-allow-remainder", cl::Hidden,
cl::desc("Allow generation of a loop remainder (extra iterations) "
"when unrolling a loop."));
static cl::opt<bool>
UnrollRuntime("unroll-runtime", cl::ZeroOrMore, cl::Hidden,
cl::desc("Unroll loops with run-time trip counts"));
static cl::opt<unsigned> PragmaUnrollThreshold(
"pragma-unroll-threshold", cl::init(16 * 1024), cl::Hidden,
cl::desc("Unrolled size limit for loops with an unroll(full) or "
"unroll_count pragma."));
/// A magic value for use with the Threshold parameter to indicate
/// that the loop unroll should be performed regardless of how much
/// code expansion would result.
static const unsigned NoThreshold = UINT_MAX;
/// Default unroll count for loops with run-time trip count if
/// -unroll-count is not set
static const unsigned DefaultUnrollRuntimeCount = 8;
/// Gather the various unrolling parameters based on the defaults, compiler
/// flags, TTI overrides and user specified parameters.
static TargetTransformInfo::UnrollingPreferences gatherUnrollingPreferences(
Loop *L, const TargetTransformInfo &TTI, Optional<unsigned> UserThreshold,
Optional<unsigned> UserCount, Optional<bool> UserAllowPartial,
Optional<bool> UserRuntime) {
TargetTransformInfo::UnrollingPreferences UP;
// Set up the defaults
UP.Threshold = 150;
UP.PercentDynamicCostSavedThreshold = 50;
UP.DynamicCostSavingsDiscount = 100;
UP.OptSizeThreshold = 0;
UP.PartialThreshold = UP.Threshold;
UP.PartialOptSizeThreshold = 0;
UP.Count = 0;
UP.MaxCount = UINT_MAX;
UP.FullUnrollMaxCount = UINT_MAX;
UP.Partial = false;
UP.Runtime = false;
UP.AllowRemainder = true;
UP.AllowExpensiveTripCount = false;
UP.Force = false;
// Override with any target specific settings
TTI.getUnrollingPreferences(L, UP);
// Apply size attributes
if (L->getHeader()->getParent()->optForSize()) {
UP.Threshold = UP.OptSizeThreshold;
UP.PartialThreshold = UP.PartialOptSizeThreshold;
}
// Apply any user values specified by cl::opt
if (UnrollThreshold.getNumOccurrences() > 0) {
UP.Threshold = UnrollThreshold;
UP.PartialThreshold = UnrollThreshold;
}
if (UnrollPercentDynamicCostSavedThreshold.getNumOccurrences() > 0)
UP.PercentDynamicCostSavedThreshold =
UnrollPercentDynamicCostSavedThreshold;
if (UnrollDynamicCostSavingsDiscount.getNumOccurrences() > 0)
UP.DynamicCostSavingsDiscount = UnrollDynamicCostSavingsDiscount;
if (UnrollMaxCount.getNumOccurrences() > 0)
UP.MaxCount = UnrollMaxCount;
if (UnrollFullMaxCount.getNumOccurrences() > 0)
UP.FullUnrollMaxCount = UnrollFullMaxCount;
if (UnrollAllowPartial.getNumOccurrences() > 0)
UP.Partial = UnrollAllowPartial;
if (UnrollAllowRemainder.getNumOccurrences() > 0)
UP.AllowRemainder = UnrollAllowRemainder;
if (UnrollRuntime.getNumOccurrences() > 0)
UP.Runtime = UnrollRuntime;
// Apply user values provided by argument
if (UserThreshold.hasValue()) {
UP.Threshold = *UserThreshold;
UP.PartialThreshold = *UserThreshold;
}
if (UserCount.hasValue())
UP.Count = *UserCount;
if (UserAllowPartial.hasValue())
UP.Partial = *UserAllowPartial;
if (UserRuntime.hasValue())
UP.Runtime = *UserRuntime;
return UP;
}
namespace {
/// A struct to densely store the state of an instruction after unrolling at
/// each iteration.
///
/// This is designed to work like a tuple of <Instruction *, int> for the
/// purposes of hashing and lookup, but to be able to associate two boolean
/// states with each key.
struct UnrolledInstState {
Instruction *I;
int Iteration : 30;
unsigned IsFree : 1;
unsigned IsCounted : 1;
};
/// Hashing and equality testing for a set of the instruction states.
struct UnrolledInstStateKeyInfo {
typedef DenseMapInfo<Instruction *> PtrInfo;
typedef DenseMapInfo<std::pair<Instruction *, int>> PairInfo;
static inline UnrolledInstState getEmptyKey() {
return {PtrInfo::getEmptyKey(), 0, 0, 0};
}
static inline UnrolledInstState getTombstoneKey() {
return {PtrInfo::getTombstoneKey(), 0, 0, 0};
}
static inline unsigned getHashValue(const UnrolledInstState &S) {
return PairInfo::getHashValue({S.I, S.Iteration});
}
static inline bool isEqual(const UnrolledInstState &LHS,
const UnrolledInstState &RHS) {
return PairInfo::isEqual({LHS.I, LHS.Iteration}, {RHS.I, RHS.Iteration});
}
};
}
namespace {
struct EstimatedUnrollCost {
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
/// \brief The estimated cost after unrolling.
int UnrolledCost;
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
/// \brief The estimated dynamic cost of executing the instructions in the
/// rolled form.
int RolledDynamicCost;
};
}
/// \brief Figure out if the loop is worth full unrolling.
///
/// Complete loop unrolling can make some loads constant, and we need to know
/// if that would expose any further optimization opportunities. This routine
/// estimates this optimization. It computes cost of unrolled loop
/// (UnrolledCost) and dynamic cost of the original loop (RolledDynamicCost). By
/// dynamic cost we mean that we won't count costs of blocks that are known not
/// to be executed (i.e. if we have a branch in the loop and we know that at the
/// given iteration its condition would be resolved to true, we won't add up the
/// cost of the 'false'-block).
/// \returns Optional value, holding the RolledDynamicCost and UnrolledCost. If
/// the analysis failed (no benefits expected from the unrolling, or the loop is
/// too big to analyze), the returned value is None.
static Optional<EstimatedUnrollCost>
analyzeLoopUnrollCost(const Loop *L, unsigned TripCount, DominatorTree &DT,
ScalarEvolution &SE, const TargetTransformInfo &TTI,
int MaxUnrolledLoopSize) {
// We want to be able to scale offsets by the trip count and add more offsets
// to them without checking for overflows, and we already don't want to
// analyze *massive* trip counts, so we force the max to be reasonably small.
assert(UnrollMaxIterationsCountToAnalyze < (INT_MAX / 2) &&
"The unroll iterations max is too large!");
// Only analyze inner loops. We can't properly estimate cost of nested loops
// and we won't visit inner loops again anyway.
if (!L->empty())
return None;
// Don't simulate loops with a big or unknown tripcount
if (!UnrollMaxIterationsCountToAnalyze || !TripCount ||
TripCount > UnrollMaxIterationsCountToAnalyze)
return None;
SmallSetVector<BasicBlock *, 16> BBWorklist;
SmallSetVector<std::pair<BasicBlock *, BasicBlock *>, 4> ExitWorklist;
DenseMap<Value *, Constant *> SimplifiedValues;
SmallVector<std::pair<Value *, Constant *>, 4> SimplifiedInputValues;
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
// The estimated cost of the unrolled form of the loop. We try to estimate
// this by simplifying as much as we can while computing the estimate.
int UnrolledCost = 0;
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
// We also track the estimated dynamic (that is, actually executed) cost in
// the rolled form. This helps identify cases when the savings from unrolling
// aren't just exposing dead control flows, but actual reduced dynamic
// instructions due to the simplifications which we expect to occur after
// unrolling.
int RolledDynamicCost = 0;
// We track the simplification of each instruction in each iteration. We use
// this to recursively merge costs into the unrolled cost on-demand so that
// we don't count the cost of any dead code. This is essentially a map from
// <instruction, int> to <bool, bool>, but stored as a densely packed struct.
DenseSet<UnrolledInstState, UnrolledInstStateKeyInfo> InstCostMap;
// A small worklist used to accumulate cost of instructions from each
// observable and reached root in the loop.
SmallVector<Instruction *, 16> CostWorklist;
// PHI-used worklist used between iterations while accumulating cost.
SmallVector<Instruction *, 4> PHIUsedList;
// Helper function to accumulate cost for instructions in the loop.
auto AddCostRecursively = [&](Instruction &RootI, int Iteration) {
assert(Iteration >= 0 && "Cannot have a negative iteration!");
assert(CostWorklist.empty() && "Must start with an empty cost list");
assert(PHIUsedList.empty() && "Must start with an empty phi used list");
CostWorklist.push_back(&RootI);
for (;; --Iteration) {
do {
Instruction *I = CostWorklist.pop_back_val();
// InstCostMap only uses I and Iteration as a key, the other two values
// don't matter here.
auto CostIter = InstCostMap.find({I, Iteration, 0, 0});
if (CostIter == InstCostMap.end())
// If an input to a PHI node comes from a dead path through the loop
// we may have no cost data for it here. What that actually means is
// that it is free.
continue;
auto &Cost = *CostIter;
if (Cost.IsCounted)
// Already counted this instruction.
continue;
// Mark that we are counting the cost of this instruction now.
