cpp-taskflow/example/taskflow.cpp at master · hug2008/cpp-taskflow · GitHub

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// 2018/12/04 - modified by Tsung-Wei Huang

// - replaced privatized threadpool with work stealing threadpool

// 2018/10/24 - modified by Tsung-Wei Huang

// - Taskflow is templated at threadpool

// - added graph-level comparison with different thread pools

// 2018/09/19 - created by Tsung-Wei Huang

// This program is used to benchmark the taskflow under different types

// of workloads.

#include <taskflow/taskflow.hpp>

#include <chrono>

#include <random>

#include <climits>

#include <iomanip>

constexpr int WIDTH = 12;

// Procedure: benchmark

#define BENCHMARK(TITLE, F) \

std::cout \

<< std::setw(WIDTH) << TITLE << std::flush \

<< std::setw(WIDTH) << F<tf::BasicTaskflow<tf::SimpleThreadpool>>() << std::flush \

<< std::setw(WIDTH) << F<tf::BasicTaskflow<tf::ProactiveThreadpool>>() << std::flush \

<< std::setw(WIDTH) << F<tf::BasicTaskflow<tf::SpeculativeThreadpool>>() << std::flush \

<< std::setw(WIDTH) << F<tf::BasicTaskflow<tf::WorkStealingThreadpool>>() << std::flush \

<< std::endl;

// ============================================================================

// Dynamic Stem

// ============================================================================

// Function: dynamic_stem

template <typename T>

auto dynamic_stem() {

auto beg = std::chrono::high_resolution_clock::now();

{

const int L = 1024;

std::atomic<size_t> sum {0};

T tf;

std::optional<tf::Task> prev;

for(int l=0; l<L; ++l) {

auto curr = tf.silent_emplace([&, l] (auto& subflow) {

sum.fetch_add(1, std::memory_order_relaxed);

std::optional<tf::Task> p;

for(int k=0; k<L; k++) {

auto c = subflow.silent_emplace([&] () {

sum.fetch_add(1, std::memory_order_relaxed);

});

if(p) {

p->precede(c);

}

p = c;

}

if(l & 1) {

subflow.detach();

}

});

if(prev) {

prev->precede(curr);

}

prev = curr;

}

tf.wait_for_all();

assert(sum == L*(L+1));

}

auto end = std::chrono::high_resolution_clock::now();

return std::chrono::duration_cast<std::chrono::milliseconds>(end - beg).count();

}

// ============================================================================

// Map-Reduce

// ============================================================================

// Function: map_reduce

template <typename T>

auto map_reduce() {

auto beg = std::chrono::high_resolution_clock::now();

{

const int num_batches = 65536;

std::vector<int> C(1024, 10);

std::atomic<size_t> sum {0};

T tf;

std::optional<tf::Task> prev;

for(int i=0; i<num_batches; ++i) {

auto [s, t] = tf.parallel_for(C.begin(), C.end(), [&] (int v) {

sum.fetch_add(v, std::memory_order_relaxed);

});

if(prev) {

prev->precede(s);

}

prev = t;

}

tf.wait_for_all();

assert(sum == num_batches * C.size() * 10);

}

auto end = std::chrono::high_resolution_clock::now();

return std::chrono::duration_cast<std::chrono::milliseconds>(end - beg).count();

}

// ============================================================================

// Level Graph

// ============================================================================

// Function: level_graph

template <typename T>

auto level_graph() {

const int num_levels = 2048;

const int num_nodes_per_level = 1024;

auto beg = std::chrono::high_resolution_clock::now();

{

std::atomic<size_t> sum {0};

T tf;

std::vector< std::vector<tf::Task> > tasks;

tasks.resize(num_levels);

for(int l=0; l<num_levels; ++l) {

for(int i=0; i<num_nodes_per_level; ++i) {

tasks[l].push_back(tf.silent_emplace([&] () {

sum.fetch_add(1, std::memory_order_relaxed);

}));

}

// connections for each level l to l+1

for(int l=0; l<num_levels-1; ++l) {

for(int i=0; i<num_nodes_per_level; ++i) {

for(int j=0; j<num_nodes_per_level; j=j+i+1) {

tasks[l][i].precede(tasks[l+1][j]);

}

tf.wait_for_all();

assert(sum == num_levels * num_nodes_per_level);

}

auto end = std::chrono::high_resolution_clock::now();

return std::chrono::duration_cast<std::chrono::milliseconds>(end - beg).count();

}

// ============================================================================

// Linear Graph

// ============================================================================

// Function: linear_graph

template <typename T>

auto linear_graph() {

const int num_nodes = 1000000;

auto beg = std::chrono::high_resolution_clock::now();

