[llvm-exegesis] Add an analysis mode.

Summary:
The analysis mode gives the user a clustered view of the measurement results.
Next steps are (requires the split ok AsmTemplate.Name into {mnemonic, mode}):
 - Show the sched class.
 - Highlight any inconsistencies with the checked-in data.

Reviewers: gchatelet

Subscribers: mgorny, llvm-commits, tschuett

Differential Revision: https://reviews.llvm.org/D46865

llvm-svn: 332344
This commit is contained in:
Clement Courbet 2018-05-15 12:08:00 +00:00
parent c0e7687557
commit be6ab91eb0
6 changed files with 209 additions and 40 deletions

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@ -0,0 +1,84 @@
//===-- Analysis.cpp --------------------------------------------*- C++ -*-===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
#include "BenchmarkResult.h"
#include "Analysis.h"
#include "llvm/Support/FormatVariadic.h"
#include <vector>
namespace exegesis {
static const char kCsvSep = ',';
static void writeCsvEscaped(llvm::raw_ostream& OS, const std::string& S) {
if (std::find(S.begin(), S.end(), kCsvSep) == S.end()) {
OS << S;
} else {
// Needs escaping.
OS << '"';
for (const char C : S) {
if (C == '"')
OS << "\"\"";
else
OS << C;
}
OS << '"';
}
}
// Prints a row representing an instruction, along with scheduling info and
// point coordinates (measurements).
static void printInstructionRow(const InstructionBenchmark &Point,
const llvm::MCSubtargetInfo &STI,
const size_t ClusterId, llvm::raw_ostream &OS) {
OS << ClusterId << kCsvSep;
writeCsvEscaped(OS, Point.AsmTmpl.Name);
// FIXME: Print the sched class once InstructionBenchmark separates key into
// (mnemonic, mode, opaque).
for (const auto &Measurement : Point.Measurements) {
OS << kCsvSep;
writeCsvEscaped(OS, llvm::formatv("{0:F}", Measurement.Value));
}
OS << "\n";
}
static void printCluster(const std::vector<InstructionBenchmark> &Points,
const llvm::MCSubtargetInfo &STI, const size_t ClusterId,
const InstructionBenchmarkClustering::Cluster &Cluster,
llvm::raw_ostream &OS) {
// Print all points.
for (const auto &PointId : Cluster.PointIndices) {
printInstructionRow(Points[PointId], STI, ClusterId, OS);
}
}
llvm::Error
printAnalysisClusters(const InstructionBenchmarkClustering &Clustering,
const llvm::MCSubtargetInfo &STI, llvm::raw_ostream &OS) {
if (Clustering.getPoints().empty())
return llvm::Error::success();
// Write the header.
OS << "cluster_id;key,sched_class";
for (const auto &Measurement : Clustering.getPoints().front().Measurements) {
OS << kCsvSep;
writeCsvEscaped(OS, Measurement.Key);
}
OS << "\n";
// Write the points.
for (size_t I = 0, E = Clustering.getValidClusters().size(); I < E; ++I) {
printCluster(Clustering.getPoints(), STI, I,
Clustering.getValidClusters()[I], OS);
OS << "\n\n";
}
return llvm::Error::success();
}
} // namespace exegesis

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@ -0,0 +1,32 @@
//===-- Analysis.h ----------------------------------------------*- C++ -*-===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
///
/// \file
/// Analysis output for benchmark results.
///
//===----------------------------------------------------------------------===//
#ifndef LLVM_TOOLS_LLVM_EXEGESIS_ANALYSIS_H
#define LLVM_TOOLS_LLVM_EXEGESIS_ANALYSIS_H
#include "Clustering.h"
#include "llvm/MC/MCSubtargetInfo.h"
#include "llvm/Support/Error.h"
#include "llvm/Support/raw_ostream.h"
namespace exegesis {
// Prints a csv of instructions for each cluster.
llvm::Error
printAnalysisClusters(const InstructionBenchmarkClustering &Clustering,
const llvm::MCSubtargetInfo &STI, llvm::raw_ostream &OS);
} // namespace exegesis
#endif // LLVM_TOOLS_LLVM_EXEGESIS_CLUSTERING_H

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@ -1,5 +1,6 @@
add_library(LLVMExegesis
STATIC
Analysis.cpp
BenchmarkResult.cpp
BenchmarkRunner.cpp
Clustering.cpp

