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#include "../../hnswlib/hnswlib.h"
#include <thread>
#include <chrono>
template<class Function>
inline void ParallelFor(size_t start, size_t end, size_t numThreads, Function fn) {
if (numThreads <= 0) {
numThreads = std::thread::hardware_concurrency();
}
if (numThreads == 1) {
for (size_t id = start; id < end; id++) {
fn(id, 0);
}
} else {
std::vector<std::thread> threads;
std::atomic<size_t> current(start);
// keep track of exceptions in threads
// https://stackoverflow.com/a/32428427/1713196
std::exception_ptr lastException = nullptr;
std::mutex lastExceptMutex;
for (size_t threadId = 0; threadId < numThreads; ++threadId) {
threads.push_back(std::thread([&, threadId] {
while (true) {
size_t id = current.fetch_add(1);
if (id >= end) {
break;
}
try {
fn(id, threadId);
} catch (...) {
std::unique_lock<std::mutex> lastExcepLock(lastExceptMutex);
lastException = std::current_exception();
/*
* This will work even when current is the largest value that
* size_t can fit, because fetch_add returns the previous value
* before the increment (what will result in overflow
* and produce 0 instead of current + 1).
*/
current = end;
break;
}
}
}));
}
for (auto &thread : threads) {
thread.join();
}
if (lastException) {
std::rethrow_exception(lastException);
}
}
}
int main() {
std::cout << "Running multithread load test" << std::endl;
int d = 16;
int num_elements = 1000;
int max_elements = 2 * num_elements;
int num_threads = 50;
std::mt19937 rng;
rng.seed(47);
std::uniform_real_distribution<> distrib_real;
hnswlib::L2Space space(d);
// generate batch1 and batch2 data
float* batch1 = new float[d * max_elements];
for (int i = 0; i < d * max_elements; i++) {
batch1[i] = distrib_real(rng);
}
float* batch2 = new float[d * num_elements];
for (int i = 0; i < d * num_elements; i++) {
batch2[i] = distrib_real(rng);
}
// generate random labels to delete them from index
std::vector<int> rand_labels(max_elements);
for (int i = 0; i < max_elements; i++) {
rand_labels[i] = i;
}
std::shuffle(rand_labels.begin(), rand_labels.end(), rng);
int iter = 0;
while (iter < 200) {
hnswlib::HierarchicalNSW<float>* alg_hnsw = new hnswlib::HierarchicalNSW<float>(&space, max_elements, 16, 200, 123, true);
// add batch1 data
ParallelFor(0, max_elements, num_threads, [&](size_t row, size_t threadId) {
alg_hnsw->addPoint((void*)(batch1 + d * row), row);
});
// delete half random elements of batch1 data
for (int i = 0; i < num_elements; i++) {
alg_hnsw->markDelete(rand_labels[i]);
}
// replace deleted elements with batch2 data
ParallelFor(0, num_elements, num_threads, [&](size_t row, size_t threadId) {
int label = rand_labels[row] + max_elements;
alg_hnsw->addPoint((void*)(batch2 + d * row), label, true);
});
iter += 1;
delete alg_hnsw;
}
std::cout << "Finish" << std::endl;
delete[] batch1;
delete[] batch2;
return 0;
}
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