int main()
{
int numBenchmarks = 6;
#ifndef BENCHMARK_VALARRAY
numBenchmarks--; // No valarray
#endif
#ifndef FORTRAN_90
numBenchmarks--; // No fortran 90
#endif
BenchmarkExt<int> bench("DAXPY Benchmark", numBenchmarks);
const int numSizes = 19;
bench.setNumParameters(numSizes);
Vector<int> parameters(numSizes);
Vector<long> iters(numSizes);
Vector<double> flops(numSizes);
for (int i=0; i < numSizes; ++i)
{
parameters(i) = static_cast<int>(pow(10.0, 0.25*(i+1)));
iters(i) = 50000000L / parameters(i);
if (iters(i) < 2)
iters(i) = 2;
flops(i) = 2 * parameters(i) * 2;
}
bench.setParameterVector(parameters);
bench.setIterations(iters);
bench.setOpsPerIteration(flops);
bench.beginBenchmarking();
float a = .398498293819823;
daxpyVectorVersion(bench, a, -a);
daxpyArrayVersion(bench, a);
daxpyF77Version(bench, a);
daxpyBLASVersion(bench, a);
#ifdef FORTRAN_90
daxpyF90Version(bench, a);
#endif
#ifdef BENCHMARK_VALARRAY
daxpyValarrayVersion(bench, a);
#endif
bench.endBenchmarking();
bench.saveMatlabGraph("daxpy.m");
return 0;
}
int main()
{ //menu driven program
while(1){
int numberOfThreads;
printf("\nEnter the no of threads:(1/2/4) /(Enter 8 for 600 Samples /Exit-0: ");
scanf("%d",&numberOfThreads);
// Enter 1/2/3 threads for GFLOPS/GIOPS
// Incase to get 600 samples for GFLOPS/GIOPS Enter 8
// To exit press 0
if(numberOfThreads!=1 && numberOfThreads!=2 && numberOfThreads!=4 && numberOfThreads!=0 && numberOfThreads!=8)
{
printf("\nInvalid choice..Please enter again");
}
else if(numberOfThreads==8)
{
flops(4);
iops(4);
}
else if(numberOfThreads==0)
{
exit(0);
}
else
{
flopsCal(numberOfThreads);
iopsCal(numberOfThreads);
}
}
return 0;
}
int main()
{
BenchmarkExt<int> bench("Array DAXPY", 2);
const int numSizes = 128;
bench.setNumParameters(numSizes);
bench.setRateDescription("Mflops/s");
Vector<int> parameters(numSizes);
Vector<long> iters(numSizes);
Vector<double> flops(numSizes);
for (int i=0; i < numSizes; ++i)
{
parameters[i] = (i+1);
iters[i] = 16*32*8*8*8/(i+1)/(i+1)/(i+1);
float npoints = parameters[i];
flops[i] = npoints * npoints * npoints * 2 * 2;
}
bench.setParameterVector(parameters);
bench.setIterations(iters);
bench.setFlopsPerIteration(flops);
bench.beginBenchmarking();
arrdaxpyBlitzVersion(bench);
arrdaxpyFortran77Version(bench);
bench.endBenchmarking();
bench.saveMatlabGraph("arrdaxpy.m");
return 0;
}
int main()
{
int numBenchmarks = 5;
if (runvector) numBenchmarks++;
#ifdef BENCHMARK_VALARRAY
numBenchmarks++;
#endif
#ifdef FORTRAN_90
numBenchmarks++;
#endif
BenchmarkExt<int> bench("loop100: $x=(1.0-$c*$c)/((4*w)*sin(1.0+$c*$c-2*v*$c))*$a*$b*u*exp(-z*$d)", numBenchmarks);
bench.setNumParameters(numSizes);
Array<int,1> parameters(numSizes);
Array<long,1> iters(numSizes);
Array<double,1> flops(numSizes);
parameters=pow(pow(2.,0.25),tensor::i)+tensor::i;
flops = 18 * parameters;
iters = 100000000L / flops;
iters = where(iters<2, 2, iters);
cout << iters << endl;