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@ -57,17 +57,18 @@ std::vector<size_t> rangeQuery(const std::vector<InstructionBenchmark> &Points,
} // namespace
InstructionBenchmarkClustering::InstructionBenchmarkClustering()
: NoiseCluster_(ClusterId::noise()), ErrorCluster_(ClusterId::error()) {}
InstructionBenchmarkClustering::InstructionBenchmarkClustering(
const std::vector<InstructionBenchmark> &Points)
: Points_(Points), NoiseCluster_(ClusterId::noise()),
ErrorCluster_(ClusterId::error()) {}
llvm::Error InstructionBenchmarkClustering::validateAndSetup(
const std::vector<InstructionBenchmark> &Points) {
ClusterIdForPoint_.resize(Points.size());
llvm::Error InstructionBenchmarkClustering::validateAndSetup() {
ClusterIdForPoint_.resize(Points_.size());
// Mark erroneous measurements out.
// All points must have the same number of dimensions, in the same order.
const std::vector<BenchmarkMeasure> *LastMeasurement = nullptr;
for (size_t P = 0, NumPoints = Points.size(); P < NumPoints; ++P) {
const auto &Point = Points[P];
for (size_t P = 0, NumPoints = Points_.size(); P < NumPoints; ++P) {
const auto &Point = Points_[P];
if (!Point.Error.empty()) {
ClusterIdForPoint_[P] = ClusterId::error();
ErrorCluster_.PointIndices.push_back(P);
@ -96,13 +97,12 @@ llvm::Error InstructionBenchmarkClustering::validateAndSetup(
return llvm::Error::success();
}
void InstructionBenchmarkClustering::dbScan(
const std::vector<InstructionBenchmark> &Points, const size_t MinPts,
const double EpsilonSquared) {
for (size_t P = 0, NumPoints = Points.size(); P < NumPoints; ++P) {
void InstructionBenchmarkClustering::dbScan(const size_t MinPts,
const double EpsilonSquared) {
for (size_t P = 0, NumPoints = Points_.size(); P < NumPoints; ++P) {
if (!ClusterIdForPoint_[P].isUndef())
continue; // Previously processed in inner loop.
const auto Neighbors = rangeQuery(Points, P, EpsilonSquared);
const auto Neighbors = rangeQuery(Points_, P, EpsilonSquared);
if (Neighbors.size() + 1 < MinPts) { // Density check.
// The region around P is not dense enough to create a new cluster, mark
// as noise for now.
@ -136,7 +136,7 @@ void InstructionBenchmarkClustering::dbScan(
ClusterIdForPoint_[Q] = CurrentCluster.Id;
CurrentCluster.PointIndices.push_back(Q);
// And extend to the neighbors of Q if the region is dense enough.
const auto Neighbors = rangeQuery(Points, Q, EpsilonSquared);
const auto Neighbors = rangeQuery(Points_, Q, EpsilonSquared);
if (Neighbors.size() + 1 >= MinPts) {
ToProcess.insert(Neighbors.begin(), Neighbors.end());
}
@ -144,7 +144,7 @@ void InstructionBenchmarkClustering::dbScan(
}
// Add noisy points to noise cluster.
for (size_t P = 0, NumPoints = Points.size(); P < NumPoints; ++P) {
for (size_t P = 0, NumPoints = Points_.size(); P < NumPoints; ++P) {
if (ClusterIdForPoint_[P].isNoise()) {
NoiseCluster_.PointIndices.push_back(P);
}
@ -155,15 +155,15 @@ llvm::Expected<InstructionBenchmarkClustering>
InstructionBenchmarkClustering::create(
const std::vector<InstructionBenchmark> &Points, const size_t MinPts,
const double Epsilon) {
InstructionBenchmarkClustering Clustering;
if (auto Error = Clustering.validateAndSetup(Points)) {
return std::move(Error);
InstructionBenchmarkClustering Clustering(Points);
if (auto Error = Clustering.validateAndSetup()) {
return Error;
}
if (Clustering.ErrorCluster_.PointIndices.size() == Points.size()) {
return Clustering; // Nothing to cluster.
}
Clustering.dbScan(Points, MinPts, Epsilon * Epsilon);
Clustering.dbScan(MinPts, Epsilon * Epsilon);
return Clustering;
}

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@ -72,6 +72,8 @@ public:
return ClusterIdForPoint_[P];
}
const std::vector<InstructionBenchmark> &getPoints() const { return Points_; }
const Cluster &getCluster(ClusterId Id) const {
assert(!Id.isUndef() && "unlabeled cluster");
if (Id.isNoise()) {
@ -86,10 +88,11 @@ public:
const std::vector<Cluster> &getValidClusters() const { return Clusters_; }
private:
InstructionBenchmarkClustering();
llvm::Error validateAndSetup(const std::vector<InstructionBenchmark> &Points);
void dbScan(const std::vector<InstructionBenchmark> &Points, size_t MinPts,
double EpsilonSquared);
InstructionBenchmarkClustering(
const std::vector<InstructionBenchmark> &Points);
llvm::Error validateAndSetup();
void dbScan(size_t MinPts, double EpsilonSquared);
const std::vector<InstructionBenchmark> &Points_;
int NumDimensions_ = 0;
// ClusterForPoint_[P] is the cluster id for Points[P].
std::vector<ClusterId> ClusterIdForPoint_;

