mirror of
https://github.com/paboyle/Grid.git
synced 2024-09-19 16:55:37 +01:00
Eigen implementation and SYCL implementation
This commit is contained in:
Peter Boyle
parent
6ae52da571
commit
18d2d7da4a
@ -89,9 +89,10 @@ public:
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gridblasHandle = theGridAccelerator;
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#endif
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#ifdef GRID_ONE_MKL
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cl::sycl::cpu_selector selector;
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cl::sycl::gpu_selector selector;
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cl::sycl::device selectedDevice { selector };
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gridblasHandle =new sycl::queue (selectedDevice);
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cl::sycl::property_list q_prop{cl::sycl::property::queue::in_order()};
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gridblasHandle =new sycl::queue (selectedDevice,q_prop);
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#endif
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gridblasInit=1;
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}
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@ -207,6 +208,9 @@ public:
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assert(Bkn.size()==batchCount);
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assert(Cmn.size()==batchCount);
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assert(OpA!=GridBLAS_OP_T); // Complex case expect no transpose
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assert(OpB!=GridBLAS_OP_T);
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int lda = m; // m x k column major
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int ldb = k; // k x n column major
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int ldc = m; // m x b column major
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@ -266,26 +270,131 @@ public:
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assert(err==CUBLAS_STATUS_SUCCESS);
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#endif
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#ifdef GRID_SYCL
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//MKL’s cblas_<T>gemm_batch & OneAPI
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#warning "oneMKL implementation not built "
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#endif
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#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
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// Need a default/reference implementation
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int sda = lda*k;
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int sdb = ldb*k;
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int sdc = ldc*n;
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for (int p = 0; p < batchCount; ++p) {
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for (int mm = 0; mm < m; ++mm) {
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for (int nn = 0; nn < n; ++nn) {
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ComplexD c_mn(0.0);
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for (int kk = 0; kk < k; ++kk)
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c_mn += Amk[p][mm + kk*lda ] * Bkn[p][kk + nn*ldb];
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Cmn[p][mm + nn*ldc] = (alpha)*c_mn + (beta)*Cmn[p][mm + nn*ldc ];
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// std::cerr << " Calling SYCL batched ZGEMM "<<std::endl;
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int64_t m64=m;
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int64_t n64=n;
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int64_t k64=k;
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int64_t lda64=lda;
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int64_t ldb64=ldb;
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int64_t ldc64=ldc;
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int64_t batchCount64=batchCount;
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oneapi::mkl::transpose iOpA;
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oneapi::mkl::transpose iOpB;
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if ( OpA == GridBLAS_OP_N ) iOpA = oneapi::mkl::transpose::N;
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if ( OpA == GridBLAS_OP_T ) iOpA = oneapi::mkl::transpose::T;
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if ( OpA == GridBLAS_OP_C ) iOpA = oneapi::mkl::transpose::C;
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if ( OpB == GridBLAS_OP_N ) iOpB = oneapi::mkl::transpose::N;
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if ( OpB == GridBLAS_OP_T ) iOpB = oneapi::mkl::transpose::T;
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if ( OpB == GridBLAS_OP_C ) iOpB = oneapi::mkl::transpose::C;
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oneapi::mkl::blas::column_major::gemm_batch(*gridblasHandle,
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&iOpA,
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&iOpB,
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&m64,&n64,&k64,
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(ComplexD *) &alpha_p[0],
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(const ComplexD **)&Amk[0], (const int64_t *)&lda64,
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(const ComplexD **)&Bkn[0], (const int64_t *)&ldb64,
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(ComplexD *) &beta_p[0],
