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[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
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84
tools/llvm-exegesis/lib/Analysis.cpp
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84
tools/llvm-exegesis/lib/Analysis.cpp
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//===-- Analysis.cpp --------------------------------------------*- C++ -*-===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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#include "BenchmarkResult.h"
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#include "Analysis.h"
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#include "llvm/Support/FormatVariadic.h"
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#include <vector>
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namespace exegesis {
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static const char kCsvSep = ',';
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static void writeCsvEscaped(llvm::raw_ostream& OS, const std::string& S) {
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if (std::find(S.begin(), S.end(), kCsvSep) == S.end()) {
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OS << S;
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} else {
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// Needs escaping.
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OS << '"';
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for (const char C : S) {
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if (C == '"')
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OS << "\"\"";
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else
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OS << C;
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}
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OS << '"';
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}
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}
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// Prints a row representing an instruction, along with scheduling info and
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// point coordinates (measurements).
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static void printInstructionRow(const InstructionBenchmark &Point,
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const llvm::MCSubtargetInfo &STI,
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const size_t ClusterId, llvm::raw_ostream &OS) {
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OS << ClusterId << kCsvSep;
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writeCsvEscaped(OS, Point.AsmTmpl.Name);
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// FIXME: Print the sched class once InstructionBenchmark separates key into
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// (mnemonic, mode, opaque).
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for (const auto &Measurement : Point.Measurements) {
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OS << kCsvSep;
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writeCsvEscaped(OS, llvm::formatv("{0:F}", Measurement.Value));
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}
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OS << "\n";
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}
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static void printCluster(const std::vector<InstructionBenchmark> &Points,
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const llvm::MCSubtargetInfo &STI, const size_t ClusterId,
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const InstructionBenchmarkClustering::Cluster &Cluster,
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llvm::raw_ostream &OS) {
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// Print all points.
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for (const auto &PointId : Cluster.PointIndices) {
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printInstructionRow(Points[PointId], STI, ClusterId, OS);
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}
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}
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llvm::Error
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printAnalysisClusters(const InstructionBenchmarkClustering &Clustering,
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const llvm::MCSubtargetInfo &STI, llvm::raw_ostream &OS) {
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if (Clustering.getPoints().empty())
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return llvm::Error::success();
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// Write the header.
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OS << "cluster_id;key,sched_class";
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for (const auto &Measurement : Clustering.getPoints().front().Measurements) {
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OS << kCsvSep;
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writeCsvEscaped(OS, Measurement.Key);
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}
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OS << "\n";
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// Write the points.
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for (size_t I = 0, E = Clustering.getValidClusters().size(); I < E; ++I) {
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printCluster(Clustering.getPoints(), STI, I,
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Clustering.getValidClusters()[I], OS);
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OS << "\n\n";
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}
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return llvm::Error::success();
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}
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} // namespace exegesis
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32
tools/llvm-exegesis/lib/Analysis.h
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32
tools/llvm-exegesis/lib/Analysis.h
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//===-- Analysis.h ----------------------------------------------*- C++ -*-===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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///
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/// \file
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/// Analysis output for benchmark results.
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///
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//===----------------------------------------------------------------------===//
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#ifndef LLVM_TOOLS_LLVM_EXEGESIS_ANALYSIS_H
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#define LLVM_TOOLS_LLVM_EXEGESIS_ANALYSIS_H
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#include "Clustering.h"
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#include "llvm/MC/MCSubtargetInfo.h"
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#include "llvm/Support/Error.h"
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#include "llvm/Support/raw_ostream.h"
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namespace exegesis {
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// Prints a csv of instructions for each cluster.
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llvm::Error
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printAnalysisClusters(const InstructionBenchmarkClustering &Clustering,
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const llvm::MCSubtargetInfo &STI, llvm::raw_ostream &OS);
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} // namespace exegesis
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#endif // LLVM_TOOLS_LLVM_EXEGESIS_CLUSTERING_H
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@ -1,5 +1,6 @@
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add_library(LLVMExegesis
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STATIC
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Analysis.cpp
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BenchmarkResult.cpp
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BenchmarkRunner.cpp
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Clustering.cpp
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@ -57,17 +57,18 @@ std::vector<size_t> rangeQuery(const std::vector<InstructionBenchmark> &Points,
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} // namespace
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InstructionBenchmarkClustering::InstructionBenchmarkClustering()
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: NoiseCluster_(ClusterId::noise()), ErrorCluster_(ClusterId::error()) {}
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InstructionBenchmarkClustering::InstructionBenchmarkClustering(
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const std::vector<InstructionBenchmark> &Points)
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: Points_(Points), NoiseCluster_(ClusterId::noise()),
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ErrorCluster_(ClusterId::error()) {}
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llvm::Error InstructionBenchmarkClustering::validateAndSetup(
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const std::vector<InstructionBenchmark> &Points) {
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ClusterIdForPoint_.resize(Points.size());
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llvm::Error InstructionBenchmarkClustering::validateAndSetup() {
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ClusterIdForPoint_.resize(Points_.size());
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// Mark erroneous measurements out.
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// All points must have the same number of dimensions, in the same order.
