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/* Ergo, version 3.8, a program for linear scaling electronic structure
* calculations.
* Copyright (C) 2019 Elias Rudberg, Emanuel H. Rubensson, Pawel Salek,
* and Anastasia Kruchinina.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
* Primary academic reference:
* Ergo: An open-source program for linear-scaling electronic structure
* calculations,
* Elias Rudberg, Emanuel H. Rubensson, Pawel Salek, and Anastasia
* Kruchinina,
* SoftwareX 7, 107 (2018),
* <http://dx.doi.org/10.1016/j.softx.2018.03.005>
*
* For further information about Ergo, see <http://www.ergoscf.org>.
*/
/** @file blastime.cc
\brief Benchmark code for matrix-matrix multiplication (gemm)
operation, measuring timings for different matrix sizes.
*/
#include <iostream>
#include <fstream>
#include <iomanip> /* For setprecision in fstream */
#include <ctime>
#include <cmath>
#include <cstdlib>
#include <string.h>
#include <sys/time.h>
#include <vector>
#include "mat_gblas.h"
static const int MIN_TIME_PER_STEP = 5;
static const int SIZE_INCREMENT = 2;
static double get_wall_seconds() {
struct timeval tv;
gettimeofday(&tv, NULL);
double seconds = tv.tv_sec + (double)tv.tv_usec / 1000000;
return seconds;
}
template<class T>
static void tomatlabfile(char* name,T* values,int s,std::ofstream& output);
template<typename real>
int mainFun(int maxDim, double* timev, double* gflops, bool writeTomFile) {
try {
// bool CPUtime = false;
const real ONE=1.0;
const real ZERO=0.0;
double start, end;
int i;
int steps = 500000;//50000000;
/* Find reasonable number of steps */
double secondsTaken = 0;
int testSize = SIZE_INCREMENT;
while (secondsTaken < MIN_TIME_PER_STEP) {
steps = steps*3;
real* A=new real [testSize*testSize];
real* B=new real [testSize*testSize];
real* C=new real [testSize*testSize];
for(i = testSize*testSize-1; i>=0; i--) A[i] = 1.0;
for(i = testSize*testSize-1; i>=0; i--) B[i] = 1.0;
for(i = testSize*testSize-1; i>=0; i--) C[i] = 0.0;
int m = testSize;
int n = testSize;
int k = testSize;
start = get_wall_seconds();
for(int j=0; j<steps; j++) {
mat::gemm("N","N",&m,&n,&k,&ONE,A,&m,B,&k,&ZERO,C,&m);
}
end = get_wall_seconds();
secondsTaken = end-start;
}
printf("%d tests took %6.2f seconds.\n", steps, secondsTaken);
/* Run actual benchmark */
int maxStep = maxDim/SIZE_INCREMENT;
for (int step = 1; step <= maxStep; step++) {
int size = step*SIZE_INCREMENT;
real* A=new real [size*size];
real* B=new real [size*size];
real* C=new real [size*size];
for(i = size*size-1; i>=0; i--) A[i] = 1.0;
for(i = size*size-1; i>=0; i--) B[i] = 1.0;
for(i = size*size-1; i>=0; i--) C[i] = 0.0;
int m = size;
int n = size;
int k = size;
start = get_wall_seconds();
for(int j=0; j<steps; j++) {
mat::gemm("N","N",&m,&n,&k,&ONE,A,&m,B,&k,&ZERO,C,&m);
}
end = get_wall_seconds();
secondsTaken = end-start;
timev[step-1] = secondsTaken;
gflops[step-1]=(2*pow(double(size),3)+4*pow(double(size),2))/(timev[step-1]*1e9)*steps;
// gflops[step-1]=((2*pow(size,3)+4*pow(size,2))/timev[step-1])*(steps/1000000000);
delete[] A;
delete[] B;
delete[] C;
std::cout<<"size="<<std::setw(4)<<size
<<" steps="<<std::setw(8)<<steps
<<" time="<<std::setw(6)<<timev[step-1]
<<" Gflops="<<std::setw(10)
<<gflops[step-1]<<std::endl;
if (timev[step-1]>MIN_TIME_PER_STEP*2) {