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(ComplexD **)&Cmn[0], (const int64_t *)&ldc64,
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(int64_t)1,&batchCount64,std::vector<sycl::event>());
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synchronise();
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#if 0
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// This code was used to check the mat mul on Sunspot/OneMKL
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std::cerr << " Called SYCL batched ZGEMM OpA "<< OpA << " OpB "<<OpB <<std::endl;
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std::vector<ComplexD> A(m*k); // pointer list to matrices
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std::vector<ComplexD> B(k*n);
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std::vector<ComplexD> C(m*n);
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// int sda = lda*k;
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// int sdb = ldb*k;
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// int sdc = ldc*n;
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std::cerr << " Checking the GEMM results "<<std::endl;
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for (int p = 0; p < 1; ++p) {
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ComplexD * Amk_p; // pointer list to matrices
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ComplexD * Bkn_p; // pointer list to matrices
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ComplexD * Cmn_p; // pointer list to matrices
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acceleratorCopyFromDevice((void *)&Amk[p],(void *)&Amk_p,sizeof(ComplexD*));
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acceleratorCopyFromDevice((void *)&Bkn[p],(void *)&Bkn_p,sizeof(ComplexD*));
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acceleratorCopyFromDevice((void *)&Cmn[p],(void *)&Cmn_p,sizeof(ComplexD*));
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std::cerr << " p " << p << " copied pointers "<<std::endl;
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acceleratorCopyFromDevice((void *)Amk_p,(void *)&A[0],m*k*sizeof(ComplexD));
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acceleratorCopyFromDevice((void *)Bkn_p,(void *)&B[0],k*n*sizeof(ComplexD));
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acceleratorCopyFromDevice((void *)Cmn_p,(void *)&C[0],m*n*sizeof(ComplexD));
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std::cerr << " p " << p << " copied matrices "<<std::endl;
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std::cerr << " C[0] "<<C[0]<<std::endl;
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std::cerr << " A[0] "<<A[0]<<std::endl;
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std::cerr << " B[0] "<<B[0]<<std::endl;
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std::cerr << " m "<<m<<std::endl;
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std::cerr << " n "<<n<<std::endl;
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std::cerr << " k "<<k<<std::endl;
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for (int mm = 0; mm < m; ++mm) {
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for (int nn = 0; nn < n; ++nn) {
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ComplexD c_mn(0.0);
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for (int kk = 0; kk < k; ++kk) {
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int idx_a, idx_b;
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// int lda = m; // m x k column major
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// int ldb = k; // k x n column major
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// int ldc = m; // m x b column major
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if(OpA!=GridBLAS_OP_N) {
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idx_a =kk + mm*lda;
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} else {
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idx_a =mm + kk*lda;
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}
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if(OpB!=GridBLAS_OP_N) {
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idx_b =nn + kk*ldb;
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} else {
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idx_b =kk + nn*ldb;
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}
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// std::cerr << " idx_a "<<idx_a<<" idx_b "<<idx_b<<std::endl;
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ComplexD Ac = A[idx_a];
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ComplexD Bc = B[idx_b];
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if(OpA==GridBLAS_OP_C) Ac = conjugate(Ac);
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if(OpB==GridBLAS_OP_C) Bc = conjugate(Bc);
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c_mn += Ac*Bc;
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}
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std::cerr << " beta "<<beta<<" alpha "<<alpha<<" C_"<<mm<<","<<nn<<" "<<c_mn<<" "<<C[mm + nn*ldc]<<std::endl;
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}
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}
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}
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}
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#endif
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// synchronise();
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#endif
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#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