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@ -12,8 +12,10 @@
///
//===----------------------------------------------------------------------===//
#include "lib/Analysis.h"
#include "lib/BenchmarkResult.h"
#include "lib/BenchmarkRunner.h"
#include "lib/Clustering.h"
#include "lib/Latency.h"
#include "lib/LlvmState.h"
#include "lib/PerfHelper.h"
@ -23,8 +25,11 @@
#include "llvm/ADT/Twine.h"
#include "llvm/MC/MCInstBuilder.h"
#include "llvm/MC/MCRegisterInfo.h"
#include "llvm/MC/MCSubtargetInfo.h"
#include "llvm/Support/CommandLine.h"
#include "llvm/Support/Format.h"
#include "llvm/Support/Path.h"
#include "llvm/Support/TargetRegistry.h"
#include "llvm/Support/TargetSelect.h"
#include <algorithm>
#include <random>
@ -39,26 +44,41 @@ static llvm::cl::opt<std::string>
OpcodeName("opcode-name", llvm::cl::desc("opcode to measure, by name"),
llvm::cl::init(""));
enum class BenchmarkModeE { Latency, Uops };
static llvm::cl::opt<BenchmarkModeE>
BenchmarkMode("benchmark-mode", llvm::cl::desc("the benchmark mode to run"),
llvm::cl::values(clEnumValN(BenchmarkModeE::Latency,
"latency", "Instruction Latency"),
clEnumValN(BenchmarkModeE::Uops, "uops",
"Uop Decomposition")));
static llvm::cl::opt<std::string>
BenchmarkFile("benchmarks-file", llvm::cl::desc(""), llvm::cl::init("-"));
enum class BenchmarkModeE { Latency, Uops, Analysis };
static llvm::cl::opt<BenchmarkModeE> BenchmarkMode(
"benchmark-mode", llvm::cl::desc("the benchmark mode to run"),
llvm::cl::values(
clEnumValN(BenchmarkModeE::Latency, "latency", "Instruction Latency"),
clEnumValN(BenchmarkModeE::Uops, "uops", "Uop Decomposition"),
clEnumValN(BenchmarkModeE::Analysis, "analysis", "Analysis")));
static llvm::cl::opt<unsigned>
NumRepetitions("num-repetitions",
llvm::cl::desc("number of time to repeat the asm snippet"),
llvm::cl::init(10000));
static llvm::cl::opt<unsigned> AnalysisNumPoints(
"analysis-numpoints",
llvm::cl::desc("minimum number of points in an analysis cluster"),
llvm::cl::init(3));
static llvm::cl::opt<float>
AnalysisEpsilon("analysis-epsilon",
llvm::cl::desc("dbscan epsilon for analysis clustering"),
llvm::cl::init(0.1));
namespace exegesis {
void main() {
if (OpcodeName.empty() == (OpcodeIndex == 0)) {
void benchmarkMain() {
if (exegesis::pfm::pfmInitialize())
llvm::report_fatal_error("cannot initialize libpfm");
if (OpcodeName.empty() == (OpcodeIndex == 0))
llvm::report_fatal_error(
"please provide one and only one of 'opcode-index' or 'opcode-name'");
}
llvm::InitializeNativeTarget();
llvm::InitializeNativeTargetAsmPrinter();
@ -94,10 +114,42 @@ void main() {
case BenchmarkModeE::Uops:
Runner = llvm::make_unique<UopsBenchmarkRunner>();
break;
case BenchmarkModeE::Analysis:
llvm_unreachable("not a benchmark");
}
Runner->run(State, Opcode, NumRepetitions > 0 ? NumRepetitions : 1, Filter)
.writeYamlOrDie("-");
.writeYamlOrDie(BenchmarkFile);
exegesis::pfm::pfmTerminate();
}
void analysisMain() {
// Read benchmarks.
const std::vector<InstructionBenchmark> Points =
InstructionBenchmark::readYamlsOrDie(BenchmarkFile);
llvm::outs() << "Parsed " << Points.size() << " benchmark points\n";
if (Points.empty()) {
llvm::errs() << "no benchmarks to analyze\n";
return;
}
// FIXME: Check that all points have the same triple/cpu.
// FIXME: Merge points from several runs (latency and uops).
llvm::InitializeAllTargets();
std::string Error;
const auto *TheTarget =
llvm::TargetRegistry::lookupTarget(Points[0].LLVMTriple, Error);
if (!TheTarget) {
llvm::errs() << "unknown target '" << Points[0].LLVMTriple << "'\n";
return;
}
std::unique_ptr<llvm::MCSubtargetInfo> STI(TheTarget->createMCSubtargetInfo(
Points[0].LLVMTriple, Points[0].CpuName, ""));
const auto Clustering = llvm::cantFail(InstructionBenchmarkClustering::create(
Points, AnalysisNumPoints, AnalysisEpsilon));
if (auto Err = printAnalysisClusters(Clustering, *STI, llvm::outs()))
llvm::report_fatal_error(std::move(Err));
}
} // namespace exegesis
@ -105,13 +157,10 @@ void main() {
int main(int Argc, char **Argv) {
llvm::cl::ParseCommandLineOptions(Argc, Argv, "");
if (exegesis::pfm::pfmInitialize()) {
llvm::errs() << "cannot initialize libpfm\n";
return EXIT_FAILURE;
if (BenchmarkMode == BenchmarkModeE::Analysis) {
exegesis::analysisMain();
} else {
exegesis::benchmarkMain();
}
exegesis::main();
exegesis::pfm::pfmTerminate();
return EXIT_SUCCESS;
}