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https://github.com/paboyle/Grid.git
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Batched blas
This commit is contained in:
Peter Boyle
parent
b19ae8f465
commit
e1d0a7cec3
@ -55,9 +55,12 @@ NAMESPACE_BEGIN(Grid);
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typedef int32_t gridblasHandle_t;
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#endif
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enum GridBLASOperation_t { GridBLAS_OP_N, GridBLAS_OP_T, GridBLAS_OP_C } ;
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class GridBLAS {
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public:
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static gridblasHandle_t gridblasHandle;
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static int gridblasInit;
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@ -109,37 +112,71 @@ public:
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accelerator_barrier();
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#endif
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}
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void benchmark(int nbasis, int nrhs, int coarseVol, int nstencil)
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void gemmBatched(int m,int n, int k,
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ComplexD alpha,
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deviceVector<ComplexD*> &Amk, // pointer list to matrices
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deviceVector<ComplexD*> &Bkn,
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ComplexD beta,
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deviceVector<ComplexD*> &Cmn)
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{
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int32_t N_A = nbasis*nbasis*coarseVol*nstencil;
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int32_t N_B = nbasis*nrhs*coarseVol*nstencil; // One leg of stencil at a time
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int32_t N_C = nbasis*nrhs*coarseVol*nstencil;
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deviceVector<ComplexD> A(N_A); acceleratorMemSet(&A[0],0,N_A*sizeof(ComplexD));
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deviceVector<ComplexD> B(N_B); acceleratorMemSet(&B[0],0,N_B*sizeof(ComplexD));
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deviceVector<ComplexD> C(N_C); acceleratorMemSet(&C[0],0,N_C*sizeof(ComplexD));
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ComplexD alpha(1.0);
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ComplexD beta (1.0);
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for(int i=0;i<10;i++){
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RealD t0 = usecond();
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for(int s=0;s<nstencil;s++){
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gemmStridedBatched(nbasis,nrhs,nbasis,
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alpha,
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&A[0], // m x k
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&B[0], // k x n
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beta,
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&C[0], // m x n
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coarseVol);
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}
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synchronise();
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RealD t1 = usecond();
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RealD flops = 8.0*nbasis*nbasis*nrhs*coarseVol*nstencil;
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RealD bytes = 1.0*sizeof(ComplexD)*(nbasis*nbasis+nbasis*nrhs*3)*coarseVol*nstencil;
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std::cout << " batched Blas call "<<i<<" "<< flops/(t1-t0)/1.e3 <<" GF/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
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std::cout << " batched Blas call "<<i<<" "<< bytes/(t1-t0)/1.e3 <<" GB/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
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}
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gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
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m,n,k,
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alpha,
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Amk,
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Bkn,
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beta,
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Cmn);
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}
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void gemmBatched(int m,int n, int k,
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ComplexF alpha,
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deviceVector<ComplexF*> &Amk, // pointer list to matrices
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deviceVector<ComplexF*> &Bkn,
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ComplexF beta,
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deviceVector<ComplexF*> &Cmn)
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{
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gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
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m,n,k,
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alpha,
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Amk,
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Bkn,
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beta,
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Cmn);
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}
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void gemmBatched(int m,int n, int k,
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RealD alpha,
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deviceVector<RealD*> &Amk, // pointer list to matrices
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deviceVector<RealD*> &Bkn,
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RealD beta,
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deviceVector<RealD*> &Cmn)
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{
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gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
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m,n,k,
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alpha,
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Amk,
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Bkn,
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beta,
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Cmn);
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}
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void gemmBatched(int m,int n, int k,
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RealF alpha,
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deviceVector<RealF*> &Amk, // pointer list to matrices
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deviceVector<RealF*> &Bkn,
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RealF beta,
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deviceVector<RealF*> &Cmn)
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{
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gemmBatched(GridBLAS_OP_N,GridBLAS_OP_N,
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m,n,k,
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alpha,
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Amk,
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Bkn,
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beta,
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Cmn);
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}
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void gemmBatched(int m,int n, int k,
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void gemmBatched(GridBLASOperation_t OpA,
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GridBLASOperation_t OpB,
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int m,int n, int k,
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ComplexD alpha,
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deviceVector<ComplexD*> &Amk, // pointer list to matrices
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deviceVector<ComplexD*> &Bkn,
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@ -148,23 +185,36 @@ public:
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{
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RealD t2=usecond();
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int32_t batchCount = Amk.size();
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// Use C-row major storage, so transpose calls
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assert(Bkn.size()==batchCount);
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assert(Cmn.size()==batchCount);
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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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lda = k;
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if(OpB!=GridBLAS_OP_N)
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ldb = n;
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static deviceVector<ComplexD> alpha_p(1);
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static deviceVector<ComplexD> beta_p(1);
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// can prestore the 1 and the zero on device