Cost.IsCounted = true;
// If this is a PHI node in the loop header, just add it to the PHI set.
if (auto *PhiI = dyn_cast<PHINode>(I))
if (PhiI->getParent() == L->getHeader()) {
assert(Cost.IsFree && "Loop PHIs shouldn't be evaluated as they "
"inherently simplify during unrolling.");
if (Iteration == 0)
continue;
// Push the incoming value from the backedge into the PHI used list
// if it is an in-loop instruction. We'll use this to populate the
// cost worklist for the next iteration (as we count backwards).
if (auto *OpI = dyn_cast<Instruction>(
PhiI->getIncomingValueForBlock(L->getLoopLatch())))
if (L->contains(OpI))
PHIUsedList.push_back(OpI);
continue;
}
// First accumulate the cost of this instruction.
if (!Cost.IsFree) {
UnrolledCost += TTI.getUserCost(I);
DEBUG(dbgs() << "Adding cost of instruction (iteration " << Iteration
<< "): ");
DEBUG(I->dump());
}
// We must count the cost of every operand which is not free,
// recursively. If we reach a loop PHI node, simply add it to the set
// to be considered on the next iteration (backwards!).
for (Value *Op : I->operands()) {
// Check whether this operand is free due to being a constant or
// outside the loop.
auto *OpI = dyn_cast<Instruction>(Op);
if (!OpI || !L->contains(OpI))
continue;
// Otherwise accumulate its cost.
CostWorklist.push_back(OpI);
}
} while (!CostWorklist.empty());
if (PHIUsedList.empty())
// We've exhausted the search.
break;
assert(Iteration > 0 &&
"Cannot track PHI-used values past the first iteration!");
CostWorklist.append(PHIUsedList.begin(), PHIUsedList.end());
PHIUsedList.clear();
}
};
// Ensure that we don't violate the loop structure invariants relied on by
// this analysis.
assert(L->isLoopSimplifyForm() && "Must put loop into normal form first.");
assert(L->isLCSSAForm(DT) &&
"Must have loops in LCSSA form to track live-out values.");
DEBUG(dbgs() << "Starting LoopUnroll profitability analysis...\n");
// Simulate execution of each iteration of the loop counting instructions,
// which would be simplified.
// Since the same load will take different values on different iterations,
// we literally have to go through all loop's iterations.
for (unsigned Iteration = 0; Iteration < TripCount; ++Iteration) {
DEBUG(dbgs() << " Analyzing iteration " << Iteration << "\n");
// Prepare for the iteration by collecting any simplified entry or backedge
// inputs.
for (Instruction &I : *L->getHeader()) {
auto *PHI = dyn_cast<PHINode>(&I);
if (!PHI)
break;
// The loop header PHI nodes must have exactly two input: one from the
// loop preheader and one from the loop latch.
assert(
PHI->getNumIncomingValues() == 2 &&
"Must have an incoming value only for the preheader and the latch.");
Value *V = PHI->getIncomingValueForBlock(
Iteration == 0 ? L->getLoopPreheader() : L->getLoopLatch());
Constant *C = dyn_cast<Constant>(V);
if (Iteration != 0 && !C)
C = SimplifiedValues.lookup(V);
if (C)
SimplifiedInputValues.push_back({PHI, C});
}
// Now clear and re-populate the map for the next iteration.
SimplifiedValues.clear();
while (!SimplifiedInputValues.empty())
SimplifiedValues.insert(SimplifiedInputValues.pop_back_val());
UnrolledInstAnalyzer Analyzer(Iteration, SimplifiedValues, SE, L);
BBWorklist.clear();
BBWorklist.insert(L->getHeader());
// Note that we *must not* cache the size, this loop grows the worklist.
for (unsigned Idx = 0; Idx != BBWorklist.size(); ++Idx) {
BasicBlock *BB = BBWorklist[Idx];
// Visit all instructions in the given basic block and try to simplify
// it. We don't change the actual IR, just count optimization
// opportunities.
for (Instruction &I : *BB) {
// Track this instruction's expected baseline cost when executing the
// rolled loop form.
RolledDynamicCost += TTI.getUserCost(&I);
// Visit the instruction to analyze its loop cost after unrolling,
// and if the visitor returns true, mark the instruction as free after
// unrolling and continue.
bool IsFree = Analyzer.visit(I);
bool Inserted = InstCostMap.insert({&I, (int)Iteration,
(unsigned)IsFree,
/*IsCounted*/ false}).second;
(void)Inserted;
assert(Inserted && "Cannot have a state for an unvisited instruction!");
if (IsFree)
continue;
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
// If the instruction might have a side-effect recursively account for
// the cost of it and all the instructions leading up to it.
if (I.mayHaveSideEffects())
AddCostRecursively(I, Iteration);
// Can't properly model a cost of a call.
// FIXME: With a proper cost model we should be able to do it.
if(isa<CallInst>(&I))
return None;
// If unrolled body turns out to be too big, bail out.
if (UnrolledCost > MaxUnrolledLoopSize) {
DEBUG(dbgs() << " Exceeded threshold.. exiting.\n"
<< " UnrolledCost: " << UnrolledCost
<< ", MaxUnrolledLoopSize: " << MaxUnrolledLoopSize
<< "\n");
return None;
}
}
TerminatorInst *TI = BB->getTerminator();
// Add in the live successors by first checking whether we have terminator
// that may be simplified based on the values simplified by this call.
BasicBlock *KnownSucc = nullptr;
if (BranchInst *BI = dyn_cast<BranchInst>(TI)) {
if (BI->isConditional()) {
if (Constant *SimpleCond =
SimplifiedValues.lookup(BI->getCondition())) {
// Just take the first successor if condition is undef
if (isa<UndefValue>(SimpleCond))
KnownSucc = BI->getSuccessor(0);
else if (ConstantInt *SimpleCondVal =
dyn_cast<ConstantInt>(SimpleCond))
KnownSucc = BI->getSuccessor(SimpleCondVal->isZero() ? 1 : 0);
}
}
} else if (SwitchInst *SI = dyn_cast<SwitchInst>(TI)) {
if (Constant *SimpleCond =
SimplifiedValues.lookup(SI->getCondition())) {
// Just take the first successor if condition is undef
if (isa<UndefValue>(SimpleCond))
KnownSucc = SI->getSuccessor(0);
else if (ConstantInt *SimpleCondVal =
dyn_cast<ConstantInt>(SimpleCond))
KnownSucc = SI->findCaseValue(SimpleCondVal).getCaseSuccessor();
}
}
if (KnownSucc) {
if (L->contains(KnownSucc))
BBWorklist.insert(KnownSucc);
else
ExitWorklist.insert({BB, KnownSucc});
continue;
}
// Add BB's successors to the worklist.
for (BasicBlock *Succ : successors(BB))
if (L->contains(Succ))
BBWorklist.insert(Succ);
else
ExitWorklist.insert({BB, Succ});
AddCostRecursively(*TI, Iteration);
}
// If we found no optimization opportunities on the first iteration, we
// won't find them on later ones too.
if (UnrolledCost == RolledDynamicCost) {
DEBUG(dbgs() << " No opportunities found.. exiting.\n"
<< " UnrolledCost: " << UnrolledCost << "\n");
return None;
}
}
while (!ExitWorklist.empty()) {
BasicBlock *ExitingBB, *ExitBB;
std::tie(ExitingBB, ExitBB) = ExitWorklist.pop_back_val();
for (Instruction &I : *ExitBB) {
auto *PN = dyn_cast<PHINode>(&I);
if (!PN)
break;
Value *Op = PN->getIncomingValueForBlock(ExitingBB);
if (auto *OpI = dyn_cast<Instruction>(Op))
if (L->contains(OpI))
AddCostRecursively(*OpI, TripCount - 1);
}
}
DEBUG(dbgs() << "Analysis finished:\n"
<< "UnrolledCost: " << UnrolledCost << ", "
<< "RolledDynamicCost: " << RolledDynamicCost << "\n");
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
return {{UnrolledCost, RolledDynamicCost}};
}
/// ApproximateLoopSize - Approximate the size of the loop.
static unsigned ApproximateLoopSize(const Loop *L, unsigned &NumCalls,
bool &NotDuplicatable, bool &Convergent,
const TargetTransformInfo &TTI,
AssumptionCache *AC) {
SmallPtrSet<const Value *, 32> EphValues;
CodeMetrics::collectEphemeralValues(L, AC, EphValues);
CodeMetrics Metrics;
for (BasicBlock *BB : L->blocks())
Metrics.analyzeBasicBlock(BB, TTI, EphValues);
NumCalls = Metrics.NumInlineCandidates;
NotDuplicatable = Metrics.notDuplicatable;
Convergent = Metrics.convergent;
2011-07-23 02:29:16 +02:00
unsigned LoopSize = Metrics.NumInsts;
2011-07-23 02:29:16 +02:00
// Don't allow an estimate of size zero. This would allows unrolling of loops
// with huge iteration counts, which is a compile time problem even if it's
// not a problem for code quality. Also, the code using this size may assume
// that each loop has at least three instructions (likely a conditional
// branch, a comparison feeding that branch, and some kind of loop increment
// feeding that comparison instruction).
