Add interesting benchmark by @samuelpmish

CMakeLists.txt

@@ -198,6 +198,7 @@ if (PHMAP_BUILD_EXAMPLES)
     add_executable(ex_hash_bench examples/hash_bench.cc phmap.natvis)
     add_executable(ex_matt examples/matt.cc phmap.natvis)
     add_executable(ex_mt_word_counter examples/mt_word_counter.cc phmap.natvis)
+    add_executable(ex_p_bench examples/p_bench.cc phmap.natvis)
 
     target_link_libraries(ex_knucleotide Threads::Threads)
     target_link_libraries(ex_bench Threads::Threads)

examples/p_bench.cc

@@ -0,0 +1,189 @@
+// example graciously provided @samuelpmish
+// ----------------------------------------
+//
+// Getting rid of the mutexes for read access
+//
+// This example demonstrated how to populate a parallel_flat_hash_map from multiple
+// concurrent threads (The map is protected by internal mutexes), but then doing a
+// swap to get rid of the mutexes (and all locking) for accessing the same hash_map
+// in `read` only mode, again concurrently from multiple threads.
+// --------------------------------------------------------------------------------
+#include <random>
+#include <iostream>
+#include <unordered_map>
+#include <unordered_set>
+#include "parallel_hashmap/phmap.h"
+
+///////////////////////////////////////////////////////////////////////////////
+
+#include <chrono>
+
+class timer {
+    typedef std::chrono::high_resolution_clock::time_point time_point;
+    typedef std::chrono::duration<double>                  duration_type;
+
+public:
+    void   start()   { then = std::chrono::high_resolution_clock::now(); }
+    void   stop()    { now = std::chrono::high_resolution_clock::now(); }
+    double elapsed() { return std::chrono::duration_cast<duration_type>(now - then).count(); }
+
+private:
+    time_point then, now;
+};  
+
+///////////////////////////////////////////////////////////////////////////////
+
+#include <thread>
+
+struct threadpool {
+
+    std::vector< uint64_t > partition(uint64_t n) {
+        uint64_t quotient = n / num_threads;
+        uint64_t remainder = n % num_threads;
+
+        std::vector< uint64_t > blocks(num_threads + 1);
+        blocks[0] = 0;
+        for (int i = 1; i < num_threads + 1; i++) {
+            if (remainder > 0) {
+                blocks[i] = blocks[i-1] + quotient + 1;
+                remainder--;
+            } else {
+                blocks[i] = blocks[i-1] + quotient;
+            }
+        }
+        return blocks;
+    }
+
+    threadpool(int n) : num_threads(n) {}
+
+    template < typename lambda >
+    void parallel_for(uint64_t n, const lambda & f) {
+
+        std::vector< uint64_t > blocks = partition(n);
+
+        for (int tid = 0; tid < num_threads; tid++) {
+            threads.push_back(std::thread([&](uint64_t i0) {
+                for (uint64_t i = blocks[i0]; i < blocks[i0+1]; i++) {
+                    f(i);
+                }
+            }, tid));
+        }
+
+        for (int i = 0; i < num_threads; i++) {
+            threads[i].join();
+        }
+
+        threads.clear();
+    }
+
+    int num_threads;
+    std::vector< std::thread > threads;
+};
+
+///////////////////////////////////////////////////////////////////////////////
+
+template < int n >
+using pmap = phmap::parallel_flat_hash_map< 
+                uint64_t, 
+                uint64_t,
+                std::hash<uint64_t>,
+                std::equal_to<uint64_t>, 
+                std::allocator<std::pair<const uint64_t, uint64_t>>, 
