eigen/bench/product_threshold.cpp
2010-03-05 18:11:54 +01:00

144 lines
3.2 KiB
C++

#include <iostream>
#include <Eigen/Core>
#include <bench/BenchTimer.h>
using namespace Eigen;
using namespace std;
#define END 9
template<int S> struct map_size { enum { ret = S }; };
template<> struct map_size<10> { enum { ret = 20 }; };
template<> struct map_size<11> { enum { ret = 50 }; };
template<> struct map_size<12> { enum { ret = 100 }; };
template<> struct map_size<13> { enum { ret = 300 }; };
template<int M, int N,int K> struct alt_prod
{
enum {
ret = M==1 && N==1 ? InnerProduct
: K==1 ? OuterProduct
: M==1 ? GemvProduct
: N==1 ? GemvProduct
: GemmProduct
};
};
void print_mode(int mode)
{
if(mode==InnerProduct) std::cout << "i";
if(mode==OuterProduct) std::cout << "o";
if(mode==CoeffBasedProductMode) std::cout << "c";
if(mode==LazyCoeffBasedProductMode) std::cout << "l";
if(mode==GemvProduct) std::cout << "v";
if(mode==GemmProduct) std::cout << "m";
}
template<int Mode, typename Lhs, typename Rhs, typename Res>
EIGEN_DONT_INLINE void prod(const Lhs& a, const Rhs& b, Res& c)
{
c.noalias() += typename ProductReturnType<Lhs,Rhs,Mode>::Type(a,b);
}
template<int M, int N, int K, typename Scalar, int Mode>
EIGEN_DONT_INLINE void bench_prod()
{
typedef Matrix<Scalar,M,K> Lhs; Lhs a; a.setRandom();
typedef Matrix<Scalar,K,N> Rhs; Rhs b; b.setRandom();
typedef Matrix<Scalar,M,N> Res; Res c; c.setRandom();
BenchTimer t;
double n = 2.*double(M)*double(N)*double(K);
int rep = 100000./n;
rep /= 2;
if(rep<1) rep = 1;
do {
rep *= 2;
t.reset();
BENCH(t,1,rep,prod<CoeffBasedProductMode>(a,b,c));
} while(t.best()<0.1);
t.reset();
BENCH(t,5,rep,prod<Mode>(a,b,c));
print_mode(Mode);
std::cout << int(1e-6*n*rep/t.best()) << "\t";
}
template<int N> struct print_n;
template<int M, int N, int K> struct loop_on_m;
template<int M, int N, int K, typename Scalar, int Mode> struct loop_on_n;
template<int M, int N, int K>
struct loop_on_k
{
static void run()
{
std::cout << "K=" << K << "\t";
print_n<N>::run();
std::cout << "\n";
loop_on_m<M,N,K>::run();
std::cout << "\n\n";
loop_on_k<M,N,K+1>::run();
}
};
template<int M, int N>
struct loop_on_k<M,N,END> { static void run(){} };
template<int M, int N, int K>
struct loop_on_m
{
static void run()
{
std::cout << M << "f\t";
loop_on_n<M,N,K,float,CoeffBasedProductMode>::run();
std::cout << "\n";
std::cout << M << "f\t";
loop_on_n<M,N,K,float,-1>::run();
std::cout << "\n";
loop_on_m<M+1,N,K>::run();
}
};
template<int N, int K>
struct loop_on_m<END,N,K> { static void run(){} };
template<int M, int N, int K, typename Scalar, int Mode>
struct loop_on_n
{
static void run()
{
bench_prod<M,N,K,Scalar,Mode==-1? alt_prod<M,N,K>::ret : Mode>();
loop_on_n<M,N+1,K,Scalar,Mode>::run();
}
};
template<int M, int K, typename Scalar, int Mode>
struct loop_on_n<M,END,K,Scalar,Mode> { static void run(){} };
template<int N> struct print_n
{
static void run()
{
std::cout << map_size<N>::ret << "\t";
print_n<N+1>::run();
}
};
template<> struct print_n<END> { static void run(){} };
int main()
{
loop_on_k<1,1,1>::run();
return 0;
}