LoopSize = std::max(LoopSize, 3u);
2011-07-23 02:29:16 +02:00
return LoopSize;
}
// Returns the loop hint metadata node with the given name (for example,
// "llvm.loop.unroll.count"). If no such metadata node exists, then nullptr is
// returned.
static MDNode *GetUnrollMetadataForLoop(const Loop *L, StringRef Name) {
if (MDNode *LoopID = L->getLoopID())
return GetUnrollMetadata(LoopID, Name);
return nullptr;
}
// Returns true if the loop has an unroll(full) pragma.
static bool HasUnrollFullPragma(const Loop *L) {
return GetUnrollMetadataForLoop(L, "llvm.loop.unroll.full");
}
// Returns true if the loop has an unroll(enable) pragma. This metadata is used
// for both "#pragma unroll" and "#pragma clang loop unroll(enable)" directives.
static bool HasUnrollEnablePragma(const Loop *L) {
return GetUnrollMetadataForLoop(L, "llvm.loop.unroll.enable");
}
// Returns true if the loop has an unroll(disable) pragma.
static bool HasUnrollDisablePragma(const Loop *L) {
return GetUnrollMetadataForLoop(L, "llvm.loop.unroll.disable");
}
// Returns true if the loop has an runtime unroll(disable) pragma.
static bool HasRuntimeUnrollDisablePragma(const Loop *L) {
return GetUnrollMetadataForLoop(L, "llvm.loop.unroll.runtime.disable");
}
// If loop has an unroll_count pragma return the (necessarily
// positive) value from the pragma. Otherwise return 0.
static unsigned UnrollCountPragmaValue(const Loop *L) {
MDNode *MD = GetUnrollMetadataForLoop(L, "llvm.loop.unroll.count");
if (MD) {
assert(MD->getNumOperands() == 2 &&
"Unroll count hint metadata should have two operands.");
IR: Split Metadata from Value Split `Metadata` away from the `Value` class hierarchy, as part of PR21532. Assembly and bitcode changes are in the wings, but this is the bulk of the change for the IR C++ API. I have a follow-up patch prepared for `clang`. If this breaks other sub-projects, I apologize in advance :(. Help me compile it on Darwin I'll try to fix it. FWIW, the errors should be easy to fix, so it may be simpler to just fix it yourself. This breaks the build for all metadata-related code that's out-of-tree. Rest assured the transition is mechanical and the compiler should catch almost all of the problems. Here's a quick guide for updating your code: - `Metadata` is the root of a class hierarchy with three main classes: `MDNode`, `MDString`, and `ValueAsMetadata`. It is distinct from the `Value` class hierarchy. It is typeless -- i.e., instances do *not* have a `Type`. - `MDNode`'s operands are all `Metadata *` (instead of `Value *`). - `TrackingVH<MDNode>` and `WeakVH` referring to metadata can be replaced with `TrackingMDNodeRef` and `TrackingMDRef`, respectively. If you're referring solely to resolved `MDNode`s -- post graph construction -- just use `MDNode*`. - `MDNode` (and the rest of `Metadata`) have only limited support for `replaceAllUsesWith()`. As long as an `MDNode` is pointing at a forward declaration -- the result of `MDNode::getTemporary()` -- it maintains a side map of its uses and can RAUW itself. Once the forward declarations are fully resolved RAUW support is dropped on the ground. This means that uniquing collisions on changing operands cause nodes to become "distinct". (This already happened fairly commonly, whenever an operand went to null.) If you're constructing complex (non self-reference) `MDNode` cycles, you need to call `MDNode::resolveCycles()` on each node (or on a top-level node that somehow references all of the nodes). Also, don't do that. Metadata cycles (and the RAUW machinery needed to construct them) are expensive. - An `MDNode` can only refer to a `Constant` through a bridge called `ConstantAsMetadata` (one of the subclasses of `ValueAsMetadata`). As a side effect, accessing an operand of an `MDNode` that is known to be, e.g., `ConstantInt`, takes three steps: first, cast from `Metadata` to `ConstantAsMetadata`; second, extract the `Constant`; third, cast down to `ConstantInt`. The eventual goal is to introduce `MDInt`/`MDFloat`/etc. and have metadata schema owners transition away from using `Constant`s when the type isn't important (and they don't care about referring to `GlobalValue`s). In the meantime, I've added transitional API to the `mdconst` namespace that matches semantics with the old code, in order to avoid adding the error-prone three-step equivalent to every call site. If your old code was: MDNode *N = foo(); bar(isa <ConstantInt>(N->getOperand(0))); baz(cast <ConstantInt>(N->getOperand(1))); bak(cast_or_null <ConstantInt>(N->getOperand(2))); bat(dyn_cast <ConstantInt>(N->getOperand(3))); bay(dyn_cast_or_null<ConstantInt>(N->getOperand(4))); you can trivially match its semantics with: MDNode *N = foo(); bar(mdconst::hasa <ConstantInt>(N->getOperand(0))); baz(mdconst::extract <ConstantInt>(N->getOperand(1))); bak(mdconst::extract_or_null <ConstantInt>(N->getOperand(2))); bat(mdconst::dyn_extract <ConstantInt>(N->getOperand(3))); bay(mdconst::dyn_extract_or_null<ConstantInt>(N->getOperand(4))); and when you transition your metadata schema to `MDInt`: MDNode *N = foo(); bar(isa <MDInt>(N->getOperand(0))); baz(cast <MDInt>(N->getOperand(1))); bak(cast_or_null <MDInt>(N->getOperand(2))); bat(dyn_cast <MDInt>(N->getOperand(3))); bay(dyn_cast_or_null<MDInt>(N->getOperand(4))); - A `CallInst` -- specifically, intrinsic instructions -- can refer to metadata through a bridge called `MetadataAsValue`. This is a subclass of `Value` where `getType()->isMetadataTy()`. `MetadataAsValue` is the *only* class that can legally refer to a `LocalAsMetadata`, which is a bridged form of non-`Constant` values like `Argument` and `Instruction`. It can also refer to any other `Metadata` subclass. (I'll break all your testcases in a follow-up commit, when I propagate this change to assembly.) llvm-svn: 223802
2014-12-09 19:38:53 +01:00
unsigned Count =
mdconst::extract<ConstantInt>(MD->getOperand(1))->getZExtValue();
assert(Count >= 1 && "Unroll count must be positive.");
return Count;
}
return 0;
}
// Remove existing unroll metadata and add unroll disable metadata to
// indicate the loop has already been unrolled. This prevents a loop
// from being unrolled more than is directed by a pragma if the loop
// unrolling pass is run more than once (which it generally is).
static void SetLoopAlreadyUnrolled(Loop *L) {
MDNode *LoopID = L->getLoopID();
// First remove any existing loop unrolling metadata.
IR: Split Metadata from Value Split `Metadata` away from the `Value` class hierarchy, as part of PR21532. Assembly and bitcode changes are in the wings, but this is the bulk of the change for the IR C++ API. I have a follow-up patch prepared for `clang`. If this breaks other sub-projects, I apologize in advance :(. Help me compile it on Darwin I'll try to fix it. FWIW, the errors should be easy to fix, so it may be simpler to just fix it yourself. This breaks the build for all metadata-related code that's out-of-tree. Rest assured the transition is mechanical and the compiler should catch almost all of the problems. Here's a quick guide for updating your code: - `Metadata` is the root of a class hierarchy with three main classes: `MDNode`, `MDString`, and `ValueAsMetadata`. It is distinct from the `Value` class hierarchy. It is typeless -- i.e., instances do *not* have a `Type`. - `MDNode`'s operands are all `Metadata *` (instead of `Value *`). - `TrackingVH<MDNode>` and `WeakVH` referring to metadata can be replaced with `TrackingMDNodeRef` and `TrackingMDRef`, respectively. If you're referring solely to resolved `MDNode`s -- post graph construction -- just use `MDNode*`. - `MDNode` (and the rest of `Metadata`) have only limited support for `replaceAllUsesWith()`. As long as an `MDNode` is pointing at a forward declaration -- the result of `MDNode::getTemporary()` -- it maintains a side map of its uses and can RAUW itself. Once the forward declarations are fully resolved RAUW support is dropped on the ground. This means that uniquing collisions on changing operands cause nodes to become "distinct". (This already happened fairly commonly, whenever an operand went to null.) If you're constructing complex (non self-reference) `MDNode` cycles, you need to call `MDNode::resolveCycles()` on each node (or on a top-level node that somehow references all of the nodes). Also, don't do that. Metadata cycles (and the RAUW machinery needed to construct them) are expensive. - An `MDNode` can only refer to a `Constant` through a bridge called `ConstantAsMetadata` (one of the subclasses of `ValueAsMetadata`). As a side effect, accessing an operand of an `MDNode` that is known to be, e.g., `ConstantInt`, takes three steps: first, cast from `Metadata` to `ConstantAsMetadata`; second, extract the `Constant`; third, cast down to `ConstantInt`. The eventual goal is to introduce `MDInt`/`MDFloat`/etc. and have metadata schema owners transition away from using `Constant`s when the type isn't important (and they don't care about referring to `GlobalValue`s). In the meantime, I've added transitional API to the `mdconst` namespace that matches semantics with the old code, in order to avoid adding the error-prone three-step equivalent to every call site. If your old code was: MDNode *N = foo(); bar(isa <ConstantInt>(N->getOperand(0))); baz(cast <ConstantInt>(N->getOperand(1))); bak(cast_or_null <ConstantInt>(N->getOperand(2))); bat(dyn_cast <ConstantInt>(N->getOperand(3))); bay(dyn_cast_or_null<ConstantInt>(N->getOperand(4))); you can trivially match its semantics with: MDNode *N = foo(); bar(mdconst::hasa <ConstantInt>(N->getOperand(0))); baz(mdconst::extract <ConstantInt>(N->getOperand(1))); bak(mdconst::extract_or_null <ConstantInt>(N->getOperand(2))); bat(mdconst::dyn_extract <ConstantInt>(N->getOperand(3))); bay(mdconst::dyn_extract_or_null<ConstantInt>(N->getOperand(4))); and when you transition your metadata schema to `MDInt`: MDNode *N = foo(); bar(isa <MDInt>(N->getOperand(0))); baz(cast <MDInt>(N->getOperand(1))); bak(cast_or_null <MDInt>(N->getOperand(2))); bat(dyn_cast <MDInt>(N->getOperand(3))); bay(dyn_cast_or_null<MDInt>(N->getOperand(4))); - A `CallInst` -- specifically, intrinsic instructions -- can refer to metadata through a bridge called `MetadataAsValue`. This is a subclass of `Value` where `getType()->isMetadataTy()`. `MetadataAsValue` is the *only* class that can legally refer to a `LocalAsMetadata`, which is a bridged form of non-`Constant` values like `Argument` and `Instruction`. It can also refer to any other `Metadata` subclass. (I'll break all your testcases in a follow-up commit, when I propagate this change to assembly.) llvm-svn: 223802
2014-12-09 19:38:53 +01:00
SmallVector<Metadata *, 4> MDs;
// Reserve first location for self reference to the LoopID metadata node.