bench.setParameterVector(parameters);
bench.setIterations(iters);
bench.setOpsPerIteration(flops);
bench.setDependentVariable("flops");
bench.beginBenchmarking();
double u = 0.39123982498157938742;
double v = 0.39123982498157938742;
double w = 0.39123982498157938742;
double z = 0.39123982498157938742;
ArrayVersion(bench, u, v, w, z);
ArrayVersion_unaligned(bench, u, v, w, z);
ArrayVersion_misaligned(bench, u, v, w, z);
ArrayVersion_index(bench, u, v, w, z);
//doTinyVectorVersion(bench, u, v, w, z);
F77Version(bench, u, v, w, z);
#ifdef FORTRAN_90
F90Version(bench, u, v, w, z);
#endif
#ifdef BENCHMARK_VALARRAY
ValarrayVersion(bench, u, v, w, z);
#endif
if(runvector)
VectorVersion(bench, u, v, w, z);
bench.endBenchmarking();
bench.saveMatlabGraph("loop100.m");
return 0;
}
int main()
{
int numBenchmarks = 5;
if (runvector) numBenchmarks++;
#ifdef BENCHMARK_VALARRAY
numBenchmarks++;
#endif
#ifdef FORTRAN_90
numBenchmarks++;
#endif
BenchmarkExt<int> bench("floop3: $y = $y + a*$x", numBenchmarks);
bench.setNumParameters(numSizes);
Array<int,1> parameters(numSizes);
Array<long,1> iters(numSizes);
Array<double,1> flops(numSizes);
parameters=pow(pow(2.,0.25),tensor::i)+tensor::i;
flops = 2 * parameters;
iters = 100000000L / flops;
iters = where(iters<2, 2, iters);
cout << iters << endl;
bench.setParameterVector(parameters);
bench.setIterations(iters);
bench.setOpsPerIteration(flops);
bench.setDependentVariable("flops");
bench.beginBenchmarking();
float a = 0.39123982498157938742;
ArrayVersion(bench, a);
ArrayVersion_unaligned(bench, a);
ArrayVersion_misaligned(bench, a);
ArrayVersion_index(bench, a);
//doTinyVectorVersion(bench, a);
F77Version(bench, a);
#ifdef FORTRAN_90
F90Version(bench, a);
#endif
#ifdef BENCHMARK_VALARRAY
ValarrayVersion(bench, a);
#endif
if(runvector)
VectorVersion(bench, a);
bench.endBenchmarking();
bench.saveMatlabGraph("floop3.m");
return 0;
}
int main()
{
if (dontActuallyRunBenchmark())
return 0;
int numBenchmarks = 2;
BenchmarkExt<int> bench("loop1: $x=sqrt($y)", numBenchmarks);
const int numSizes = 26;
bench.setNumParameters(numSizes);
//bench.setRateDescription("Mflops/s"); removed
Vector<int> parameters(numSizes);
Vector<long> iters(numSizes);
Vector<double> flops(numSizes);
for (int i=0; i < numSizes; ++i)
{
parameters(i) = (int)pow(10.0, (i+1)/4.0);
iters[i] = 50000000L / parameters(i);
if (iters(i) < 2)
iters(i) = 2;
flops(i) = 1 * parameters(i);
}
bench.setParameterVector(parameters);
bench.setIterations(iters);
bench.setOpsPerIteration(flops);
bench.beginBenchmarking();
VectorVersion(bench);
ArrayVersion(bench);
bench.endBenchmarking();
bench.saveMatlabGraph("loop1.m");
return 0;
}
int main()
{
int numBenchmarks = 5;
#ifndef BENCHMARK_VALARRAY
numBenchmarks--; // No valarray
#endif
#ifndef FORTRAN_90
numBenchmarks--; // No fortran 90
#endif
BenchmarkExt<int> bench("loop18: $x=(u+$a)*(v+$b)", numBenchmarks);
const int numSizes = 23;