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// Need a default/reference implementation; use Eigen
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if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_N) ) {
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thread_for (p, batchCount, {
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Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],m,k);
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Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],k,n);
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Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
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eCmn = beta * eCmn + alpha * eAmk * eBkn ;
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});
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} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_N) ) {
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thread_for (p, batchCount, {
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Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],k,m);
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Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],k,n);
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Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
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eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn ;
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});
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} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_C) ) {
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thread_for (p, batchCount, {
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Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],m,k);
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Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],n,k);
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Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
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eCmn = beta * eCmn + alpha * eAmk * eBkn.adjoint() ;
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});
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} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_C) ) {
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thread_for (p, batchCount, {
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Eigen::Map<Eigen::MatrixXcd> eAmk(Amk[p],k,m);
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Eigen::Map<Eigen::MatrixXcd> eBkn(Bkn[p],n,k);
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Eigen::Map<Eigen::MatrixXcd> eCmn(Cmn[p],m,n);
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eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn.adjoint() ;
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} );
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} else {
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assert(0);
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}
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#endif
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RealD t1=usecond();
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RealD flops = 8.0*m*n*k*batchCount;
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RealD bytes = 1.0*sizeof(ComplexD)*(m*k+k*n+m*n)*batchCount;
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@ -306,6 +415,9 @@ public:
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RealD t2=usecond();
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int32_t batchCount = Amk.size();
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assert(OpA!=GridBLAS_OP_T); // Complex case expect no transpose
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assert(OpB!=GridBLAS_OP_T);
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int lda = m; // m x k column major
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int ldb = k; // k x n column major
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int ldc = m; // m x b column major
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@ -366,26 +478,69 @@ public:
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assert(err==CUBLAS_STATUS_SUCCESS);
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#endif
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#ifdef GRID_SYCL
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//MKL’s cblas_<T>gemm_batch & OneAPI
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#warning "oneMKL implementation not built "
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int64_t m64=m;
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int64_t n64=n;
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int64_t k64=k;
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int64_t lda64=lda;
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int64_t ldb64=ldb;
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int64_t ldc64=ldc;
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int64_t batchCount64=batchCount;
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oneapi::mkl::transpose iOpA;
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oneapi::mkl::transpose iOpB;
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if ( OpA == GridBLAS_OP_N ) iOpA = oneapi::mkl::transpose::N;
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if ( OpA == GridBLAS_OP_T ) iOpA = oneapi::mkl::transpose::T;
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if ( OpA == GridBLAS_OP_C ) iOpA = oneapi::mkl::transpose::C;
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if ( OpB == GridBLAS_OP_N ) iOpB = oneapi::mkl::transpose::N;