IR: Split Metadata from Value Split `Metadata` away from the `Value` class hierarchy, as part of PR21532. Assembly and bitcode changes are in the wings, but this is the bulk of the change for the IR C++ API. I have a follow-up patch prepared for `clang`. If this breaks other sub-projects, I apologize in advance :(. Help me compile it on Darwin I'll try to fix it. FWIW, the errors should be easy to fix, so it may be simpler to just fix it yourself. This breaks the build for all metadata-related code that's out-of-tree. Rest assured the transition is mechanical and the compiler should catch almost all of the problems. Here's a quick guide for updating your code: - `Metadata` is the root of a class hierarchy with three main classes: `MDNode`, `MDString`, and `ValueAsMetadata`. It is distinct from the `Value` class hierarchy. It is typeless -- i.e., instances do *not* have a `Type`. - `MDNode`'s operands are all `Metadata *` (instead of `Value *`). - `TrackingVH<MDNode>` and `WeakVH` referring to metadata can be replaced with `TrackingMDNodeRef` and `TrackingMDRef`, respectively. If you're referring solely to resolved `MDNode`s -- post graph construction -- just use `MDNode*`. - `MDNode` (and the rest of `Metadata`) have only limited support for `replaceAllUsesWith()`. As long as an `MDNode` is pointing at a forward declaration -- the result of `MDNode::getTemporary()` -- it maintains a side map of its uses and can RAUW itself. Once the forward declarations are fully resolved RAUW support is dropped on the ground. This means that uniquing collisions on changing operands cause nodes to become "distinct". (This already happened fairly commonly, whenever an operand went to null.) If you're constructing complex (non self-reference) `MDNode` cycles, you need to call `MDNode::resolveCycles()` on each node (or on a top-level node that somehow references all of the nodes). Also, don't do that. Metadata cycles (and the RAUW machinery needed to construct them) are expensive. - An `MDNode` can only refer to a `Constant` through a bridge called `ConstantAsMetadata` (one of the subclasses of `ValueAsMetadata`). As a side effect, accessing an operand of an `MDNode` that is known to be, e.g., `ConstantInt`, takes three steps: first, cast from `Metadata` to `ConstantAsMetadata`; second, extract the `Constant`; third, cast down to `ConstantInt`. The eventual goal is to introduce `MDInt`/`MDFloat`/etc. and have metadata schema owners transition away from using `Constant`s when the type isn't important (and they don't care about referring to `GlobalValue`s). In the meantime, I've added transitional API to the `mdconst` namespace that matches semantics with the old code, in order to avoid adding the error-prone three-step equivalent to every call site. If your old code was: MDNode *N = foo(); bar(isa <ConstantInt>(N->getOperand(0))); baz(cast <ConstantInt>(N->getOperand(1))); bak(cast_or_null <ConstantInt>(N->getOperand(2))); bat(dyn_cast <ConstantInt>(N->getOperand(3))); bay(dyn_cast_or_null<ConstantInt>(N->getOperand(4))); you can trivially match its semantics with: MDNode *N = foo(); bar(mdconst::hasa <ConstantInt>(N->getOperand(0))); baz(mdconst::extract <ConstantInt>(N->getOperand(1))); bak(mdconst::extract_or_null <ConstantInt>(N->getOperand(2))); bat(mdconst::dyn_extract <ConstantInt>(N->getOperand(3))); bay(mdconst::dyn_extract_or_null<ConstantInt>(N->getOperand(4))); and when you transition your metadata schema to `MDInt`: MDNode *N = foo(); bar(isa <MDInt>(N->getOperand(0))); baz(cast <MDInt>(N->getOperand(1))); bak(cast_or_null <MDInt>(N->getOperand(2))); bat(dyn_cast <MDInt>(N->getOperand(3))); bay(dyn_cast_or_null<MDInt>(N->getOperand(4))); - A `CallInst` -- specifically, intrinsic instructions -- can refer to metadata through a bridge called `MetadataAsValue`. This is a subclass of `Value` where `getType()->isMetadataTy()`. `MetadataAsValue` is the *only* class that can legally refer to a `LocalAsMetadata`, which is a bridged form of non-`Constant` values like `Argument` and `Instruction`. It can also refer to any other `Metadata` subclass. (I'll break all your testcases in a follow-up commit, when I propagate this change to assembly.) llvm-svn: 223802
2014-12-09 19:38:53 +01:00
MDs.push_back(nullptr);
if (LoopID) {
for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
bool IsUnrollMetadata = false;
MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i));
if (MD) {
const MDString *S = dyn_cast<MDString>(MD->getOperand(0));
IsUnrollMetadata = S && S->getString().startswith("llvm.loop.unroll.");
}
if (!IsUnrollMetadata)
MDs.push_back(LoopID->getOperand(i));
}
}
// Add unroll(disable) metadata to disable future unrolling.
