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add matlab-like mixed product

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This commit is contained in:
Gael Guennebaud 2010-07-22 13:19:09 +02:00
parent bec3f9bfe4
commit 06250a154c
1 changed files with 89 additions and 14 deletions
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103
bench/bench_gemm.cpp
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@ -10,15 +10,16 @@ using namespace std;
using namespace Eigen;
#ifndef SCALAR
#define SCALAR std::complex<double>
// #define SCALAR double
#define SCALAR std::complex<float>
// #define SCALAR float
#endif
typedef SCALAR Scalar;
typedef NumTraits<Scalar>::Real RealScalar;
typedef Matrix<RealScalar,Dynamic,Dynamic> A;
typedef Matrix<Scalar,Dynamic,Dynamic> B;
typedef Matrix</*Real*/Scalar,Dynamic,Dynamic> B;
typedef Matrix<Scalar,Dynamic,Dynamic> C;
typedef Matrix<RealScalar,Dynamic,Dynamic> M;
#ifdef HAVE_BLAS
@ -35,7 +36,7 @@ static std::complex<float> cfzero = 0;
static std::complex<double> cdone = 1;
static std::complex<double> cdzero = 0;
static char notrans = 'N';
static char trans = 'T';
static char trans = 'T';
static char nonunit = 'N';
static char lower = 'L';
static char right = 'R';
@ -87,10 +88,30 @@ void blas_gemm(const MatrixXd& a, const MatrixXd& b, MatrixXd& c)
#endif
void matlab_cplx_cplx(const M& ar, const M& ai, const M& br, const M& bi, M& cr, M& ci)
{
cr.noalias() += ar * br;
cr.noalias() -= ai * bi;
ci.noalias() += ar * bi;
ci.noalias() += ai * br;
}
void matlab_real_cplx(const M& a, const M& br, const M& bi, M& cr, M& ci)
{
cr.noalias() += a * br;
ci.noalias() += a * bi;
}
void matlab_cplx_real(const M& ar, const M& ai, const M& b, M& cr, M& ci)
{
cr.noalias() += ar * b;
ci.noalias() += ai * b;
}
template<typename A, typename B, typename C>
EIGEN_DONT_INLINE void gemm(const A& a, const B& b, C& c)
{
c.noalias() += a * b;
c.noalias() += a * b;
}
int main(int argc, char ** argv)
@ -99,8 +120,8 @@ int main(int argc, char ** argv)
std::ptrdiff_t l2 = ei_queryTopLevelCacheSize();
std::cout << "L1 cache size = " << (l1>0 ? l1/1024 : -1) << " KB\n";
std::cout << "L2/L3 cache size = " << (l2>0 ? l2/1024 : -1) << " KB\n";
typedef ei_product_blocking_traits<Scalar,Scalar> Blocking;
std::cout << "Register blocking = " << Blocking::mr << " x " << Blocking::nr << "\n";
typedef ei_gebp_traits<Scalar,Scalar> Traits;
std::cout << "Register blocking = " << Traits::mr << " x " << Traits::nr << "\n";
int rep = 1; // number of repetitions per try
int tries = 2; // number of tries, we keep the best
@ -135,19 +156,19 @@ int main(int argc, char ** argv)
int m = s;
int n = s;
int p = s;
A a(m,n); a.setRandom();
B b(n,p); b.setRandom();
C c(m,p); c.setOnes();
A a(m,p); a.setRandom();
B b(p,n); b.setRandom();
C c(m,n); c.setOnes();
std::cout << "Matrix sizes = " << m << "x" << p << " * " << p << "x" << n << "\n";
std::ptrdiff_t cm(m), cn(n), ck(p);
computeProductBlockingSizes<Scalar,Scalar>(ck, cm, cn);
std::cout << "blocking size = " << cm << " x " << ck << "\n";
std::ptrdiff_t mc(m), nc(n), kc(p);
computeProductBlockingSizes<Scalar,Scalar>(kc, mc, nc);
std::cout << "blocking size (mc x kc) = " << mc << " x " << kc << "\n";
C r = c;
// check the parallel product is correct
#ifdef EIGEN_HAS_OPENMP
#if defined EIGEN_HAS_OPENMP
int procs = omp_get_max_threads();
if(procs>1)
{
@ -161,6 +182,17 @@ int main(int argc, char ** argv)
c.noalias() += a * b;
if(!r.isApprox(c)) std::cerr << "Warning, your parallel product is crap!\n\n";
}
#elif defined HAVE_BLAS
blas_gemm(a,b,r);
c.noalias() += a * b;
if(!r.isApprox(c)) std::cerr << "Warning, your product is crap!\n\n";
// std::cerr << r << "\n\n" << c << "\n\n";
#else
gemm(a,b,c);
r.noalias() += a.cast<Scalar>() * b.cast<Scalar>();
if(!r.isApprox(c)) std::cerr << "Warning, your product is crap!\n\n";
// std::cerr << c << "\n\n";
// std::cerr << r << "\n\n";
#endif
#ifdef HAVE_BLAS
@ -187,6 +219,49 @@ int main(int argc, char ** argv)
std::cout << "mt speed up x" << tmono.best(CPU_TIMER) / tmt.best(REAL_TIMER) << " => " << (100.0*tmono.best(CPU_TIMER) / tmt.best(REAL_TIMER))/procs << "%\n";
}
#endif
#ifdef DECOUPLED
if((NumTraits<A::Scalar>::IsComplex) && (NumTraits<B::Scalar>::IsComplex))
{
M ar(m,p); ar.setRandom();
M ai(m,p); ai.setRandom();
M br(p,n); br.setRandom();
M bi(p,n); bi.setRandom();
M cr(m,n); cr.setRandom();
M ci(m,n); ci.setRandom();
BenchTimer t;
BENCH(t, tries, rep, matlab_cplx_cplx(ar,ai,br,bi,cr,ci));
std::cout << "\"matlab\" cpu " << t.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << t.total(CPU_TIMER) << "s)\n";
std::cout << "\"matlab\" real " << t.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << t.total(REAL_TIMER) << "s)\n";
}
if((!NumTraits<A::Scalar>::IsComplex) && (NumTraits<B::Scalar>::IsComplex))
{
M a(m,p); a.setRandom();
M br(p,n); br.setRandom();
M bi(p,n); bi.setRandom();
M cr(m,n); cr.setRandom();
M ci(m,n); ci.setRandom();
BenchTimer t;
BENCH(t, tries, rep, matlab_real_cplx(a,br,bi,cr,ci));
std::cout << "\"matlab\" cpu " << t.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << t.total(CPU_TIMER) << "s)\n";
std::cout << "\"matlab\" real " << t.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << t.total(REAL_TIMER) << "s)\n";
}
if((NumTraits<A::Scalar>::IsComplex) && (!NumTraits<B::Scalar>::IsComplex))
{
M ar(m,p); ar.setRandom();
M ai(m,p); ai.setRandom();
M b(p,n); b.setRandom();
M cr(m,n); cr.setRandom();
M ci(m,n); ci.setRandom();
BenchTimer t;
BENCH(t, tries, rep, matlab_cplx_real(ar,ai,b,cr,ci));
std::cout << "\"matlab\" cpu " << t.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << t.total(CPU_TIMER) << "s)\n";
std::cout << "\"matlab\" real " << t.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << t.total(REAL_TIMER) << "s)\n";
}
#endif
return 0;
}