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if ( OpB == GridBLAS_OP_T ) iOpB = oneapi::mkl::transpose::T;
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if ( OpB == GridBLAS_OP_C ) iOpB = oneapi::mkl::transpose::C;
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oneapi::mkl::blas::column_major::gemm_batch(*gridblasHandle,
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&iOpA,
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&iOpB,
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&m64,&n64,&k64,
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(ComplexF *) &alpha_p[0],
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(const ComplexF **)&Amk[0], (const int64_t *)&lda64,
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(const ComplexF **)&Bkn[0], (const int64_t *)&ldb64,
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(ComplexF *) &beta_p[0],
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(ComplexF **)&Cmn[0], (const int64_t *)&ldc64,
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(int64_t)1,&batchCount64,std::vector<sycl::event>());
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synchronise();
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#endif
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#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
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int sda = lda*k;
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int sdb = ldb*k;
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int sdc = ldc*n;
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ComplexF alphaf(real(alpha),imag(alpha));
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ComplexF betaf(real(beta),imag(beta));
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// Need a default/reference implementation
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for (int p = 0; p < batchCount; ++p) {
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for (int mm = 0; mm < m; ++mm) {
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for (int nn = 0; nn < n; ++nn) {
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ComplexF c_mn(0.0);
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for (int kk = 0; kk < k; ++kk)
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c_mn += Amk[p][mm + kk*lda ] * Bkn[p][kk + nn*ldb];
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Cmn[p][mm + nn*ldc] = (alphaf)*c_mn + (betaf)*Cmn[p][mm + nn*ldc ];
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}
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// Need a default/reference implementation; use Eigen
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if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_N) ) {
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thread_for (p, batchCount, {
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Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],m,k);
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Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],k,n);
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Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
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eCmn = beta * eCmn + alpha * eAmk * eBkn ;
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});
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} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_N) ) {
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thread_for (p, batchCount, {
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Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],k,m);
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Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],k,n);
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Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
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eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn ;
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});
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} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_C) ) {
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thread_for (p, batchCount, {
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Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],m,k);
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Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],n,k);
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Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
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eCmn = beta * eCmn + alpha * eAmk * eBkn.adjoint() ;
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});
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} else if ( (OpA == GridBLAS_OP_C ) && (OpB == GridBLAS_OP_C) ) {
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thread_for (p, batchCount, {
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Eigen::Map<Eigen::MatrixXcf> eAmk(Amk[p],k,m);
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Eigen::Map<Eigen::MatrixXcf> eBkn(Bkn[p],n,k);
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Eigen::Map<Eigen::MatrixXcf> eCmn(Cmn[p],m,n);
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eCmn = beta * eCmn + alpha * eAmk.adjoint() * eBkn.adjoint() ;
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} );
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} else {
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assert(0);
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}
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}
