Complex Tensor Contractions are unusually slow

[mganahl]

Hi Devin, Thanks for this nice library!

I'm currently testing the library, and I found the following: For real tensors, tblis is substantially faster than a contraction using dgemm for the cases I tested. For double matrices, dgemm and tblis are about equal. For a test case of 1000 matrix multiplications of two 200 x 200 matrices, a timing gives (using OMP_NUM_THREADS=4 on a 4 core machine)

TBLIS: fastest of 1000 contractions: 281 microseconds TBLIS: average time per contraction: 390.587 microseconds DGEMM: fastest of 1000 contractions: 311 microseconds DGEMM: average time per contraction: 332.135 microseconds

For complex types however, the contractions are actually much slower than when using zgemm. When I compile and run the code below (1000 matrix multiplications of two 200 x 200 matrices), I get the following output:

TBLIS: fastest of 1000 contractions: 14917 microseconds TBLIS: average time per contraction: 15622.9 microseconds ZGEMM: fastest of 1000 contractions: 932 microseconds ZGEMM: average time per contraction: 1053.49 microseconds

Is this to be expected, or am I doing something wrong? I was building with g++ 5 o and comparing to zgemm implementation from openblas.

thanks!

Below, mat_mat_prod is a wrapper around zgemm;

#include #include <tblis.h> #include "lib/linalg/blasroutines.hpp" typedef double Real; typedef complex Complex;

using std::cout; using std::endl; using std::vector;

int main(int argc, char** argv){

int d1=200,d2=200,d3=200; vector < tblis::label_type > la={1,2}; vector < tblis::label_type > lb={2,3}; vector < tblis::label_type > lc={1,3}; tblis::tensor < Complex> A({d1,d2}); tblis::tensor < Complex> B({d2,d3}); tblis::tensor < Complex > C({d1,d3}); Complex beta=0.0; Complex alpha=1.0; auto mA=new Complex [d1d2]; auto mB=new Complex [d2d3]; auto mC=new Complex [d1*d3]; int Nmax=1000; vector time(Nmax); vector time2(Nmax); cout<<"doing TBLIS contraction"<<endl; for(uint n=0;n<Nmax;n++){ auto time0 = std::chrono::high_resolution_clock::now(); tblis::mult(alpha,A,la.data(),B,lb.data(),beta,C,lc.data()); auto time1 = std::chrono::high_resolution_clock::now(); time[n]=std::chrono::duration_caststd::chrono::microseconds(time1-time0).count(); } cout<<"doing ZGEMM contraction"<<endl; for(uint n=0;n<Nmax;n++){ auto time0 = std::chrono::high_resolution_clock::now(); blasroutines::mat_mat_prod(alpha,mA ,d1,d2,mB,d2,d3,mC,'N','N'); auto time1 = std::chrono::high_resolution_clock::now(); time2[n]=std::chrono::duration_caststd::chrono::microseconds(time1-time0).count(); } cout<< "TBLIS: fastest of "<<Nmax<<" contractions: "<<*std::min_element(time.begin(),time.end()) << " microseconds\n"; cout<< "TBLIS: average time per contraction: "<<std::accumulate(time.begin(),time.end(),0.0)*1.0/Nmax << " microseconds\n"; cout<< "ZGEMM: fastest of "<<Nmax<<" contractions: "<<*std::min_element(time2.begin(),time2.end()) << " microseconds\n"; cout<< "ZGEMM: average time per contraction: "<<std::accumulate(time2.begin(),time2.end(),0.0)*1.0/Nmax << " microseconds\n";

delete[] mA; delete[] mB; delete[] mC; return 0; }

[devinamatthews]

The problem is that TBLIS doesn't currently include optimized complex microkernels for most architectures. Basically you are getting a slightly fancy triple loop for these cases.

The approach that I had planned to take is the "1m" method, where the real microkernels are reused by cleverly packing the real and imaginary parts of the complex operands. This hasn't been implemented yet, but perhaps soon.