LLVMContext &Context = L->getHeader()->getContext();
IR: Split Metadata from Value Split `Metadata` away from the `Value` class hierarchy, as part of PR21532. Assembly and bitcode changes are in the wings, but this is the bulk of the change for the IR C++ API. I have a follow-up patch prepared for `clang`. If this breaks other sub-projects, I apologize in advance :(. Help me compile it on Darwin I'll try to fix it. FWIW, the errors should be easy to fix, so it may be simpler to just fix it yourself. This breaks the build for all metadata-related code that's out-of-tree. Rest assured the transition is mechanical and the compiler should catch almost all of the problems. Here's a quick guide for updating your code: - `Metadata` is the root of a class hierarchy with three main classes: `MDNode`, `MDString`, and `ValueAsMetadata`. It is distinct from the `Value` class hierarchy. It is typeless -- i.e., instances do *not* have a `Type`. - `MDNode`'s operands are all `Metadata *` (instead of `Value *`). - `TrackingVH<MDNode>` and `WeakVH` referring to metadata can be replaced with `TrackingMDNodeRef` and `TrackingMDRef`, respectively. If you're referring solely to resolved `MDNode`s -- post graph construction -- just use `MDNode*`. - `MDNode` (and the rest of `Metadata`) have only limited support for `replaceAllUsesWith()`. As long as an `MDNode` is pointing at a forward declaration -- the result of `MDNode::getTemporary()` -- it maintains a side map of its uses and can RAUW itself. Once the forward declarations are fully resolved RAUW support is dropped on the ground. This means that uniquing collisions on changing operands cause nodes to become "distinct". (This already happened fairly commonly, whenever an operand went to null.) If you're constructing complex (non self-reference) `MDNode` cycles, you need to call `MDNode::resolveCycles()` on each node (or on a top-level node that somehow references all of the nodes). Also, don't do that. Metadata cycles (and the RAUW machinery needed to construct them) are expensive. - An `MDNode` can only refer to a `Constant` through a bridge called `ConstantAsMetadata` (one of the subclasses of `ValueAsMetadata`). As a side effect, accessing an operand of an `MDNode` that is known to be, e.g., `ConstantInt`, takes three steps: first, cast from `Metadata` to `ConstantAsMetadata`; second, extract the `Constant`; third, cast down to `ConstantInt`. The eventual goal is to introduce `MDInt`/`MDFloat`/etc. and have metadata schema owners transition away from using `Constant`s when the type isn't important (and they don't care about referring to `GlobalValue`s). In the meantime, I've added transitional API to the `mdconst` namespace that matches semantics with the old code, in order to avoid adding the error-prone three-step equivalent to every call site. If your old code was: MDNode *N = foo(); bar(isa <ConstantInt>(N->getOperand(0))); baz(cast <ConstantInt>(N->getOperand(1))); bak(cast_or_null <ConstantInt>(N->getOperand(2))); bat(dyn_cast <ConstantInt>(N->getOperand(3))); bay(dyn_cast_or_null<ConstantInt>(N->getOperand(4))); you can trivially match its semantics with: MDNode *N = foo(); bar(mdconst::hasa <ConstantInt>(N->getOperand(0))); baz(mdconst::extract <ConstantInt>(N->getOperand(1))); bak(mdconst::extract_or_null <ConstantInt>(N->getOperand(2))); bat(mdconst::dyn_extract <ConstantInt>(N->getOperand(3))); bay(mdconst::dyn_extract_or_null<ConstantInt>(N->getOperand(4))); and when you transition your metadata schema to `MDInt`: MDNode *N = foo(); bar(isa <MDInt>(N->getOperand(0))); baz(cast <MDInt>(N->getOperand(1))); bak(cast_or_null <MDInt>(N->getOperand(2))); bat(dyn_cast <MDInt>(N->getOperand(3))); bay(dyn_cast_or_null<MDInt>(N->getOperand(4))); - A `CallInst` -- specifically, intrinsic instructions -- can refer to metadata through a bridge called `MetadataAsValue`. This is a subclass of `Value` where `getType()->isMetadataTy()`. `MetadataAsValue` is the *only* class that can legally refer to a `LocalAsMetadata`, which is a bridged form of non-`Constant` values like `Argument` and `Instruction`. It can also refer to any other `Metadata` subclass. (I'll break all your testcases in a follow-up commit, when I propagate this change to assembly.) llvm-svn: 223802
2014-12-09 19:38:53 +01:00
SmallVector<Metadata *, 1> DisableOperands;
DisableOperands.push_back(MDString::get(Context, "llvm.loop.unroll.disable"));
MDNode *DisableNode = MDNode::get(Context, DisableOperands);
IR: Split Metadata from Value Split `Metadata` away from the `Value` class hierarchy, as part of PR21532. Assembly and bitcode changes are in the wings, but this is the bulk of the change for the IR C++ API. I have a follow-up patch prepared for `clang`. If this breaks other sub-projects, I apologize in advance :(. Help me compile it on Darwin I'll try to fix it. FWIW, the errors should be easy to fix, so it may be simpler to just fix it yourself. This breaks the build for all metadata-related code that's out-of-tree. Rest assured the transition is mechanical and the compiler should catch almost all of the problems. Here's a quick guide for updating your code: - `Metadata` is the root of a class hierarchy with three main classes: `MDNode`, `MDString`, and `ValueAsMetadata`. It is distinct from the `Value` class hierarchy. It is typeless -- i.e., instances do *not* have a `Type`. - `MDNode`'s operands are all `Metadata *` (instead of `Value *`). - `TrackingVH<MDNode>` and `WeakVH` referring to metadata can be replaced with `TrackingMDNodeRef` and `TrackingMDRef`, respectively. If you're referring solely to resolved `MDNode`s -- post graph construction -- just use `MDNode*`. - `MDNode` (and the rest of `Metadata`) have only limited support for `replaceAllUsesWith()`. As long as an `MDNode` is pointing at a forward declaration -- the result of `MDNode::getTemporary()` -- it maintains a side map of its uses and can RAUW itself. Once the forward declarations are fully resolved RAUW support is dropped on the ground. This means that uniquing collisions on changing operands cause nodes to become "distinct". (This already happened fairly commonly, whenever an operand went to null.) If you're constructing complex (non self-reference) `MDNode` cycles, you need to call `MDNode::resolveCycles()` on each node (or on a top-level node that somehow references all of the nodes). Also, don't do that. Metadata cycles (and the RAUW machinery needed to construct them) are expensive. - An `MDNode` can only refer to a `Constant` through a bridge called `ConstantAsMetadata` (one of the subclasses of `ValueAsMetadata`). As a side effect, accessing an operand of an `MDNode` that is known to be, e.g., `ConstantInt`, takes three steps: first, cast from `Metadata` to `ConstantAsMetadata`; second, extract the `Constant`; third, cast down to `ConstantInt`. The eventual goal is to introduce `MDInt`/`MDFloat`/etc. and have metadata schema owners transition away from using `Constant`s when the type isn't important (and they don't care about referring to `GlobalValue`s). In the meantime, I've added transitional API to the `mdconst` namespace that matches semantics with the old code, in order to avoid adding the error-prone three-step equivalent to every call site. If your old code was: MDNode *N = foo(); bar(isa <ConstantInt>(N->getOperand(0))); baz(cast <ConstantInt>(N->getOperand(1))); bak(cast_or_null <ConstantInt>(N->getOperand(2))); bat(dyn_cast <ConstantInt>(N->getOperand(3))); bay(dyn_cast_or_null<ConstantInt>(N->getOperand(4))); you can trivially match its semantics with: MDNode *N = foo(); bar(mdconst::hasa <ConstantInt>(N->getOperand(0))); baz(mdconst::extract <ConstantInt>(N->getOperand(1))); bak(mdconst::extract_or_null <ConstantInt>(N->getOperand(2))); bat(mdconst::dyn_extract <ConstantInt>(N->getOperand(3))); bay(mdconst::dyn_extract_or_null<ConstantInt>(N->getOperand(4))); and when you transition your metadata schema to `MDInt`: MDNode *N = foo(); bar(isa <MDInt>(N->getOperand(0))); baz(cast <MDInt>(N->getOperand(1))); bak(cast_or_null <MDInt>(N->getOperand(2))); bat(dyn_cast <MDInt>(N->getOperand(3))); bay(dyn_cast_or_null<MDInt>(N->getOperand(4))); - A `CallInst` -- specifically, intrinsic instructions -- can refer to metadata through a bridge called `MetadataAsValue`. This is a subclass of `Value` where `getType()->isMetadataTy()`. `MetadataAsValue` is the *only* class that can legally refer to a `LocalAsMetadata`, which is a bridged form of non-`Constant` values like `Argument` and `Instruction`. It can also refer to any other `Metadata` subclass. (I'll break all your testcases in a follow-up commit, when I propagate this change to assembly.) llvm-svn: 223802
2014-12-09 19:38:53 +01:00
MDs.push_back(DisableNode);
IR: Split Metadata from Value Split `Metadata` away from the `Value` class hierarchy, as part of PR21532. Assembly and bitcode changes are in the wings, but this is the bulk of the change for the IR C++ API. I have a follow-up patch prepared for `clang`. If this breaks other sub-projects, I apologize in advance :(. Help me compile it on Darwin I'll try to fix it. FWIW, the errors should be easy to fix, so it may be simpler to just fix it yourself. This breaks the build for all metadata-related code that's out-of-tree. Rest assured the transition is mechanical and the compiler should catch almost all of the problems. Here's a quick guide for updating your code: - `Metadata` is the root of a class hierarchy with three main classes: `MDNode`, `MDString`, and `ValueAsMetadata`. It is distinct from the `Value` class hierarchy. It is typeless -- i.e., instances do *not* have a `Type`. - `MDNode`'s operands are all `Metadata *` (instead of `Value *`). - `TrackingVH<MDNode>` and `WeakVH` referring to metadata can be replaced with `TrackingMDNodeRef` and `TrackingMDRef`, respectively. If you're referring solely to resolved `MDNode`s -- post graph construction -- just use `MDNode*`. - `MDNode` (and the rest of `Metadata`) have only limited support for `replaceAllUsesWith()`. As long as an `MDNode` is pointing at a forward declaration -- the result of `MDNode::getTemporary()` -- it maintains a side map of its uses and can RAUW itself. Once the forward declarations are fully resolved RAUW support is dropped on the ground. This means that uniquing collisions on changing operands cause nodes to become "distinct". (This already happened fairly commonly, whenever an operand went to null.) If you're constructing complex (non self-reference) `MDNode` cycles, you need to call `MDNode::resolveCycles()` on each node (or on a top-level node that somehow references all of the nodes). Also, don't do that. Metadata cycles (and the RAUW machinery needed to construct them) are expensive. - An `MDNode` can only refer to a `Constant` through a bridge called `ConstantAsMetadata` (one of the subclasses of `ValueAsMetadata`). As a side effect, accessing an operand of an `MDNode` that is known to be, e.g., `ConstantInt`, takes three steps: first, cast from `Metadata` to `ConstantAsMetadata`; second, extract the `Constant`; third, cast down to `ConstantInt`. The eventual goal is to introduce `MDInt`/`MDFloat`/etc. and have metadata schema owners transition away from using `Constant`s when the type isn't important (and they don't care about referring to `GlobalValue`s). In the meantime, I've added transitional API to the `mdconst` namespace that matches semantics with the old code, in order to avoid adding the error-prone three-step equivalent to every call site. If your old code was: MDNode *N = foo(); bar(isa <ConstantInt>(N->getOperand(0))); baz(cast <ConstantInt>(N->getOperand(1))); bak(cast_or_null <ConstantInt>(N->getOperand(2))); bat(dyn_cast <ConstantInt>(N->getOperand(3))); bay(dyn_cast_or_null<ConstantInt>(N->getOperand(4))); you can trivially match its semantics with: MDNode *N = foo(); bar(mdconst::hasa <ConstantInt>(N->getOperand(0))); baz(mdconst::extract <ConstantInt>(N->getOperand(1))); bak(mdconst::extract_or_null <ConstantInt>(N->getOperand(2))); bat(mdconst::dyn_extract <ConstantInt>(N->getOperand(3))); bay(mdconst::dyn_extract_or_null<ConstantInt>(N->getOperand(4))); and when you transition your metadata schema to `MDInt`: MDNode *N = foo(); bar(isa <MDInt>(N->getOperand(0))); baz(cast <MDInt>(N->getOperand(1))); bak(cast_or_null <MDInt>(N->getOperand(2))); bat(dyn_cast <MDInt>(N->getOperand(3))); bay(dyn_cast_or_null<MDInt>(N->getOperand(4))); - A `CallInst` -- specifically, intrinsic instructions -- can refer to metadata through a bridge called `MetadataAsValue`. This is a subclass of `Value` where `getType()->isMetadataTy()`. `MetadataAsValue` is the *only* class that can legally refer to a `LocalAsMetadata`, which is a bridged form of non-`Constant` values like `Argument` and `Instruction`. It can also refer to any other `Metadata` subclass. (I'll break all your testcases in a follow-up commit, when I propagate this change to assembly.) llvm-svn: 223802
2014-12-09 19:38:53 +01:00
MDNode *NewLoopID = MDNode::get(Context, MDs);
// Set operand 0 to refer to the loop id itself.