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#endif
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RealD t1=usecond();
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RealD flops = 8.0*m*n*k*batchCount;
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@ -408,6 +563,9 @@ public:
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RealD t2=usecond();
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int32_t batchCount = Amk.size();
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assert(OpA!=GridBLAS_OP_C); // Real case no conjugate
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assert(OpB!=GridBLAS_OP_C);
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int lda = m; // m x k column major
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int ldb = k; // k x n column major
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int ldc = m; // m x b column major
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@ -467,24 +625,69 @@ public:
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assert(err==CUBLAS_STATUS_SUCCESS);
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#endif
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#ifdef GRID_SYCL
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//MKL’s cblas_<T>gemm_batch & OneAPI
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#warning "oneMKL implementation not built "
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int64_t m64=m;
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int64_t n64=n;
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int64_t k64=k;
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int64_t lda64=lda;
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int64_t ldb64=ldb;
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int64_t ldc64=ldc;
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int64_t batchCount64=batchCount;
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oneapi::mkl::transpose iOpA;
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oneapi::mkl::transpose iOpB;
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if ( OpA == GridBLAS_OP_N ) iOpA = oneapi::mkl::transpose::N;
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if ( OpA == GridBLAS_OP_T ) iOpA = oneapi::mkl::transpose::T;
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if ( OpA == GridBLAS_OP_C ) iOpA = oneapi::mkl::transpose::C;
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if ( OpB == GridBLAS_OP_N ) iOpB = oneapi::mkl::transpose::N;
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if ( OpB == GridBLAS_OP_T ) iOpB = oneapi::mkl::transpose::T;
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if ( OpB == GridBLAS_OP_C ) iOpB = oneapi::mkl::transpose::C;
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oneapi::mkl::blas::column_major::gemm_batch(*gridblasHandle,
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&iOpA,
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&iOpB,
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&m64,&n64,&k64,
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(float *) &alpha_p[0],
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(const float **)&Amk[0], (const int64_t *)&lda64,
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(const float **)&Bkn[0], (const int64_t *)&ldb64,
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(float *) &beta_p[0],
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(float **)&Cmn[0], (const int64_t *)&ldc64,
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(int64_t)1,&batchCount64,std::vector<sycl::event>());
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synchronise();
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#endif
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#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
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int sda = lda*k;
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int sdb = ldb*k;
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int sdc = ldc*n;
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// Need a default/reference implementation
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for (int p = 0; p < batchCount; ++p) {
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for (int mm = 0; mm < m; ++mm) {
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for (int nn = 0; nn < n; ++nn) {
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RealD c_mn(0.0);
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for (int kk = 0; kk < k; ++kk)
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c_mn += Amk[p][mm + kk*lda ] * Bkn[p][kk + nn*ldb];
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Cmn[p][mm + nn*ldc] = (alpha)*c_mn + (beta)*Cmn[p][mm + nn*ldc ];
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}
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// Need a default/reference implementation; use Eigen
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if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_N) ) {
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thread_for (p, batchCount, {
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Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],m,k);
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Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],k,n);
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Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
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eCmn = beta * eCmn + alpha * eAmk * eBkn ;
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});