{

size_t sum {0};

T tf;

std::vector<tf::Task> tasks;

for(int i=0; i<num_nodes; ++i) {

tasks.push_back(tf.silent_emplace([&] () { ++sum; }));

}

tf.linearize(tasks);

tf.wait_for_all();

assert(sum == num_nodes);

}

auto end = std::chrono::high_resolution_clock::now();

return std::chrono::duration_cast<std::chrono::milliseconds>(end - beg).count();

}

// ============================================================================

// Binary Tree

// ============================================================================

// Function: binary_tree

template <typename T>

auto binary_tree() {

const int num_levels = 21;

auto beg = std::chrono::high_resolution_clock::now();

{

T tf;

std::atomic<size_t> sum {0};

std::function<void(int, tf::Task)> insert;

insert = [&] (int l, tf::Task parent) {

if(l < num_levels) {

auto lc = tf.silent_emplace([&] () {

sum.fetch_add(1, std::memory_order_relaxed);

});

auto rc = tf.silent_emplace([&] () {

sum.fetch_add(1, std::memory_order_relaxed);

});

parent.precede(lc);

parent.precede(rc);

insert(l+1, lc);

insert(l+1, rc);

}

};

auto root = tf.silent_emplace([&] () {

sum.fetch_add(1, std::memory_order_relaxed);

});

insert(1, root);

// synchronize until all tasks finish

tf.wait_for_all();

assert(sum == (1 << (num_levels)) - 1);

}

auto end = std::chrono::high_resolution_clock::now();

return std::chrono::duration_cast<std::chrono::milliseconds>(end - beg).count();

}

// ============================================================================

// Empty Jobs

// ============================================================================

// Function: empty_jobs

template <typename T>

auto empty_jobs() {

const int num_tasks = 2000000;

auto beg = std::chrono::high_resolution_clock::now();

{

T tf;

for(size_t i=0; i<num_tasks; i++){

tf.silent_emplace([](){});

}

tf.wait_for_all();

}

auto end = std::chrono::high_resolution_clock::now();

return std::chrono::duration_cast<std::chrono::milliseconds>(end - beg).count();

}

// ============================================================================

// Atomic add

// ============================================================================

// Function: atomic_add

template <typename T>

auto atomic_add() {

const int num_tasks = 1000000;

auto beg = std::chrono::high_resolution_clock::now();

{

std::atomic<int> counter(0);

T tf;

for(size_t i=0; i<num_tasks; i++){

tf.silent_emplace([&counter](){

counter.fetch_add(1, std::memory_order_relaxed);

});

}

tf.wait_for_all();

assert(counter == num_tasks);

}

auto end = std::chrono::high_resolution_clock::now();

return std::chrono::duration_cast<std::chrono::milliseconds>(end - beg).count();

}

// ============================================================================

// Multiple Dispatches

// ============================================================================

// Function: multiple_dispatches

template <typename T>

auto multiple_dispatches() {

auto create_graph = [] (T& tf, size_t N, std::atomic<int>& c) {

for(size_t i=0; i<N; ++i) {

auto [A, B, C, D] = tf.silent_emplace(

[&] () { c.fetch_add(1, std::memory_order_relaxed); },

[&] () { c.fetch_add(1, std::memory_order_relaxed); }

);

A.precede(B);

C.precede(D);

}

};

auto beg = std::chrono::high_resolution_clock::now();

{

T tf;

for(int p=0; p<1024; ++p) {

std::atomic<int> counter(0);

create_graph(tf, p, counter);

tf.wait_for_all();

assert(counter == p * 4);

}

auto end = std::chrono::high_resolution_clock::now();

return std::chrono::duration_cast<std::chrono::milliseconds>(end - beg).count();

}

// ----------------------------------------------------------------------------

// Function: main

int main(int argc, char* argv[]) {

std::cout << std::setw(WIDTH) << "workload"

<< std::setw(WIDTH) << "tf+simple"

<< std::setw(WIDTH) << "tf+pro"

<< std::setw(WIDTH) << "tf+spec"

<< std::setw(WIDTH) << "tf+steal"

<< std::endl;

BENCHMARK("map-reduce", map_reduce);

BENCHMARK("empty jobs", empty_jobs);

BENCHMARK("atomic add", atomic_add);

BENCHMARK("dispatches", multiple_dispatches);

BENCHMARK("b-tree", binary_tree);

BENCHMARK("linear", linear_graph);

BENCHMARK("dag", level_graph);

BENCHMARK("dynamic", dynamic_stem);

return 0;

}

cpp-taskflow/example/taskflow.cpp at master · hug2008/cpp-taskflow · GitHub

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