forked from OSchip/llvm-project
[llvm-exegesis] InstructionBenchmarkClustering::rangeQuery(): write into llvm::SmallVectorImpl& output parameter
Summary: I do believe this is the correct fix. We call `rangeQuery()` *very* often. And many times it's output vector is large (tens of thousands entries), so small-size-opt won't help. Old: (D54389) ``` Performance counter stats for './bin/llvm-exegesis -mode=analysis -analysis-epsilon=100000 -benchmarks-file=/tmp/benchmarks.yaml -analysis-inconsistencies-output-file=/tmp/clusters.html' (10 runs): 7934.528363 task-clock (msec) # 1.000 CPUs utilized ( +- 0.19% ) ... 7.9354 +- 0.0148 seconds time elapsed ( +- 0.19% ) ``` New: ``` Performance counter stats for './bin/llvm-exegesis -mode=analysis -analysis-epsilon=100000 -benchmarks-file=/tmp/benchmarks.yaml -analysis-inconsistencies-output-file=/tmp/clusters.html' (10 runs): 7383.793440 task-clock (msec) # 1.000 CPUs utilized ( +- 0.47% ) ... 7.3868 +- 0.0340 seconds time elapsed ( +- 0.46% ) ``` And another -7%. And that isn't even the good bit yet. Old: * calls to allocation functions: 2081419 * temporary allocations: 219658 (10.55%) * bytes allocated in total (ignoring deallocations): 4.31 GB New: * calls to allocation functions: 1880295 (-10%) * temporary allocations: 18758 (1%) (-91% *sic*) * bytes allocated in total (ignoring deallocations): 545.15 MB (-88% *sic*) Reviewers: courbet, MaskRay, RKSimon, gchatelet, john.brawn Reviewed By: courbet, MaskRay Subscribers: tschuett, llvm-commits Differential Revision: https://reviews.llvm.org/D54390 llvm-svn: 347202
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@ -33,9 +33,9 @@ namespace exegesis {
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// Finds the points at distance less than sqrt(EpsilonSquared) of Q (not
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// including Q).
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llvm::SmallVector<size_t, 0>
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InstructionBenchmarkClustering::rangeQuery(const size_t Q) const {
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llvm::SmallVector<size_t, 0> Neighbors;
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void InstructionBenchmarkClustering::rangeQuery(
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const size_t Q, llvm::SmallVectorImpl<size_t> &Neighbors) const {
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Neighbors.clear();
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const auto &QMeasurements = Points_[Q].Measurements;
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for (size_t P = 0, NumPoints = Points_.size(); P < NumPoints; ++P) {
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if (P == Q)
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@ -47,7 +47,6 @@ InstructionBenchmarkClustering::rangeQuery(const size_t Q) const {
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Neighbors.push_back(P);
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}
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}
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return Neighbors;
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}
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bool InstructionBenchmarkClustering::isNeighbour(
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@ -103,10 +102,11 @@ llvm::Error InstructionBenchmarkClustering::validateAndSetup() {
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}
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void InstructionBenchmarkClustering::dbScan(const size_t MinPts) {
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llvm::SmallVector<size_t, 0> Neighbors; // Persistent buffer to avoid allocs.
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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(P);
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rangeQuery(P, Neighbors);
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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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@ -141,7 +141,7 @@ void InstructionBenchmarkClustering::dbScan(const size_t MinPts) {
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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(Q);
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rangeQuery(Q, Neighbors);
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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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@ -97,7 +97,7 @@ private:
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const std::vector<InstructionBenchmark> &Points, double EpsilonSquared);
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llvm::Error validateAndSetup();
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void dbScan(size_t MinPts);
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llvm::SmallVector<size_t, 0> rangeQuery(size_t Q) const;
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void rangeQuery(size_t Q, llvm::SmallVectorImpl<size_t> &Scratchpad) const;
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const std::vector<InstructionBenchmark> &Points_;
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const double EpsilonSquared_;
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