+                n, 
+                std::mutex >;
+
+template < int n >
+using pmap_nullmutex = phmap::parallel_flat_hash_map< 
+                uint64_t, 
+                uint64_t,
+                std::hash<uint64_t>,
+                std::equal_to<uint64_t>, 
+                std::allocator<std::pair<const uint64_t, uint64_t>>, 
+                n, 
+                phmap::NullMutex >;
+
+
+
+template < typename Map, typename Map_nomutex >
+void renumber(const std::vector< uint64_t > & vertex_ids, 
+              std::vector< std::array< uint64_t, 4 > > elements,
+              int num_threads) {
+    bool supports_parallel_insertion = 
+        !std::is_same< Map, std::unordered_map<uint64_t, uint64_t> >::value;
+
+    Map new_ids;
+    std::atomic< uint64_t > new_id{ 0 };
+
+    timer stopwatch;
+    threadpool pool((supports_parallel_insertion) ? num_threads : 1);
+
+    stopwatch.start();
+    pool.parallel_for(vertex_ids.size(), [&](uint64_t i){
+        auto id = new_id++;
+        new_ids[vertex_ids[i]] = id;
+    });
+    stopwatch.stop();
+    std::cout << stopwatch.elapsed() * 1000 << "ms ";
+
+    pool.num_threads = num_threads;
+    stopwatch.start();
+    Map_nomutex new_ids_nc;
+    new_ids_nc.swap(new_ids);
+    pool.parallel_for(elements.size(), [&](uint64_t i) {
+        auto & elem = elements[i];
+        elem = {  new_ids_nc.at(elem[0]),
+                  new_ids_nc.at(elem[1]),
+                  new_ids_nc.at(elem[2]),
+                  new_ids_nc.at(elem[3]) };
+    });
+    stopwatch.stop();
+    std::cout << stopwatch.elapsed() * 1000 << "ms" << std::endl;
+}
+
+int main() {
+    uint64_t nvertices = 5000000;
+    uint64_t nelements = 25000000;
+
+    std::random_device rd;  // a seed source for the random number engine
+    std::mt19937 gen(rd()); // mersenne_twister_engine seeded with rd()
+    std::uniform_int_distribution<uint64_t> vertex_id_dist(0, uint64_t(1) << 35);
+    std::uniform_int_distribution<uint64_t> elem_id_dist(0, nvertices-1);
+
+    std::cout << "generating dataset ." << std::flush;
+    std::vector< uint64_t > vertex_ids(nvertices);
+    for (uint64_t i = 0; i < nvertices; i++) {
+        vertex_ids[i] = vertex_id_dist(gen);
+    }
+
+    std::cout << "." << std::flush;
+
+    std::vector< std::array<uint64_t, 4> > elements(nelements);
+    for (uint64_t i = 0; i < nelements; i++) {
+        elements[i] = {
+            vertex_ids[elem_id_dist(gen)], 
+            vertex_ids[elem_id_dist(gen)], 
+            vertex_ids[elem_id_dist(gen)], 
+            vertex_ids[elem_id_dist(gen)]
+        };
+    }
+    std::cout << " done" << std::endl;
+
+    using stdmap = std::unordered_map<uint64_t, uint64_t>;
+    std::cout << "std::unordered_map, 1 thread: ";
+    renumber< stdmap, stdmap >(vertex_ids, elements, 1);
+
+    std::cout << "std::unordered_map, 32 thread (single threaded insertion): ";
+    renumber< stdmap, stdmap >(vertex_ids, elements, 32);
+
+    std::cout << "pmap4, 1 thread: ";
+    renumber< pmap<4>, pmap_nullmutex<4> >(vertex_ids, elements, 1);
+
+    std::cout << "pmap4, 32 threads: ";
+    renumber< pmap<4>, pmap_nullmutex<4> >(vertex_ids, elements, 32);
+
+    std::cout << "pmap6, 1 thread: ";
+    renumber< pmap<6>, pmap_nullmutex<6> >(vertex_ids, elements, 1);
+
+    std::cout << "pmap6, 32 threads: ";
+    renumber< pmap<6>, pmap_nullmutex<6> >(vertex_ids, elements, 32);
+}