NewLoopID->replaceOperandWith(0, NewLoopID);
L->setLoopID(NewLoopID);
}
static bool canUnrollCompletely(Loop *L, unsigned Threshold,
unsigned PercentDynamicCostSavedThreshold,
unsigned DynamicCostSavingsDiscount,
uint64_t UnrolledCost,
uint64_t RolledDynamicCost) {
if (Threshold == NoThreshold) {
DEBUG(dbgs() << " Can fully unroll, because no threshold is set.\n");
return true;
}
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
if (UnrolledCost <= Threshold) {
DEBUG(dbgs() << " Can fully unroll, because unrolled cost: "
<< UnrolledCost << "<" << Threshold << "\n");
return true;
}
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
assert(UnrolledCost && "UnrolledCost can't be 0 at this point.");
assert(RolledDynamicCost >= UnrolledCost &&
"Cannot have a higher unrolled cost than a rolled cost!");
// Compute the percentage of the dynamic cost in the rolled form that is
// saved when unrolled. If unrolling dramatically reduces the estimated
// dynamic cost of the loop, we use a higher threshold to allow more
// unrolling.
unsigned PercentDynamicCostSaved =
(uint64_t)(RolledDynamicCost - UnrolledCost) * 100ull / RolledDynamicCost;
if (PercentDynamicCostSaved >= PercentDynamicCostSavedThreshold &&
(int64_t)UnrolledCost - (int64_t)DynamicCostSavingsDiscount <=
(int64_t)Threshold) {
DEBUG(dbgs() << " Can fully unroll, because unrolling will reduce the "
"expected dynamic cost by "
<< PercentDynamicCostSaved << "% (threshold: "
<< PercentDynamicCostSavedThreshold << "%)\n"
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
<< " and the unrolled cost (" << UnrolledCost
<< ") is less than the max threshold ("
<< DynamicCostSavingsDiscount << ").\n");
return true;
}
DEBUG(dbgs() << " Too large to fully unroll:\n");
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
DEBUG(dbgs() << " Threshold: " << Threshold << "\n");
DEBUG(dbgs() << " Max threshold: " << DynamicCostSavingsDiscount << "\n");
DEBUG(dbgs() << " Percent cost saved threshold: "
<< PercentDynamicCostSavedThreshold << "%\n");
DEBUG(dbgs() << " Unrolled cost: " << UnrolledCost << "\n");
DEBUG(dbgs() << " Rolled dynamic cost: " << RolledDynamicCost << "\n");
DEBUG(dbgs() << " Percent cost saved: " << PercentDynamicCostSaved
<< "\n");
return false;
}
// Returns true if unroll count was set explicitly.
// Calculates unroll count and writes it to UP.Count.
static bool computeUnrollCount(Loop *L, const TargetTransformInfo &TTI,
DominatorTree &DT, LoopInfo *LI,
ScalarEvolution *SE,
OptimizationRemarkEmitter *ORE,
unsigned TripCount, unsigned TripMultiple,
unsigned LoopSize,
TargetTransformInfo::UnrollingPreferences &UP) {
// BEInsns represents number of instructions optimized when "back edge"
// becomes "fall through" in unrolled loop.
// For now we count a conditional branch on a backedge and a comparison
// feeding it.
unsigned BEInsns = 2;
// Check for explicit Count.
// 1st priority is unroll count set by "unroll-count" option.
bool UserUnrollCount = UnrollCount.getNumOccurrences() > 0;
if (UserUnrollCount) {
UP.Count = UnrollCount;
UP.AllowExpensiveTripCount = true;
UP.Force = true;
if (UP.AllowRemainder &&
(LoopSize - BEInsns) * UP.Count + BEInsns < UP.Threshold)
return true;
}
2011-07-23 02:29:16 +02:00
// 2nd priority is unroll count set by pragma.
unsigned PragmaCount = UnrollCountPragmaValue(L);
if (PragmaCount > 0) {
UP.Count = PragmaCount;
UP.Runtime = true;
UP.AllowExpensiveTripCount = true;
UP.Force = true;
if (UP.AllowRemainder &&
(LoopSize - BEInsns) * UP.Count + BEInsns < PragmaUnrollThreshold)
return true;
}
bool PragmaFullUnroll = HasUnrollFullPragma(L);
if (PragmaFullUnroll && TripCount != 0) {
UP.Count = TripCount;
if ((LoopSize - BEInsns) * UP.Count + BEInsns < PragmaUnrollThreshold)
return false;
}
bool PragmaEnableUnroll = HasUnrollEnablePragma(L);
bool ExplicitUnroll = PragmaCount > 0 || PragmaFullUnroll ||
PragmaEnableUnroll || UserUnrollCount;
uint64_t UnrolledSize;
if (ExplicitUnroll && TripCount != 0) {
// If the loop has an unrolling pragma, we want to be more aggressive with
// unrolling limits. Set thresholds to at least the PragmaThreshold value
// which is larger than the default limits.
UP.Threshold = std::max<unsigned>(UP.Threshold, PragmaUnrollThreshold);
UP.PartialThreshold =
std::max<unsigned>(UP.PartialThreshold, PragmaUnrollThreshold);
}
// 3rd priority is full unroll count.
// Full unroll make sense only when TripCount could be staticaly calculated.
// Also we need to check if we exceed FullUnrollMaxCount.
if (TripCount && TripCount <= UP.FullUnrollMaxCount) {
// When computing the unrolled size, note that BEInsns are not replicated
// like the rest of the loop body.
UnrolledSize = (uint64_t)(LoopSize - BEInsns) * TripCount + BEInsns;
if (canUnrollCompletely(L, UP.Threshold, 100, UP.DynamicCostSavingsDiscount,
[Unroll] Rework the naming and structure of the new unroll heuristics. The new naming is (to me) much easier to understand. Here is a summary of the new state of the world: - '*Threshold' is the threshold for full unrolling. It is measured against the estimated unrolled cost as computed by getUserCost in TTI (or CodeMetrics, etc). We will exceed this threshold when unrolling loops where unrolling exposes a significant degree of simplification of the logic within the loop. - '*PercentDynamicCostSavedThreshold' is the percentage of the loop's estimated dynamic execution cost which needs to be saved by unrolling to apply a discount to the estimated unrolled cost. - '*DynamicCostSavingsDiscount' is the discount applied to the estimated unrolling cost when the dynamic savings are expected to be high. When actually analyzing the loop, we now produce both an estimated unrolled cost, and an estimated rolled cost. The rolled cost is notably a dynamic estimate based on our analysis of the expected execution of each iteration. While we're still working to build up the infrastructure for making these estimates, to me it is much more clear *how* to make them better when they have reasonably descriptive names. For example, we may want to apply estimated (from heuristics or profiles) dynamic execution weights to the *dynamic* cost estimates. If we start doing that, we would also need to track the static unrolled cost and the dynamic unrolled cost, as only the latter could reasonably be weighted by profile information. This patch is sadly not without functionality change for the new unroll analysis logic. Buried in the heuristic management were several things that surprised me. For example, we never subtracted the optimized instruction count off when comparing against the unroll heursistics! I don't know if this just got lost somewhere along the way or what, but with the new accounting of things, this is much easier to keep track of and we use the post-simplification cost estimate to compare to the thresholds, and use the dynamic cost reduction ratio to select whether we can exceed the baseline threshold. The old values of these flags also don't necessarily make sense. My impression is that none of these thresholds or discounts have been tuned yet, and so they're just arbitrary placehold numbers. As such, I've not bothered to adjust for the fact that this is now a discount and not a tow-tier threshold model. We need to tune all these values once the logic is ready to be enabled. Differential Revision: http://reviews.llvm.org/D9966 llvm-svn: 239164
2015-06-05 19:01:43 +02:00
UnrolledSize, UnrolledSize)) {
UP.Count = TripCount;
return ExplicitUnroll;
} else {
// The loop isn't that small, but we still can fully unroll it if that
// helps to remove a significant number of instructions.
