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#if defined(WIN32) || defined(_WIN32) || defined(__WIN32) && !defined(__CYGWIN__)
// #define DPL_ALGORITHMS // Includes Intel's OneAPI parallel algorithm implementations
#defineMICROSOFT_ALGORITHMS// Excludes single-core SIMD implementations, which Microsoft does not support
#endif
#ifdef DPL_ALGORITHMS
// oneDPL headers should be included before standard headers
#include<oneapi/dpl/algorithm>
#include<oneapi/dpl/execution>
#include<oneapi/dpl/iterator>
#else
#include<iostream>
#include<random>
#include<ratio>
#include<vector>
#include<algorithm>
#include<execution>
#include<iterator>
#include<chrono>
#endif
//#include <oneapi/dpl/algorithm>
//#define __TBB_PREVIEW_TASK_ARENA_CONSTRAINTS_EXTENSION_PRESENT 1
//#include <oneapi/tbb/task_arena.h>
#include"SumParallel.h"
using std::chrono::duration;
using std::chrono::duration_cast;
using std::chrono::high_resolution_clock;
using std::milli;
using std::random_device;
using std::sort;
using std::vector;
constint iterationCount = 20;
//extern void print_results(const char* const tag, const unsigned long long sum, size_t sum_array_length,
// high_resolution_clock::time_point startTime, high_resolution_clock::time_point endTime);
voidprint_results(constchar* const tag, constunsignedlonglong sum, size_t sum_array_length,
high_resolution_clock::time_point startTime,
high_resolution_clock::time_point endTime)
{
printf("%s: Sum: %llu Array Length: %zu Time: %fms Throughput: %llu millions/second\n", tag, sum, sum_array_length,
duration_cast<duration<double, milli>>(endTime - startTime).count(), (unsignedlonglong)(sum_array_length / duration_cast<duration<double, milli>>(endTime - startTime).count() * 1000.0 / 1000000.0));
}
voidprint_results(constchar* const tag, constunsignedlonglong sum, size_t sum_array_length,
high_resolution_clock::time_point startTime,
high_resolution_clock::time_point endTime,
double thruput_average, double thruput_std_dev
)
{
printf("%s: Sum: %llu Array Length: %zu Time: %fms Throughput Average: %.lf million Standard Deviation: %.lf\n", tag, sum, sum_array_length,
duration_cast<duration<double, milli>>(endTime - startTime).count(), thruput_average, thruput_std_dev);
}
// From: https://stackoverflow.com/questions/7616511/calculate-mean-and-standard-deviation-from-a-vector-of-samples-in-c-using-boos
doublestd_deviation(vector<double>& v)
{
double sum = std::accumulate(v.begin(), v.end(), 0.0);
double mean = sum / v.size();
std::vector<double> diff(v.size());
//std::transform(v.begin(), v.end(), diff.begin(), std::bind2nd(std::minus<double>(), mean));
std::transform(v.begin(), v.end(), diff.begin(), [mean](double x) { return x - mean; });
double sq_sum = std::inner_product(diff.begin(), diff.end(), diff.begin(), 0.0);
double stdev = std::sqrt(sq_sum / v.size());
return(stdev);
}
intSumBenchmarkChar(vector<unsigned>& uints)
{
vector<unsignedchar> u8Copy(uints.size());
vector<unsignedchar> u8Array(uints.size());
// time how long it takes to sort them:
for (int i = 0; i < iterationCount; ++i)
{
for (size_t j = 0; j < uints.size(); j++) { // copy the original random array into the source array each time, since ParallelMergeSort modifies the source array while sorting
u8Array[j] = (unsignedchar)uints[j];
u8Copy[ j] = (unsignedchar)uints[j];
}
// Eliminate compiler ability to optimize paging-in of the input and output arrays
