Threads failing to affect performance

Question

Below is a small program meant to parallelize the approximation of the 1/(n^2) series. Note the global parameter NUM_THREADS .

My issue is that increasing the number of threads from 1 to 4 (the number of processors my computer has is 4) does not significantly affect the outcomes of timing experiments. Do you see a logical flaw in the ThreadFunction ? Is there false sharing or misplaced blocking that ends up serializing the execution?

#include <iostream>
#include <thread>
#include <vector>
#include <mutex>
#include <string>
#include <future>
#include <chrono>

std::mutex sum_mutex;           // This mutex is for the sum vector
std::vector<double> sum_vec;    // This is the sum vector
int NUM_THREADS = 1;
int UPPER_BD = 1000000;

/* Thread function */
void ThreadFunction(std::vector<double> &l, int beg, int end, int thread_num)
{
    double sum = 0;
    for(int i = beg; i < end; i++) sum += (1 / ( l[i] * l[i]) );
    std::unique_lock<std::mutex> lock1 (sum_mutex, std::defer_lock);
    lock1.lock();
    sum_vec.push_back(sum);
    lock1.unlock();
}

void ListFill(std::vector<double> &l, int z)
{
    for(int i = 0; i < z; ++i) l.push_back(i);
}

int main() 
{
    std::vector<double> l;
    std::vector<std::thread> thread_vec;

    ListFill(l, UPPER_BD);
    int len = l.size();

    int lower_bd = 1;
    int increment = (UPPER_BD - lower_bd) / NUM_THREADS;
    for (int j = 0; j < NUM_THREADS; ++j)
    {
        thread_vec.push_back(std::thread(ThreadFunction, std::ref(l), lower_bd, lower_bd + increment, j));
        lower_bd += increment;
    }

    for (auto &t : thread_vec) t.join();
    double big_sum;
    for (double z : sum_vec) big_sum += z;

    std::cout << big_sum << std::endl;

    return 0;
}

Answer 1

From looking at your code, I suspect that ListFill is taking longer than ThreadFunction. Why pass a list of values to the thread instead of the bounds each thread should loop over? Something like:

void ThreadFunction( int beg, int end ) {
    double sum = 0.0;
    for(double i = beg; i < end; i++) 
         sum += (1.0 / ( i * i) );
    std::unique_lock<std::mutex> lock1 (sum_mutex);
    sum_vec.push_back(sum);
}

To maximize parallelism, you need to push as much work as possible onto the threads. See Amdahl's Law

Answer 2

In addition to dohashi's nice improvement, you can remove the need for the mutex by populating the sum_vec in advance in the main thread:

sum_vec.resize(4);

then writing directly to it in ThreadFunction :

sum_vec[thread_num] = sum;

since each thread writes to a distinct element and doesn't modify the vector itself there is no need to lock anything.