// To check that, run additional analysis on the loop.
if (Optional<EstimatedUnrollCost> Cost = analyzeLoopUnrollCost(
L, TripCount, DT, *SE, TTI,
UP.Threshold + UP.DynamicCostSavingsDiscount))
if (canUnrollCompletely(L, UP.Threshold,
UP.PercentDynamicCostSavedThreshold,
UP.DynamicCostSavingsDiscount,
Cost->UnrolledCost, Cost->RolledDynamicCost)) {
UP.Count = TripCount;
return ExplicitUnroll;
}
}
}
// 4rd priority is partial unrolling.
// Try partial unroll only when TripCount could be staticaly calculated.
if (TripCount) {
if (UP.Count == 0)
UP.Count = TripCount;
UP.Partial |= ExplicitUnroll;
if (!UP.Partial) {
DEBUG(dbgs() << " will not try to unroll partially because "
<< "-unroll-allow-partial not given\n");
UP.Count = 0;
return false;
}
if (UP.PartialThreshold != NoThreshold) {
// Reduce unroll count to be modulo of TripCount for partial unrolling.
UnrolledSize = (uint64_t)(LoopSize - BEInsns) * UP.Count + BEInsns;
if (UnrolledSize > UP.PartialThreshold)
UP.Count = (std::max(UP.PartialThreshold, 3u) - BEInsns) /
(LoopSize - BEInsns);
if (UP.Count > UP.MaxCount)
UP.Count = UP.MaxCount;
while (UP.Count != 0 && TripCount % UP.Count != 0)
UP.Count--;
if (UP.AllowRemainder && UP.Count <= 1) {
// If there is no Count that is modulo of TripCount, set Count to
// largest power-of-two factor that satisfies the threshold limit.
// As we'll create fixup loop, do the type of unrolling only if
// remainder loop is allowed.
UP.Count = DefaultUnrollRuntimeCount;
UnrolledSize = (LoopSize - BEInsns) * UP.Count + BEInsns;
while (UP.Count != 0 && UnrolledSize > UP.PartialThreshold) {
UP.Count >>= 1;
UnrolledSize = (LoopSize - BEInsns) * UP.Count + BEInsns;
}
}
if (UP.Count < 2) {
if (PragmaEnableUnroll)
ORE->emitOptimizationRemarkMissed(
DEBUG_TYPE, L,
"Unable to unroll loop as directed by unroll(enable) pragma "
"because unrolled size is too large.");
UP.Count = 0;
}
} else {
UP.Count = TripCount;
}
if ((PragmaFullUnroll || PragmaEnableUnroll) && TripCount &&
UP.Count != TripCount)
ORE->emitOptimizationRemarkMissed(
DEBUG_TYPE, L,
"Unable to fully unroll loop as directed by unroll pragma because "
"unrolled size is too large.");
return ExplicitUnroll;
}
assert(TripCount == 0 &&
"All cases when TripCount is constant should be covered here.");
if (PragmaFullUnroll)
ORE->emitOptimizationRemarkMissed(
DEBUG_TYPE, L,
"Unable to fully unroll loop as directed by unroll(full) pragma "
"because loop has a runtime trip count.");
// 5th priority is runtime unrolling.
// Don't unroll a runtime trip count loop when it is disabled.
if (HasRuntimeUnrollDisablePragma(L)) {
UP.Count = 0;
return false;
}
// Reduce count based on the type of unrolling and the threshold values.
UP.Runtime |= PragmaEnableUnroll || PragmaCount > 0 || UserUnrollCount;
if (!UP.Runtime) {
DEBUG(dbgs() << " will not try to unroll loop with runtime trip count "
<< "-unroll-runtime not given\n");
UP.Count = 0;
return false;
}
if (UP.Count == 0)
UP.Count = DefaultUnrollRuntimeCount;
UnrolledSize = (LoopSize - BEInsns) * UP.Count + BEInsns;
// Reduce unroll count to be the largest power-of-two factor of
// the original count which satisfies the threshold limit.
while (UP.Count != 0 && UnrolledSize > UP.PartialThreshold) {
UP.Count >>= 1;
UnrolledSize = (LoopSize - BEInsns) * UP.Count + BEInsns;
}
#ifndef NDEBUG
unsigned OrigCount = UP.Count;
#endif
if (!UP.AllowRemainder && UP.Count != 0 && (TripMultiple % UP.Count) != 0) {
while (UP.Count != 0 && TripMultiple % UP.Count != 0)
UP.Count >>= 1;
DEBUG(dbgs() << "Remainder loop is restricted (that could architecture "
"specific or because the loop contains a convergent "
"instruction), so unroll count must divide the trip "
"multiple, "
<< TripMultiple << ". Reducing unroll count from "
<< OrigCount << " to " << UP.Count << ".\n");
if (PragmaCount > 0 && !UP.AllowRemainder)
ORE->emitOptimizationRemarkMissed(
DEBUG_TYPE, L,
Twine("Unable to unroll loop the number of times directed by "
"unroll_count pragma because remainder loop is restricted "
"(that could architecture specific or because the loop "
"contains a convergent instruction) and so must have an unroll "
"count that divides the loop trip multiple of ") +
Twine(TripMultiple) + ". Unrolling instead " + Twine(UP.Count) +
" time(s).");
}
if (UP.Count > UP.MaxCount)
UP.Count = UP.MaxCount;
DEBUG(dbgs() << " partially unrolling with count: " << UP.Count << "\n");
if (UP.Count < 2)
UP.Count = 0;
return ExplicitUnroll;
}
static bool tryToUnrollLoop(Loop *L, DominatorTree &DT, LoopInfo *LI,
ScalarEvolution *SE, const TargetTransformInfo &TTI,
AssumptionCache &AC, OptimizationRemarkEmitter &ORE,
bool PreserveLCSSA,
Optional<unsigned> ProvidedCount,
Optional<unsigned> ProvidedThreshold,
Optional<bool> ProvidedAllowPartial,
Optional<bool> ProvidedRuntime) {
DEBUG(dbgs() << "Loop Unroll: F[" << L->getHeader()->getParent()->getName()
<< "] Loop %" << L->getHeader()->getName() << "\n");
if (HasUnrollDisablePragma(L)) {
return false;
}
unsigned NumInlineCandidates;
bool NotDuplicatable;
bool Convergent;
unsigned LoopSize = ApproximateLoopSize(
L, NumInlineCandidates, NotDuplicatable, Convergent, TTI, &AC);
DEBUG(dbgs() << " Loop Size = " << LoopSize << "\n");
if (NotDuplicatable) {
DEBUG(dbgs() << " Not unrolling loop which contains non-duplicatable"
<< " instructions.\n");
return false;
}
if (NumInlineCandidates != 0) {
DEBUG(dbgs() << " Not unrolling loop with inlinable calls.\n");
return false;
}
if (!L->isLoopSimplifyForm()) {
DEBUG(
dbgs() << " Not unrolling loop which is not in loop-simplify form.\n");
return false;
}
// Find trip count and trip multiple if count is not available
unsigned TripCount = 0;
unsigned TripMultiple = 1;
// If there are multiple exiting blocks but one of them is the latch, use the
// latch for the trip count estimation. Otherwise insist on a single exiting
// block for the trip count estimation.
BasicBlock *ExitingBlock = L->getLoopLatch();
if (!ExitingBlock || !L->isLoopExiting(ExitingBlock))
ExitingBlock = L->getExitingBlock();
if (ExitingBlock) {
TripCount = SE->getSmallConstantTripCount(L, ExitingBlock);
TripMultiple = SE->getSmallConstantTripMultiple(L, ExitingBlock);
}
TargetTransformInfo::UnrollingPreferences UP = gatherUnrollingPreferences(
L, TTI, ProvidedThreshold, ProvidedCount, ProvidedAllowPartial,
ProvidedRuntime);
// If the loop contains a convergent operation, the prelude we'd add
// to do the first few instructions before we hit the unrolled loop
// is unsafe -- it adds a control-flow dependency to the convergent
// operation. Therefore restrict remainder loop (try unrollig without).
//
// TODO: This is quite conservative. In practice, convergent_op()
// is likely to be called unconditionally in the loop. In this
// case, the program would be ill-formed (on most architectures)
// unless n were the same on all threads in a thread group.