// Paging-in source and destination arrays leads to a 50% speed-up on Linux, and 15% on Windows
constauto startTimeRef = high_resolution_clock::now();
unsignedlonglong sum_ref = 0;
//for (size_t i = 0; i < uints.size(); i++)
// sum_ref += u8Copy[i];
sum_ref = std::accumulate(u8Copy.begin(), u8Copy.end(), 0ULL);
constauto endTimeRef = high_resolution_clock::now();
print_results("std::accumulate", sum_ref, u8Copy.size(), startTimeRef, endTimeRef);
unsignedlonglong sum = 0;
//for (size_t k = 0; k < 100; k++)
//{
constauto startTime = high_resolution_clock::now();
//long long sum = ParallelAlgorithms::SumParallel(u8Array, 0, uints.size());
//sum = ParallelAlgorithms::SumParallel(u8Array, 0, uints.size(), uints.size() / 24); // Running on 24-core is fastest, however with 2.7X run-to-run variation
sum = ParallelAlgorithms::SumParallel(u8Array.data(), 0, uints.size());
constauto endTime = high_resolution_clock::now();
print_results("Parallel Sum of uchars", sum, uints.size(), startTime, endTime);
//}
if (sum == sum_ref)
printf("Sums are equal\n");
else
{
printf("Sums are not equal\n");
exit(1);
}
}
return0;
}
intSumBenchmark(vector<unsigned>& uints)
{
vector<unsigned> u32Copy( uints.size());
vector<unsigned> u32Array(uints.size());
// time how long it takes to sort them:
for (int i = 0; i < iterationCount; ++i)
{
for (size_t j = 0; j < uints.size(); j++) { // copy the original random array into the source array each time, since ParallelMergeSort modifies the source array while sorting
u32Array[j] = (unsigned)uints[j];
u32Copy[ j] = (unsigned)uints[j];
}
// Eliminate compiler ability to optimize paging-in of the input and output arrays
// Paging-in source and destination arrays leads to a 50% speed-up on Linux, and 15% on Windows
constauto startTimeRef = high_resolution_clock::now();
longlong sum_ref = 0;
//for (size_t i = 0; i < uints.size(); i++)
// sum_ref += u8Copy[i];
sum_ref = std::accumulate(u32Copy.begin(), u32Copy.end(), 0LL);
constauto endTimeRef = high_resolution_clock::now();
print_results("std::accumulate", sum_ref, u32Copy.size(), startTimeRef, endTimeRef);
longlong sum = 0;
//for (size_t k = 0; k < 100; k++)
//{
constauto startTime = high_resolution_clock::now();
//long long sum = ParallelAlgorithms::SumParallel(u8Array, 0, uints.size());
//sum = ParallelAlgorithms::SumParallel(u8Array, 0, uints.size(), uints.size() / 24); // Running on 24-core is fastest, however with 2.7X run-to-run variation
//sum = ParallelAlgorithms::SumParallel(u32Array.data(), 0, uints.size());
sum = ParallelAlgorithms::SumParallelNonRecursive(u32Array.data(), 0, uints.size());
//sum = ParallelAlgorithms::SumParallelNonRecursiveBuffered(u32Array.data(), 0, uints.size());
//sum = ParallelAlgorithms::SumParallelNonRecursiveBufferedLocally(u32Array.data(), 0, uints.size());
//sum = ParallelAlgorithms::SumParallelNonRecursiveNoHyperthreading(u32Array.data(), 0, uints.size());
//sum = ParallelAlgorithms::SumParallelNonRecursiveBufferedLocallyNoHyperthreading(u32Array.data(), 0, uints.size());
constauto endTime = high_resolution_clock::now();
print_results("Parallel Sum of unsigned", sum, uints.size(), startTime, endTime);
//}
if (sum == sum_ref)
printf("Sums are equal\n");
else
{
printf("Sums are not equal\n");
exit(1);
}
}
return0;
}
intSumBenchmark64(vector<unsigned>& uints)
{
vector<unsignedlonglong> u64Copy( uints.size());
vector<unsignedlonglong> u64Array(uints.size());