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} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_N) ) {
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thread_for (p, batchCount, {
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Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],k,m);
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Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],k,n);
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Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
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eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn ;
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});
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} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_T) ) {
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thread_for (p, batchCount, {
|
||||
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],m,k);
|
||||
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],n,k);
|
||||
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
|
||||
eCmn = beta * eCmn + alpha * eAmk * eBkn.transpose() ;
|
||||
});
|
||||
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_T) ) {
|
||||
thread_for (p, batchCount, {
|
||||
Eigen::Map<Eigen::MatrixXf> eAmk(Amk[p],k,m);
|
||||
Eigen::Map<Eigen::MatrixXf> eBkn(Bkn[p],n,k);
|
||||
Eigen::Map<Eigen::MatrixXf> eCmn(Cmn[p],m,n);
|
||||
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn.transpose() ;
|
||||
} );
|
||||
} else {
|
||||
assert(0);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
RealD t1=usecond();
|
||||
RealD flops = 2.0*m*n*k*batchCount;
|
||||
@ -495,7 +698,6 @@ public:
|
||||
///////////////////////////////////////////////////////////////////////////
|
||||
// Double precision real GEMM
|
||||
///////////////////////////////////////////////////////////////////////////
|
||||
|
||||
void gemmBatched(GridBLASOperation_t OpA,
|
||||
GridBLASOperation_t OpB,
|
||||
int m,int n, int k,
|
||||
@ -508,6 +710,9 @@ public:
|
||||
RealD t2=usecond();
|
||||
int32_t batchCount = Amk.size();
|
||||
|
||||
assert(OpA!=GridBLAS_OP_C); // Real case no conjugate
|
||||
assert(OpB!=GridBLAS_OP_C);
|
||||
|
||||
int lda = m; // m x k column major
|
||||
int ldb = k; // k x n column major
|
||||
int ldc = m; // m x b column major
|
||||
@ -568,160 +773,115 @@ public:
|
||||
assert(err==CUBLAS_STATUS_SUCCESS);
|
||||
#endif
|
||||
#ifdef GRID_SYCL
|
||||
/*
|
||||
int64_t m64=m;
|
||||
int64_t n64=n;
|
||||
int64_t k64=k;
|
||||
int64_t lda64=lda;
|
||||
int64_t ldb64=ldb;
|
||||
int64_t ldc64=ldc;
|
||||
int64_t batchCount64=batchCount;
|
||||
oneapi::mkl::blas::column_major::gemm_batch(*theGridAccelerator,
|
||||
onemkl::transpose::N,
|
||||
onemkl::transpose::N,
|
||||
&m64,&n64,&k64,
|
||||
(double *) &alpha_p[0],
|
||||
(double **)&Amk[0], lda,
|
||||
(double **)&Bkn[0], ldb,
|
||||
(double *) &beta_p[0],
|
||||
(double **)&Cmn[0], ldc,
|
||||
1,&batchCount64);
|
||||
*/
|
||||
//MKL’s cblas_<T>gemm_batch & OneAPI
|
||||
#warning "oneMKL implementation not built "
|
||||
|
||||
oneapi::mkl::transpose iOpA;
|
||||
oneapi::mkl::transpose iOpB;
|
||||
|
||||
if ( OpA == GridBLAS_OP_N ) iOpA = oneapi::mkl::transpose::N;
|
||||
if ( OpA == GridBLAS_OP_T ) iOpA = oneapi::mkl::transpose::T;
|
||||
if ( OpA == GridBLAS_OP_C ) iOpA = oneapi::mkl::transpose::C;
|
||||
if ( OpB == GridBLAS_OP_N ) iOpB = oneapi::mkl::transpose::N;
|
||||
if ( OpB == GridBLAS_OP_T ) iOpB = oneapi::mkl::transpose::T;
|
||||
if ( OpB == GridBLAS_OP_C ) iOpB = oneapi::mkl::transpose::C;
|
||||
|
||||
oneapi::mkl::blas::column_major::gemm_batch(*gridblasHandle,
|
||||
&iOpA,
|
||||
&iOpB,
|
||||
&m64,&n64,&k64,
|
||||
(double *) &alpha_p[0],
|
||||
(const double **)&Amk[0], (const int64_t *)&lda64,
|
||||
(const double **)&Bkn[0], (const int64_t *)&ldb64,
|
||||
(double *) &beta_p[0],
|
||||
(double **)&Cmn[0], (const int64_t *)&ldc64,
|
||||
(int64_t)1,&batchCount64,std::vector<sycl::event>());
|
||||
synchronise();
|
||||
#endif
|
||||
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP)
|
||||
int sda = lda*k;
|
||||
int sdb = ldb*k;
|
||||
int sdc = ldc*n;
|
||||
// Need a default/reference implementation
|
||||
for (int p = 0; p < batchCount; ++p) {
|
||||
for (int mm = 0; mm < m; ++mm) {
|
||||
for (int nn = 0; nn < n; ++nn) {
|
||||
RealD c_mn(0.0);
|
||||
for (int kk = 0; kk < k; ++kk)
|
||||
c_mn += Amk[p][mm + kk*lda ] * Bkn[p][kk + nn*ldb];
|
||||
Cmn[p][mm + nn*ldc] = (alpha)*c_mn + (beta)*Cmn[p][mm + nn*ldc ];
|
||||
}
|
||||
// Need a default/reference implementation; use Eigen
|
||||
if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_N) ) {
|
||||
thread_for (p, batchCount, {
|
||||
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],m,k);
|
||||
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],k,n);
|
||||
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
|
||||
eCmn = beta * eCmn + alpha * eAmk * eBkn ;
|
||||
});
|
||||
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_N) ) {
|
||||
thread_for (p, batchCount, {
|
||||
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],k,m);
|
||||
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],k,n);
|
||||
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
|
||||
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn ;
|
||||
});
|
||||
} else if ( (OpA == GridBLAS_OP_N ) && (OpB == GridBLAS_OP_T) ) {
|
||||
thread_for (p, batchCount, {
|
||||
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],m,k);
|
||||
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],n,k);
|
||||
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
|
||||
eCmn = beta * eCmn + alpha * eAmk * eBkn.transpose() ;
|
