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// In KAI C++ 3.2c, restrict causes problems for copy propagation.
// Temporary kludge is to disable use of the restrict keyword.
#define BZ_DISABLE_RESTRICT
#include <blitz/vector.h>
#include <blitz/array.h>
#include <blitz/rand-uniform.h>
#include <blitz/benchext.h>
#ifdef BENCHMARK_VALARRAY
#include <valarray>
#endif
BZ_USING_NAMESPACE(blitz)
#ifdef BZ_FORTRAN_SYMBOLS_WITH_TRAILING_UNDERSCORES
#define fdaxpy fdaxpy_
#define f90daxpy f90daxpy_
#define fidaxpy fidaxpy_
#define fidaxpyo fidaxpyo_
#endif
#ifdef BZ_FORTRAN_SYMBOLS_CAPS
#define fdaxpy FDAXPY
#define f90daxpy F90DAXPY
#define fidaxpy FIDAXPY
#define fidaxpyo FIDAXPYO
#endif
extern "C" {
void fdaxpy(const int& N, const double& da, double* x,
const int& xstride, const double* y, const int& ystride);
void f90daxpy(const double& a, double* x,
const double* y, const int& length, const int& iters);
void fidaxpy(const double& a, double* x, const double* y,
const int& length, const int& iters);
void fidaxpyo(const double& a, double* x, const double* y,
const int& length, const int& iters);
}
void daxpyVectorVersion(BenchmarkExt<int>& bench, double a, double b);
void daxpyArrayVersion(BenchmarkExt<int>& bench, double a);
void daxpyF77Version(BenchmarkExt<int>& bench, double a);
void daxpyBLASVersion(BenchmarkExt<int>& bench, double a);
void daxpyF90Version(BenchmarkExt<int>& bench, double a);
#ifdef BENCHMARK_VALARRAY
void daxpyValarrayVersion(BenchmarkExt<int>& bench, double a);
#endif
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;
}
void initializeRandomDouble(double* data, int numElements, int stride = 1)
{
static Random<Uniform> rnd;
for (int i=0; i < numElements; ++i)
data[i*stride] = rnd.random();
}
template<class T>
void initializeArray(T& array, int numElements)
{
static Random<Uniform> rnd;
for (size_t i=0; i < numElements; ++i)
array[i] = rnd.random();
}
void daxpyVectorVersion(BenchmarkExt<int>& bench, double a, double b)
{
bench.beginImplementation("Vector<T>");
while (!bench.doneImplementationBenchmark())
{
int N = bench.getParameter();
cout << "Vector<T>: N = " << N << endl;
cout.flush();
long iters = bench.getIterations();
Vector<double> x(N), y(N);
initializeRandomDouble(x.data(), N);
initializeRandomDouble(y.data(), N);
bench.start();
for (long i=0; i < iters; ++i)
{
y += a * x;
y += b * x;
}
bench.stop();
}
bench.endImplementation();
}
void daxpyArrayVersion(BenchmarkExt<int>& bench, double a)
{
bench.beginImplementation("Array<T,1>");
while (!bench.doneImplementationBenchmark())
{
int N = bench.getParameter();
cout << "Array<T,1>: N = " << N << endl;
cout.flush();
long iters = bench.getIterations();
Array<double,1> x(N), y(N);
initializeRandomDouble(x.data(), N);
initializeRandomDouble(y.data(), N);
double b = - a;
bench.start();
for (long i=0; i < iters; ++i)
{
y += a * x;
y += b * x;
}
bench.stop();
}
bench.endImplementation();
}
void daxpyF77Version(BenchmarkExt<int>& bench, double a)
{
bench.beginImplementation("Fortran 77");
while (!bench.doneImplementationBenchmark())
{
int N = bench.getParameter();
cout << "Fortran 77: N = " << N << endl;
cout.flush();
int iters = bench.getIterations();
double* x = new double[N];
double* y = new double[N];
initializeRandomDouble(x, N);
initializeRandomDouble(y, N);
bench.start();
fidaxpy(a, x, y, N, iters);
bench.stop();
delete [] x;
delete [] y;
}
bench.endImplementation();
}
void daxpyBLASVersion(BenchmarkExt<int>& bench, double a)
{
bench.beginImplementation("Fortran BLAS");
while (!bench.doneImplementationBenchmark())
{
int N = bench.getParameter();
cout << "Fortran BLAS: N = " << N << endl;
cout.flush();
int iters = bench.getIterations();
double* x = new double[N];
double* y = new double[N];
initializeRandomDouble(x, N);
initializeRandomDouble(y, N);
int xstride = 1, ystride = 1;
double b = - a;
bench.start();
for (long i=0; i < iters; ++i)
{
fdaxpy(N, a, x, xstride, y, ystride);
fdaxpy(N, b, x, xstride, y, ystride);
}
bench.stop();
delete [] x;
delete [] y;
}
bench.endImplementation();
}
void daxpyF90Version(BenchmarkExt<int>& bench, double a)
{
bench.beginImplementation("Fortran 90");
while (!bench.doneImplementationBenchmark())
{
int N = bench.getParameter();
cout << "Fortran 90: N = " << N << endl;
cout.flush();
int iters = bench.getIterations();
double* x = new double[N];
double* y = new double[N];
initializeRandomDouble(x, N);
initializeRandomDouble(y, N);
bench.start();
f90daxpy(a, x, y, N, iters);
bench.stop();
delete [] x;
delete [] y;
}
bench.endImplementation();
}
#ifdef BENCHMARK_VALARRAY
void daxpyValarrayVersion(BenchmarkExt<int>& bench, double a)
{
bench.beginImplementation("valarray<T>");
while (!bench.doneImplementationBenchmark())
{
int N = bench.getParameter();
cout << "valarray<T>: N = " << N << endl;
cout.flush();
long iters = bench.getIterations();
valarray<double> x(N), y(N);
initializeArray(x, N);
initializeArray(y, N);
double b = - a;
bench.start();
for (long i=0; i < iters; ++i)
{
y += a * x;
y += b * x;
}
bench.stop();
}
bench.endImplementation();
}
#endif
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