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const std::vector<BenchmarkMeasure> *LastMeasurement = nullptr;
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for (size_t P = 0, NumPoints = Points.size(); P < NumPoints; ++P) {
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const auto &Point = Points[P];
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for (size_t P = 0, NumPoints = Points_.size(); P < NumPoints; ++P) {
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const auto &Point = Points_[P];
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if (!Point.Error.empty()) {
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ClusterIdForPoint_[P] = ClusterId::error();
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ErrorCluster_.PointIndices.push_back(P);
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@ -96,13 +97,12 @@ llvm::Error InstructionBenchmarkClustering::validateAndSetup(
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return llvm::Error::success();
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}
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void InstructionBenchmarkClustering::dbScan(
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const std::vector<InstructionBenchmark> &Points, const size_t MinPts,
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const double EpsilonSquared) {
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for (size_t P = 0, NumPoints = Points.size(); P < NumPoints; ++P) {
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void InstructionBenchmarkClustering::dbScan(const size_t MinPts,
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const double EpsilonSquared) {
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for (size_t P = 0, NumPoints = Points_.size(); P < NumPoints; ++P) {
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if (!ClusterIdForPoint_[P].isUndef())
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continue; // Previously processed in inner loop.
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const auto Neighbors = rangeQuery(Points, P, EpsilonSquared);
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const auto Neighbors = rangeQuery(Points_, P, EpsilonSquared);
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if (Neighbors.size() + 1 < MinPts) { // Density check.
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// The region around P is not dense enough to create a new cluster, mark
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// as noise for now.
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@ -136,7 +136,7 @@ void InstructionBenchmarkClustering::dbScan(
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ClusterIdForPoint_[Q] = CurrentCluster.Id;
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CurrentCluster.PointIndices.push_back(Q);
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// And extend to the neighbors of Q if the region is dense enough.
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const auto Neighbors = rangeQuery(Points, Q, EpsilonSquared);
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const auto Neighbors = rangeQuery(Points_, Q, EpsilonSquared);
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if (Neighbors.size() + 1 >= MinPts) {
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ToProcess.insert(Neighbors.begin(), Neighbors.end());
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}
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@ -144,7 +144,7 @@ void InstructionBenchmarkClustering::dbScan(
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}
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// Add noisy points to noise cluster.
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for (size_t P = 0, NumPoints = Points.size(); P < NumPoints; ++P) {
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for (size_t P = 0, NumPoints = Points_.size(); P < NumPoints; ++P) {
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if (ClusterIdForPoint_[P].isNoise()) {
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NoiseCluster_.PointIndices.push_back(P);
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}
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@ -155,15 +155,15 @@ llvm::Expected<InstructionBenchmarkClustering>
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InstructionBenchmarkClustering::create(
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const std::vector<InstructionBenchmark> &Points, const size_t MinPts,
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const double Epsilon) {
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InstructionBenchmarkClustering Clustering;
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if (auto Error = Clustering.validateAndSetup(Points)) {
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return std::move(Error);
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InstructionBenchmarkClustering Clustering(Points);
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if (auto Error = Clustering.validateAndSetup()) {
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return Error;
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}
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if (Clustering.ErrorCluster_.PointIndices.size() == Points.size()) {
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return Clustering; // Nothing to cluster.
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}
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Clustering.dbScan(Points, MinPts, Epsilon * Epsilon);
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Clustering.dbScan(MinPts, Epsilon * Epsilon);
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return Clustering;
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}
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return ClusterIdForPoint_[P];
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}
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const std::vector<InstructionBenchmark> &getPoints() const { return Points_; }
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const Cluster &getCluster(ClusterId Id) const {
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assert(!Id.isUndef() && "unlabeled cluster");
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if (Id.isNoise()) {
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@ -86,10 +88,11 @@ public:
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const std::vector<Cluster> &getValidClusters() const { return Clusters_; }
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private:
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InstructionBenchmarkClustering();
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llvm::Error validateAndSetup(const std::vector<InstructionBenchmark> &Points);
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void dbScan(const std::vector<InstructionBenchmark> &Points, size_t MinPts,
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double EpsilonSquared);
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InstructionBenchmarkClustering(
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const std::vector<InstructionBenchmark> &Points);
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llvm::Error validateAndSetup();
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void dbScan(size_t MinPts, double EpsilonSquared);
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const std::vector<InstructionBenchmark> &Points_;
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int NumDimensions_ = 0;
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// ClusterForPoint_[P] is the cluster id for Points[P].