||||
});
|
||||
} else if ( (OpA == GridBLAS_OP_T ) && (OpB == GridBLAS_OP_T) ) {
|
||||
thread_for (p, batchCount, {
|
||||
Eigen::Map<Eigen::MatrixXd> eAmk(Amk[p],k,m);
|
||||
Eigen::Map<Eigen::MatrixXd> eBkn(Bkn[p],n,k);
|
||||
Eigen::Map<Eigen::MatrixXd> eCmn(Cmn[p],m,n);
|
||||
eCmn = beta * eCmn + alpha * eAmk.transpose() * eBkn.transpose() ;
|
||||
});
|
||||
} else {
|
||||
assert(0);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
RealD t1=usecond();
|
||||
RealD flops = 2.0*m*n*k*batchCount;
|
||||
RealD bytes = 1.0*sizeof(RealD)*(m*k+k*n+m*n)*batchCount;
|
||||
}
|
||||
|
||||
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////////////////////
|
||||
// Strided case used by benchmark, but generally unused in Grid
|
||||
// Keep a code example in double complex, but don't generate the single and real variants for now
|
||||
////////////////////////////////////////////////////////////////////////////////////////////////
|
||||
|
||||
void gemmStridedBatched(int m,int n, int k,
|
||||
ComplexD alpha,
|
||||
ComplexD* Amk, // pointer list to matrices
|
||||
ComplexD* Bkn,
|
||||
ComplexD beta,
|
||||
ComplexD* Cmn,
|
||||
int batchCount)
|
||||
{
|
||||
// Use C-row major storage, so transpose calls
|
||||
int lda = m; // m x k column major
|
||||
int ldb = k; // k x n column major
|
||||
int ldc = m; // m x b column major
|
||||
int sda = m*k;
|
||||
int sdb = k*n;
|
||||
int sdc = m*n;
|
||||
deviceVector<ComplexD> alpha_p(1);
|
||||
deviceVector<ComplexD> beta_p(1);
|
||||
acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(ComplexD));
|
||||
acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(ComplexD));
|
||||
// std::cout << "blasZgemmStridedBatched mnk "<<m<<","<<n<<","<<k<<" count "<<batchCount<<std::endl;
|
||||
// std::cout << "blasZgemmStridedBatched ld "<<lda<<","<<ldb<<","<<ldc<<std::endl;
|
||||
// std::cout << "blasZgemmStridedBatched sd "<<sda<<","<<sdb<<","<<sdc<<std::endl;
|
||||
#ifdef GRID_HIP
|
||||
auto err = hipblasZgemmStridedBatched(gridblasHandle,
|
||||
HIPBLAS_OP_N,
|
||||
HIPBLAS_OP_N,
|
||||
m,n,k,
|
||||
(hipblasDoubleComplex *) &alpha_p[0],
|
||||
(hipblasDoubleComplex *) Amk, lda, sda,
|
||||
(hipblasDoubleComplex *) Bkn, ldb, sdb,
|
||||
(hipblasDoubleComplex *) &beta_p[0],
|
||||
(hipblasDoubleComplex *) Cmn, ldc, sdc,
|
||||
batchCount);
|
||||
assert(err==HIPBLAS_STATUS_SUCCESS);
|
||||
#endif
|
||||
#ifdef GRID_CUDA
|
||||
cublasZgemmStridedBatched(gridblasHandle,
|
||||
CUBLAS_OP_N,
|
||||
CUBLAS_OP_N,
|
||||
m,n,k,
|
||||
(cuDoubleComplex *) &alpha_p[0],
|
||||
(cuDoubleComplex *) Amk, lda, sda,
|
||||
(cuDoubleComplex *) Bkn, ldb, sdb,
|
||||
(cuDoubleComplex *) &beta_p[0],
|
||||
(cuDoubleComplex *) Cmn, ldc, sdc,
|
||||
batchCount);
|
||||
#endif
|
||||
#if defined(GRID_SYCL) || defined(GRID_ONE_MKL)
|
||||
oneapi::mkl::blas::column_major::gemm_batch(*gridblasHandle,
|
||||
oneapi::mkl::transpose::N,
|
||||
oneapi::mkl::transpose::N,
|
||||
m,n,k,
|
||||
alpha,
|
||||
(const ComplexD *)Amk,lda,sda,
|
||||
(const ComplexD *)Bkn,ldb,sdb,
|
||||
beta,
|
||||
(ComplexD *)Cmn,ldc,sdc,
|
||||
batchCount);
|
||||
#endif
|
||||
#if !defined(GRID_SYCL) && !defined(GRID_CUDA) && !defined(GRID_HIP) && !defined(GRID_ONE_MKL)
|
||||
// Need a default/reference implementation
|
||||
for (int p = 0; p < batchCount; ++p) {
|
||||
for (int mm = 0; mm < m; ++mm) {
|
||||
for (int nn = 0; nn < n; ++nn) {
|
||||
ComplexD c_mn(0.0);
|
||||
for (int kk = 0; kk < k; ++kk)
|
||||
c_mn += Amk[mm + kk*lda + p*sda] * Bkn[kk + nn*ldb + p*sdb];
|
||||
Cmn[mm + nn*ldc + p*sdc] = (alpha)*c_mn + (beta)*Cmn[mm + nn*ldc + p*sdc];
|
||||
}
|
||||
}
|
||||
}
|
||||
#endif
|
||||
}
|
||||
|
||||
template<class CComplex>
|
||||
double benchmark(int M, int N, int K, int BATCH)
|
||||
{
|
||||
int32_t N_A = M*K*BATCH;
|
||||
int32_t N_B = K*N*BATCH;
|
||||
int32_t N_C = M*N*BATCH;
|
||||
deviceVector<ComplexD> A(N_A); acceleratorMemSet(&A[0],0,N_A*sizeof(ComplexD));
|
||||
deviceVector<ComplexD> B(N_B); acceleratorMemSet(&B[0],0,N_B*sizeof(ComplexD));
|
||||
deviceVector<ComplexD> C(N_C); acceleratorMemSet(&C[0],0,N_C*sizeof(ComplexD));
|
||||
ComplexD alpha(1.0);
|
||||
ComplexD beta (1.0);
|
||||
deviceVector<CComplex> A(N_A); acceleratorMemSet(&A[0],0,N_A*sizeof(CComplex));
|
||||
deviceVector<CComplex> B(N_B); acceleratorMemSet(&B[0],0,N_B*sizeof(CComplex));
|
||||
deviceVector<CComplex> C(N_C); acceleratorMemSet(&C[0],0,N_C*sizeof(CComplex));
|
||||
CComplex alpha(1.0);
|
||||
CComplex beta (1.0);
|
||||
RealD flops = 8.0*M*N*K*BATCH;
|
||||
int ncall=10;
|
||||
RealD t0 = usecond();
|
||||
deviceVector<CComplex *> As(BATCH);
|
||||
deviceVector<CComplex *> Bs(BATCH);
|
||||
deviceVector<CComplex *> Cs(BATCH);
|
||||
for(int b = 0 ; b < BATCH;b++) {
|
||||
CComplex *ptr;
|
||||
ptr = &A[b*M*K]; acceleratorPut(As[b],ptr);
|
||||
ptr = &B[b*K*N]; acceleratorPut(Bs[b],ptr);
|
||||
ptr = &C[b*M*N]; acceleratorPut(Cs[b],ptr);
|
||||
}
|
||||
|
||||
for(int i=0;i<ncall;i++){
|
||||
gemmStridedBatched(M,N,K,
|
||||
alpha,
|
||||
&A[0], // m x k
|
||||
&B[0], // k x n
|
||||
beta,
|
||||
&C[0], // m x n
|
||||
BATCH);
|
||||
gemmBatched(M,N,K,
|
||||
alpha,
|
||||
As, // m x k
|
||||
Bs, // k x n
|
||||
beta,
|
||||
Cs);
|
||||
}
|
||||
synchronise();
|
||||
RealD t1 = usecond();
|
||||
RealD bytes = 1.0*sizeof(ComplexD)*(M*N*2+N*K+M*K)*BATCH;
|
||||
RealD bytes = 1.0*sizeof(CComplex)*(M*N*2+N*K+M*K)*BATCH;
|
||||
flops = 8.0*M*N*K*BATCH*ncall;
|
||||
flops = flops/(t1-t0)/1.e3;
|
||||
return flops; // Returns gigaflops
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
};
|
||||
|
||||
NAMESPACE_END(Grid);
|
||||
|
||||
Loading…
Reference in New Issue
Block a user