bench.setNumParameters(numSizes);
bench.setRateDescription("Mflops/s");
Vector<int> parameters(numSizes);
Vector<long> iters(numSizes);
Vector<double> flops(numSizes);
for (int i=0; i < numSizes; ++i)
{
parameters[i] = (int)pow(10.0, (i+1)/4.0);
iters[i] = 10000000L / parameters[i];
if (iters[i] < 2)
iters[i] = 2;
flops[i] = 3 * parameters[i];
}
bench.setParameterVector(parameters);
bench.setIterations(iters);
bench.setFlopsPerIteration(flops);
bench.beginBenchmarking();
double u = 0.39123982498157938742;
double v = 0.39123982498157938742;
VectorVersion(bench, u, v);
ArrayVersion(bench, u, v);
F77Version(bench, u, v);
#ifdef FORTRAN_90
F90Version(bench, u, v);
#endif
#ifdef BENCHMARK_VALARRAY
ValarrayVersion(bench, u, v);
#endif
bench.endBenchmarking();
bench.saveMatlabGraph("loop18.m");
return 0;
}
int main()
{
#ifdef BENCHMARK_VALARRAY
int numBenchmarks = 6;
#else
int numBenchmarks = 5;
#endif
BenchmarkExt<int> bench("DAXPY Benchmark", numBenchmarks);
const int numSizes = 19;
bench.setNumParameters(numSizes);
bench.setRateDescription("Mflops/s");
Vector<int> parameters(numSizes);
Vector<long> iters(numSizes);
Vector<double> flops(numSizes);
for (int i=0; i < numSizes; ++i)
{
parameters[i] = pow(10.0, (i+1)/4.0);
iters[i] = 50000000L / parameters[i];
if (iters[i] < 2)
iters[i] = 2;
flops[i] = 2 * parameters[i] * 2;
}
bench.setParameterVector(parameters);
bench.setIterations(iters);
bench.setOpsPerIteration(flops);
bench.beginBenchmarking();
float a = .398498293819823;
daxpyVectorVersion(bench, a, -a);
daxpyArrayVersion(bench, a);
daxpyF77Version(bench, a);
daxpyBLASVersion(bench, a);
daxpyF90Version(bench, a);
#ifdef BENCHMARK_VALARRAY
daxpyValarrayVersion(bench, a);
#endif
bench.endBenchmarking();
bench.saveMatlabGraph("daxpy2.m");
return 0;
}
int main()
{
int numBenchmarks = 10;
#ifndef FORTRAN_90
numBenchmarks--; // No fortran 90
#endif
BenchmarkExt<int> bench("Array stencil", numBenchmarks);
const int numSizes = 28;
bench.setNumParameters(numSizes);
bench.setRateDescription("Mflops/s");
Vector<int> parameters(numSizes);
Vector<long> iters(numSizes);
Vector<double> flops(numSizes);
for (int i=0; i < numSizes; ++i)
{
parameters[i] = (i+1) * 8;
iters[i] = 32*8*8*8/(i+1)/(i+1)/(i+1)/4;
if (iters[i] < 2)
iters[i] = 2;
int npoints = parameters[i] - 2;
flops[i] = npoints * npoints * npoints * 7 * 2;
}
bench.setParameterVector(parameters);
bench.setIterations(iters);
bench.setFlopsPerIteration(flops);
bench.beginBenchmarking();
#ifdef FORTRAN_90
stencilFortran90Version(bench);
#endif
stencilBlitzVersion(bench);
stencilBlitzStencilVersion(bench);
stencilBlitzExpressionVersion(bench);
stencilBlitzProductVersion(bench);
stencilBlitzProductVersion2(bench);
stencilBlitzProductVersion3(bench);
stencilBlitzIndexVersion(bench);
stencilFortran77Version(bench);
stencilFortran77VersionTiled(bench);
bench.endBenchmarking();
bench.saveMatlabGraph("stencil.m","plot");
return 0;
}