/* This prediction does not really work for large relative
matrix size increments. But it does its job sufficiently well. */
int newSteps =
ceil(double(steps)*MIN_TIME_PER_STEP*1.5/double(timev[step-1]));
std::cout << "Recomputing new steps "<< newSteps <<" = "
<< steps << " * " << MIN_TIME_PER_STEP << " / "
<< timev[step-1] << std::endl;
steps = newSteps;
}
}
}
catch (std::exception & e) {
std::cout << "Exception caught: "<<e.what() << std::endl;
std::exit(1);
}
return 0;
}
template<typename T>
static void tomatlabfile(const char* name, T* values, int s,
std::ofstream& output) {
output<<name<<"=[";
for (int i=0;i<s;i++)
{
output<<std::setprecision(10)<<values[i]<<'\n';
}
output<<"];"<<std::endl;
}
int main(int argc,char* argv[]) {
int maxDim;
char path[200];
bool writeTomFile = true;
switch (argc) {
case 2:
maxDim = atoi(argv[1]); /* Max matrix dimension. */
writeTomFile = false;
break;
case 3:
maxDim = atoi(argv[1]); /* Max matrix dimension. */
strcpy(path, argv[2]); /* Matlab filename. */
break;
default:
std::cerr<<"Wrong number of input arguments. Give at least one argument (max matrix dimension) and optionally as a second argument the name of the m-file to create." << std::endl;
std::exit(1);
}
int maxSize = maxDim/SIZE_INCREMENT;
std::vector<double> timevDouble(maxSize);
std::vector<double> gflopsDouble(maxSize);
std::vector<double> timevSingle(maxSize);
std::vector<double> gflopsSingle(maxSize);
maxDim = maxSize*SIZE_INCREMENT;
time_t startTime;
time_t endTime;
std::cout<<"Starting gemm benchmark, double precision"<<std::endl;
time(&startTime);
if (!mainFun<double>(maxDim, &timevDouble[0], &gflopsDouble[0], writeTomFile)) {
time(&endTime);
std::cout<<"Ended gemm benchmark, double precision, wall time: "
<<endTime-startTime
<<std::endl;
}
std::cout<<"Starting gemm benchmark, single precision"<<std::endl;
time(&startTime);
if (!mainFun<float>(maxDim, &timevSingle[0], &gflopsSingle[0], writeTomFile)) {
time(&endTime);
std::cout<<"Ended gemm benchmark, single precision, wall time: "
<<endTime-startTime
<<std::endl;
}
if (writeTomFile) {
std::ofstream output(path);
if (!output) {
std::cout<<"Cannot open outputfile"<<std::endl;
std::exit(1);
}
output<<"nv=1:" << SIZE_INCREMENT <<":"<<maxDim<<";"<<std::endl;
tomatlabfile<double>("timeDouble" , &timevDouble [0], maxSize, output);
tomatlabfile<double>("GflopsDouble", &gflopsDouble[0], maxSize, output);
tomatlabfile<double>("timeSingle" , &timevSingle [0], maxSize, output);
tomatlabfile<double>("GflopsSingle", &gflopsSingle[0], maxSize, output);
output<<"minX = 0;\n"
<<"maxX = max(nv);\n"
<<"minY = 0;\n"
<<"maxY = max([GflopsDouble GflopsSingle]);\n"
<<"lwidth = 1;\n"
<<"fsize = 12;\n"
<<"figure;\n"
<<std::endl
<<"subplot(221)\n"
<<"plot(nv,GflopsDouble,'LineWidth',lwidth);nflops=100000;\n"
<<"axis([minX maxX minY maxY(1)])\n"
<<"set(gca,'FontSize',fsize)\n"
<<"title('Double Precision')\n"
<<"xlabel('Matrix Size')\n"
<<"ylabel('Gflops')\n"
<<"grid on\n"
<<std::endl
<<"subplot(222)\n"
<<"plot(nv,GflopsSingle,'LineWidth',lwidth);nflops=100000;\n"
<<"axis([minX maxX minY maxY(2)])\n"
<<"set(gca,'FontSize',fsize)\n"
<<"title('Single Precision')\n"
<<"xlabel('Matrix Size')\n"
<<"ylabel('Gflops')\n"
<<"grid on\n";
}
std::exit(0);
}
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