size_t num_times = 10;
double thruput_sum;
std::vector<double> thruputs(num_times);
// time how long it takes to sort them:
for (int i = 0; i < iterationCount; ++i)
{
for (size_t j = 0; j < uints.size(); j++) { // copy the original random array into the source array each time, since ParallelMergeSort modifies the source array while sorting
u64Array[j] = (unsignedlonglong)uints[j];
u64Copy[ j] = (unsignedlonglong)uints[j];
}
// Eliminate compiler ability to optimize paging-in of the input and output arrays
// Paging-in source and destination arrays leads to a 50% speed-up on Linux, and 15% on Windows
constauto startTimeRef = high_resolution_clock::now();
unsignedlonglong sum_ref = 0;
//for (size_t i = 0; i < uints.size(); i++)
// sum_ref += u64Copy[i];
//sum_ref = std::accumulate(u64Copy.begin(), u64Copy.end(), 0ULL);
sum_ref = std::accumulate(u64Copy.begin(), u64Copy.end(), 0ULL);
//std::fill(oneapi::dpl::execution::par_unseq, u64Copy.begin(), u64Copy.end(), 42);
//std::fill(u64Copy.begin(), u64Copy.end(), 42);
constauto endTimeRef = high_resolution_clock::now();
print_results("std::accumulate", sum_ref, u64Copy.size(), startTimeRef, endTimeRef);
//unsigned long long sum_array[1000] = { 0 };
auto startTime = high_resolution_clock::now();
auto endTime = high_resolution_clock::now();
unsignedlonglong sum = 0;
thruput_sum = 0.0;
for (size_t j = 0; j < num_times; ++j)
{
startTime = high_resolution_clock::now();
sum = 0;
//unsigned long long sum = ParallelAlgorithms::SumParallel(u64Array, 0, uints.size()); // Running on 24-core is fastest, however with 2.7X run-to-run variation
//unsigned long long sum = ParallelAlgorithms::SumParallel(u64Array, 0, uints.size(), uints.size() / 24); // Running on 24-core is fastest, however with 2.7X run-to-run variation
//unsigned long long sum = ParallelAlgorithms::SumParallelNonRecursive(u64Array, 0, uints.size());
//unsigned long long sum = ParallelAlgorithms::SumParallelNonRecursive(u64Array, 0, uints.size(), uints.size() / 8);
//sum = ParallelAlgorithms::SumParallelNonRecursiveNoHyperthreading(u64Array, 0, uints.size(), uints.size() / 14);
//sum = ParallelAlgorithms::SumNonRecursive(u64Array, 0, uints.size(), uints.size() / 2);
//sum = ParallelAlgorithms::SumParallelNonRecursive(u64Array, 0, uints.size(), uints.size() / 4);
//sum = ParallelAlgorithms::SumParallelNonRecursive(u64Array, 0, uints.size(), sum_array);
//sum = ParallelAlgorithms::SumParallelNonRecursive(u64Array.data(), 0, uints.size());
//sum = ParallelAlgorithms::SumParallelNonRecursiveBuffered(u64Array, 0, uints.size());
sum = ParallelAlgorithms::SumParallel(u64Array.data(), 0, uints.size());
//sum = ParallelAlgorithms::SumParallel(u64Array, 0, uints.size(), uints.size() / 4);
//sum = ParallelAlgorithms::SumParallel(u64Array, 0, uints.size(), uints.size() / 16); // highest performance with /15 and /17 at half the performance
endTime = high_resolution_clock::now();
thruputs[j] = (double)uints.size() / (duration_cast<duration<double, milli>>(endTime - startTime).count() / 1000.0) / 1000000.0;
thruput_sum += (double)uints.size() / (duration_cast<duration<double, milli>>(endTime - startTime).count() / 1000.0) / 1000000.0;
if (sum != sum_ref)
{
printf("Sums are not equal\n");
exit(1);
}
}
print_results("Parallel 64-bit Sum", sum, uints.size(), startTime, endTime, thruput_sum / num_times, std_deviation(thruputs));
}
return0;
}