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std::vector<ClusterId> ClusterIdForPoint_;
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///
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//===----------------------------------------------------------------------===//
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#include "lib/Analysis.h"
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#include "lib/BenchmarkResult.h"
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#include "lib/BenchmarkRunner.h"
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#include "lib/Clustering.h"
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#include "lib/Latency.h"
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#include "lib/LlvmState.h"
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#include "lib/PerfHelper.h"
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#include "llvm/ADT/Twine.h"
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#include "llvm/MC/MCInstBuilder.h"
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#include "llvm/MC/MCRegisterInfo.h"
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#include "llvm/MC/MCSubtargetInfo.h"
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#include "llvm/Support/CommandLine.h"
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#include "llvm/Support/Format.h"
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#include "llvm/Support/Path.h"
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#include "llvm/Support/TargetRegistry.h"
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#include "llvm/Support/TargetSelect.h"
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#include <algorithm>
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#include <random>
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OpcodeName("opcode-name", llvm::cl::desc("opcode to measure, by name"),
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llvm::cl::init(""));
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enum class BenchmarkModeE { Latency, Uops };
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static llvm::cl::opt<BenchmarkModeE>
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BenchmarkMode("benchmark-mode", llvm::cl::desc("the benchmark mode to run"),
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llvm::cl::values(clEnumValN(BenchmarkModeE::Latency,
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"latency", "Instruction Latency"),
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clEnumValN(BenchmarkModeE::Uops, "uops",
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"Uop Decomposition")));
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static llvm::cl::opt<std::string>
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BenchmarkFile("benchmarks-file", llvm::cl::desc(""), llvm::cl::init("-"));
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enum class BenchmarkModeE { Latency, Uops, Analysis };
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static llvm::cl::opt<BenchmarkModeE> BenchmarkMode(
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"benchmark-mode", llvm::cl::desc("the benchmark mode to run"),
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llvm::cl::values(
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clEnumValN(BenchmarkModeE::Latency, "latency", "Instruction Latency"),
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clEnumValN(BenchmarkModeE::Uops, "uops", "Uop Decomposition"),
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clEnumValN(BenchmarkModeE::Analysis, "analysis", "Analysis")));
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static llvm::cl::opt<unsigned>
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NumRepetitions("num-repetitions",
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llvm::cl::desc("number of time to repeat the asm snippet"),
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llvm::cl::init(10000));
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static llvm::cl::opt<unsigned> AnalysisNumPoints(
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"analysis-numpoints",
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llvm::cl::desc("minimum number of points in an analysis cluster"),
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llvm::cl::init(3));
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static llvm::cl::opt<float>
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AnalysisEpsilon("analysis-epsilon",
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llvm::cl::desc("dbscan epsilon for analysis clustering"),
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llvm::cl::init(0.1));
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namespace exegesis {
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void main() {
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if (OpcodeName.empty() == (OpcodeIndex == 0)) {
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void benchmarkMain() {
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if (exegesis::pfm::pfmInitialize())
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llvm::report_fatal_error("cannot initialize libpfm");
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if (OpcodeName.empty() == (OpcodeIndex == 0))
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llvm::report_fatal_error(
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"please provide one and only one of 'opcode-index' or 'opcode-name'");
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}
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llvm::InitializeNativeTarget();
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llvm::InitializeNativeTargetAsmPrinter();
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case BenchmarkModeE::Uops:
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Runner = llvm::make_unique<UopsBenchmarkRunner>();
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break;
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case BenchmarkModeE::Analysis:
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llvm_unreachable("not a benchmark");
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}
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Runner->run(State, Opcode, NumRepetitions > 0 ? NumRepetitions : 1, Filter)
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.writeYamlOrDie("-");
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.writeYamlOrDie(BenchmarkFile);
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exegesis::pfm::pfmTerminate();
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}
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void analysisMain() {
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// Read benchmarks.
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const std::vector<InstructionBenchmark> Points =
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InstructionBenchmark::readYamlsOrDie(BenchmarkFile);
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llvm::outs() << "Parsed " << Points.size() << " benchmark points\n";
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if (Points.empty()) {
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llvm::errs() << "no benchmarks to analyze\n";
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return;
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}
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// FIXME: Check that all points have the same triple/cpu.
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// FIXME: Merge points from several runs (latency and uops).
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llvm::InitializeAllTargets();
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std::string Error;
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const auto *TheTarget =
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llvm::TargetRegistry::lookupTarget(Points[0].LLVMTriple, Error);
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if (!TheTarget) {
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llvm::errs() << "unknown target '" << Points[0].LLVMTriple << "'\n";
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return;
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}
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std::unique_ptr<llvm::MCSubtargetInfo> STI(TheTarget->createMCSubtargetInfo(
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Points[0].LLVMTriple, Points[0].CpuName, ""));
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const auto Clustering = llvm::cantFail(InstructionBenchmarkClustering::create(
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Points, AnalysisNumPoints, AnalysisEpsilon));
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if (auto Err = printAnalysisClusters(Clustering, *STI, llvm::outs()))
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llvm::report_fatal_error(std::move(Err));
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}
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} // namespace exegesis
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@ -105,13 +157,10 @@ void main() {
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int main(int Argc, char **Argv) {
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llvm::cl::ParseCommandLineOptions(Argc, Argv, "");
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if (exegesis::pfm::pfmInitialize()) {
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llvm::errs() << "cannot initialize libpfm\n";
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return EXIT_FAILURE;
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if (BenchmarkMode == BenchmarkModeE::Analysis) {
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exegesis::analysisMain();
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} else {
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exegesis::benchmarkMain();
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}
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exegesis::main();
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exegesis::pfm::pfmTerminate();
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return EXIT_SUCCESS;
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}
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