//===----------------------------------------------------------------------===//
#include "Clustering.h"
-#include "llvm/ADT/SetVector.h"
#include "llvm/ADT/SmallVector.h"
#include <string>
}
void InstructionBenchmarkClustering::dbScan(const size_t MinPts) {
- std::vector<size_t> Neighbors; // Persistent buffer to avoid allocs.
- for (size_t P = 0, NumPoints = Points_.size(); P < NumPoints; ++P) {
+ const size_t NumPoints = Points_.size();
+
+ // Persistent buffers to avoid allocs.
+ std::vector<size_t> Neighbors;
+ std::vector<size_t> ToProcess(NumPoints);
+ std::vector<char> Processed(NumPoints);
+
+ for (size_t P = 0; P < NumPoints; ++P) {
if (!ClusterIdForPoint_[P].isUndef())
continue; // Previously processed in inner loop.
rangeQuery(P, Neighbors);
Cluster &CurrentCluster = Clusters_.back();
ClusterIdForPoint_[P] = CurrentCluster.Id; /* Label initial point */
CurrentCluster.PointIndices.push_back(P);
+ Processed[P] = 1;
- // Process P's neighbors.
- llvm::SetVector<size_t, std::deque<size_t>> ToProcess;
- ToProcess.insert(Neighbors.begin(), Neighbors.end());
- while (!ToProcess.empty()) {
- // Retrieve a point from the set.
- const size_t Q = *ToProcess.begin();
- ToProcess.erase(ToProcess.begin());
-
- if (ClusterIdForPoint_[Q].isNoise()) {
- // Change noise point to border point.
- ClusterIdForPoint_[Q] = CurrentCluster.Id;
- CurrentCluster.PointIndices.push_back(Q);
+ // Enqueue P's neighbors.
+ size_t Tail = 0;
+ auto EnqueueUnprocessed = [&](const std::vector<size_t> &Neighbors) {
+ for (size_t Q : Neighbors)
+ if (!Processed[Q]) {
+ ToProcess[Tail++] = Q;
+ Processed[Q] = 1;
+ }
+ };
+ EnqueueUnprocessed(Neighbors);
+
+ for (size_t Head = 0; Head < Tail; ++Head) {
+ // Retrieve a point from the queue and add it to the current cluster.
+ P = ToProcess[Head];
+ ClusterId OldCID = ClusterIdForPoint_[P];
+ ClusterIdForPoint_[P] = CurrentCluster.Id;
+ CurrentCluster.PointIndices.push_back(P);
+ if (OldCID.isNoise())
continue;
- }
- if (!ClusterIdForPoint_[Q].isUndef()) {
- continue; // Previously processed.
- }
- // Add Q to the current custer.
- ClusterIdForPoint_[Q] = CurrentCluster.Id;
- CurrentCluster.PointIndices.push_back(Q);
- // And extend to the neighbors of Q if the region is dense enough.
- rangeQuery(Q, Neighbors);
- if (Neighbors.size() + 1 >= MinPts) {
- ToProcess.insert(Neighbors.begin(), Neighbors.end());
- }
+ assert(OldCID.isUndef());
+
+ // And extend to the neighbors of P if the region is dense enough.
+ rangeQuery(P, Neighbors);
+ if (Neighbors.size() + 1 >= MinPts)
+ EnqueueUnprocessed(Neighbors);
}
}
- // assert(Neighbors.capacity() == (Points_.size() - 1));
- // ^ True, but it is not quaranteed to be true in all the cases.
// Add noisy points to noise cluster.
- for (size_t P = 0, NumPoints = Points_.size(); P < NumPoints; ++P) {
- if (ClusterIdForPoint_[P].isNoise()) {
+ for (size_t P = 0; P < NumPoints; ++P)
+ if (ClusterIdForPoint_[P].isNoise())
NoiseCluster_.PointIndices.push_back(P);
- }
- }
}
llvm::Expected<InstructionBenchmarkClustering>