// Assuming n is the same on all threads, any kind of unrolling is
// safe. But currently llvm's notion of convergence isn't powerful
// enough to express this.
if (Convergent)
UP.AllowRemainder = false;
bool IsCountSetExplicitly = computeUnrollCount(
L, TTI, DT, LI, SE, &ORE, TripCount, TripMultiple, LoopSize, UP);
if (!UP.Count)
return false;
// Unroll factor (Count) must be less or equal to TripCount.
if (TripCount && UP.Count > TripCount)
UP.Count = TripCount;
// Unroll the loop.
if (!UnrollLoop(L, UP.Count, TripCount, UP.Force, UP.Runtime,
UP.AllowExpensiveTripCount, TripMultiple, LI, SE, &DT, &AC,
&ORE, PreserveLCSSA))
return false;
// If loop has an unroll count pragma or unrolled by explicitly set count
// mark loop as unrolled to prevent unrolling beyond that requested.
if (IsCountSetExplicitly)
SetLoopAlreadyUnrolled(L);
return true;
}
namespace {
class LoopUnroll : public LoopPass {
public:
static char ID; // Pass ID, replacement for typeid
LoopUnroll(Optional<unsigned> Threshold = None,
Optional<unsigned> Count = None,
Optional<bool> AllowPartial = None, Optional<bool> Runtime = None)
: LoopPass(ID), ProvidedCount(std::move(Count)),
ProvidedThreshold(Threshold), ProvidedAllowPartial(AllowPartial),
ProvidedRuntime(Runtime) {
initializeLoopUnrollPass(*PassRegistry::getPassRegistry());
}
Optional<unsigned> ProvidedCount;
Optional<unsigned> ProvidedThreshold;
Optional<bool> ProvidedAllowPartial;
Optional<bool> ProvidedRuntime;
bool runOnLoop(Loop *L, LPPassManager &) override {
if (skipLoop(L))
return false;
Function &F = *L->getHeader()->getParent();
auto &DT = getAnalysis<DominatorTreeWrapperPass>().getDomTree();
LoopInfo *LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
ScalarEvolution *SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE();
const TargetTransformInfo &TTI =
getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F);
auto &AC = getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F);
auto &ORE = getAnalysis<OptimizationRemarkEmitterWrapperPass>().getORE();
bool PreserveLCSSA = mustPreserveAnalysisID(LCSSAID);
return tryToUnrollLoop(L, DT, LI, SE, TTI, AC, ORE, PreserveLCSSA,
ProvidedCount, ProvidedThreshold,
ProvidedAllowPartial, ProvidedRuntime);
}
/// This transformation requires natural loop information & requires that
/// loop preheaders be inserted into the CFG...
///
void getAnalysisUsage(AnalysisUsage &AU) const override {
AU.addRequired<AssumptionCacheTracker>();
AU.addRequired<TargetTransformInfoWrapperPass>();
[LPM] Factor all of the loop analysis usage updates into a common helper routine. We were getting this wrong in small ways and generally being very inconsistent about it across loop passes. Instead, let's have a common place where we do this. One minor downside is that this will require some analyses like SCEV in more places than they are strictly needed. However, this seems benign as these analyses are complete no-ops, and without this consistency we can in many cases end up with the legacy pass manager scheduling deciding to split up a loop pass pipeline in order to run the function analysis half-way through. It is very, very annoying to fix these without just being very pedantic across the board. The only loop passes I've not updated here are ones that use AU.setPreservesAll() such as IVUsers (an analysis) and the pass printer. They seemed less relevant. With this patch, almost all of the problems in PR24804 around loop pass pipelines are fixed. The one remaining issue is that we run simplify-cfg and instcombine in the middle of the loop pass pipeline. We've recently added some loop variants of these passes that would seem substantially cleaner to use, but this at least gets us much closer to the previous state. Notably, the seven loop pass managers is down to three. I've not updated the loop passes using LoopAccessAnalysis because that analysis hasn't been fully wired into LoopSimplify/LCSSA, and it isn't clear that those transforms want to support those forms anyways. They all run late anyways, so this is harmless. Similarly, LSR is left alone because it already carefully manages its forms and doesn't need to get fused into a single loop pass manager with a bunch of other loop passes. LoopReroll didn't use loop simplified form previously, and I've updated the test case to match the trivially different output. Finally, I've also factored all the pass initialization for the passes that use this technique as well, so that should be done regularly and reliably. Thanks to James for the help reviewing and thinking about this stuff, and Ben for help thinking about it as well! Differential Revision: http://reviews.llvm.org/D17435 llvm-svn: 261316
2016-02-19 11:45:18 +01:00
// FIXME: Loop passes are required to preserve domtree, and for now we just
// recreate dom info if anything gets unrolled.
getLoopAnalysisUsage(AU);
}
};
}
char LoopUnroll::ID = 0;
INITIALIZE_PASS_BEGIN(LoopUnroll, "loop-unroll", "Unroll loops", false, false)
INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)
[LPM] Factor all of the loop analysis usage updates into a common helper routine. We were getting this wrong in small ways and generally being very inconsistent about it across loop passes. Instead, let's have a common place where we do this. One minor downside is that this will require some analyses like SCEV in more places than they are strictly needed. However, this seems benign as these analyses are complete no-ops, and without this consistency we can in many cases end up with the legacy pass manager scheduling deciding to split up a loop pass pipeline in order to run the function analysis half-way through. It is very, very annoying to fix these without just being very pedantic across the board. The only loop passes I've not updated here are ones that use AU.setPreservesAll() such as IVUsers (an analysis) and the pass printer. They seemed less relevant. With this patch, almost all of the problems in PR24804 around loop pass pipelines are fixed. The one remaining issue is that we run simplify-cfg and instcombine in the middle of the loop pass pipeline. We've recently added some loop variants of these passes that would seem substantially cleaner to use, but this at least gets us much closer to the previous state. Notably, the seven loop pass managers is down to three. I've not updated the loop passes using LoopAccessAnalysis because that analysis hasn't been fully wired into LoopSimplify/LCSSA, and it isn't clear that those transforms want to support those forms anyways. They all run late anyways, so this is harmless. Similarly, LSR is left alone because it already carefully manages its forms and doesn't need to get fused into a single loop pass manager with a bunch of other loop passes. LoopReroll didn't use loop simplified form previously, and I've updated the test case to match the trivially different output. Finally, I've also factored all the pass initialization for the passes that use this technique as well, so that should be done regularly and reliably. Thanks to James for the help reviewing and thinking about this stuff, and Ben for help thinking about it as well! Differential Revision: http://reviews.llvm.org/D17435 llvm-svn: 261316
2016-02-19 11:45:18 +01:00
INITIALIZE_PASS_DEPENDENCY(LoopPass)
INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass)
INITIALIZE_PASS_END(LoopUnroll, "loop-unroll", "Unroll loops", false, false)
Pass *llvm::createLoopUnrollPass(int Threshold, int Count, int AllowPartial,
int Runtime) {
// TODO: It would make more sense for this function to take the optionals
// directly, but that's dangerous since it would silently break out of tree
// callers.
return new LoopUnroll(Threshold == -1 ? None : Optional<unsigned>(Threshold),
Count == -1 ? None : Optional<unsigned>(Count),
AllowPartial == -1 ? None
: Optional<bool>(AllowPartial),
Runtime == -1 ? None : Optional<bool>(Runtime));
}
Pass *llvm::createSimpleLoopUnrollPass() {
return llvm::createLoopUnrollPass(-1, -1, 0, 0);
}
PreservedAnalyses LoopUnrollPass::run(Loop &L, AnalysisManager<Loop> &AM) {
const auto &FAM =
AM.getResult<FunctionAnalysisManagerLoopProxy>(L).getManager();
Function *F = L.getHeader()->getParent();
DominatorTree *DT = FAM.getCachedResult<DominatorTreeAnalysis>(*F);
LoopInfo *LI = FAM.getCachedResult<LoopAnalysis>(*F);
ScalarEvolution *SE = FAM.getCachedResult<ScalarEvolutionAnalysis>(*F);
auto *TTI = FAM.getCachedResult<TargetIRAnalysis>(*F);
auto *AC = FAM.getCachedResult<AssumptionAnalysis>(*F);
auto *ORE = FAM.getCachedResult<OptimizationRemarkEmitterAnalysis>(*F);
if (!DT)
report_fatal_error("LoopUnrollPass: DominatorTreeAnalysis not cached at a higher level");
if (!LI)
report_fatal_error("LoopUnrollPass: LoopAnalysis not cached at a higher level");
if (!SE)
report_fatal_error("LoopUnrollPass: ScalarEvolutionAnalysis not cached at a higher level");
if (!TTI)
report_fatal_error("LoopUnrollPass: TargetIRAnalysis not cached at a higher level");
if (!AC)
report_fatal_error("LoopUnrollPass: AssumptionAnalysis not cached at a higher level");
if (!ORE)
report_fatal_error("LoopUnrollPass: OptimizationRemarkEmitterAnalysis not "
"cached at a higher level");
bool Changed = tryToUnrollLoop(
&L, *DT, LI, SE, *TTI, *AC, *ORE, /*PreserveLCSSA*/ true, ProvidedCount,
ProvidedThreshold, ProvidedAllowPartial, ProvidedRuntime);
if (!Changed)
return PreservedAnalyses::all();
return getLoopPassPreservedAnalyses();
}