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acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(ComplexD));
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acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(ComplexD));
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RealD t0=usecond();
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// std::cout << "hipblasZgemmBatched mnk "<<m<<","<<n<<","<<k<<" count "<<batchCount<<std::endl;
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assert(Bkn.size()==batchCount);
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assert(Cmn.size()==batchCount);
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// std::cout << "ZgemmBatched mnk "<<m<<","<<n<<","<<k<<" count "<<batchCount<<std::endl;
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#ifdef GRID_HIP
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hipblasOperation_t hOpA;
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hipblasOperation_t hOpB;
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if ( OpA == GridBLAS_OP_N ) hOpA = HIPBLAS_OP_N;
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if ( OpA == GridBLAS_OP_T ) hOpA = HIPBLAS_OP_T;
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if ( OpA == GridBLAS_OP_C ) hOpA = HIPBLAS_OP_C;
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if ( OpB == GridBLAS_OP_N ) hOpB = HIPBLAS_OP_N;
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if ( OpB == GridBLAS_OP_T ) hOpB = HIPBLAS_OP_T;
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if ( OpB == GridBLAS_OP_C ) hOpB = HIPBLAS_OP_C;
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auto err = hipblasZgemmBatched(gridblasHandle,
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HIPBLAS_OP_N,
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HIPBLAS_OP_N,
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hOpA,
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hOpB,
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m,n,k,
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(hipblasDoubleComplex *) &alpha_p[0],
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(hipblasDoubleComplex **)&Amk[0], lda,
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@ -176,9 +226,17 @@ public:
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assert(err==HIPBLAS_STATUS_SUCCESS);
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#endif
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#ifdef GRID_CUDA
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cublasOperation_t hOpA;
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cublasOperation_t hOpB;
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if ( OpA == GridBLAS_OP_N ) hOpA = CUBLAS_OP_N;
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if ( OpA == GridBLAS_OP_T ) hOpA = CUBLAS_OP_T;
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if ( OpA == GridBLAS_OP_C ) hOpA = CUBLAS_OP_C;
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if ( OpB == GridBLAS_OP_N ) hOpB = CUBLAS_OP_N;
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if ( OpB == GridBLAS_OP_T ) hOpB = CUBLAS_OP_T;
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if ( OpB == GridBLAS_OP_C ) hOpB = CUBLAS_OP_C;
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auto err = cublasZgemmBatched(gridblasHandle,
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CUBLAS_OP_N,
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CUBLAS_OP_N,
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hOpA,
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hOpB,
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m,n,k,
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(cuDoubleComplex *) &alpha_p[0],
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(cuDoubleComplex **)&Amk[0], lda,
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@ -205,15 +263,18 @@ public:
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}
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}
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#endif
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// synchronise();
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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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// std::cout <<GridLogPerformance<< " batched Blas copy "<<(t0-t2)/1.e3 <<" ms "<<std::endl;
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// std::cout <<GridLogPerformance<< " batched Blas call "<<m<<","<<n<<","<<k<<" "<< flops/(t1-t0)/1.e3 <<" GF/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
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// std::cout <<GridLogPerformance<< " batched Blas call "<<m<<","<<n<<","<<k<<" "<< bytes/(t1-t0)/1.e3 <<" GB/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
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// std::cout <<GridLogMessage<< " batched Blas copy "<<(t0-t2)/1.e3 <<" ms "<<std::endl;
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// std::cout <<GridLogMessage<< " batched Blas zGemm call "<<m<<","<<n<<","<<k<<" "<< flops/(t1-t0)/1.e3 <<" GF/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
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// std::cout <<GridLogMessage<< " batched Blas zGemm call "<<m<<","<<n<<","<<k<<" "<< bytes/(t1-t0)/1.e3 <<" GB/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
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}
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void gemmBatched(int m,int n, int k,
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void gemmBatched(GridBLASOperation_t OpA,
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GridBLASOperation_t OpB,
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int m,int n, int k,
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ComplexF alpha,
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deviceVector<ComplexF*> &Amk, // pointer list to matrices
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deviceVector<ComplexF*> &Bkn,
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@ -222,23 +283,35 @@ public:
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{
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RealD t2=usecond();
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int32_t batchCount = Amk.size();
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// Use C-row major storage, so transpose calls
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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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lda = k;
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if(OpB!=GridBLAS_OP_N)
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ldb = n;
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static deviceVector<ComplexF> alpha_p(1);
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static deviceVector<ComplexF> beta_p(1);
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// can prestore the 1 and the zero on device
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acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(ComplexF));
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acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(ComplexF));
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RealD t0=usecond();
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// std::cout << "hipblasZgemmBatched mnk "<<m<<","<<n<<","<<k<<" count "<<batchCount<<std::endl;
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assert(Bkn.size()==batchCount);
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assert(Cmn.size()==batchCount);
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#ifdef GRID_HIP
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hipblasOperation_t hOpA;
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hipblasOperation_t hOpB;
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if ( OpA == GridBLAS_OP_N ) hOpA = HIPBLAS_OP_N;
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if ( OpA == GridBLAS_OP_T ) hOpA = HIPBLAS_OP_T;
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if ( OpA == GridBLAS_OP_C ) hOpA = HIPBLAS_OP_C;
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if ( OpB == GridBLAS_OP_N ) hOpB = HIPBLAS_OP_N;
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if ( OpB == GridBLAS_OP_T ) hOpB = HIPBLAS_OP_T;
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if ( OpB == GridBLAS_OP_C ) hOpB = HIPBLAS_OP_C;
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auto err = hipblasCgemmBatched(gridblasHandle,
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HIPBLAS_OP_N,
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HIPBLAS_OP_N,
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hOpA,
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hOpB,
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m,n,k,
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(hipblasComplex *) &alpha_p[0],
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(hipblasComplex **)&Amk[0], lda,
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@ -246,13 +319,21 @@ public:
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(hipblasComplex *) &beta_p[0],
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(hipblasComplex **)&Cmn[0], ldc,
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batchCount);
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// std::cout << " hipblas return code " <<(int)err<<std::endl;
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assert(err==HIPBLAS_STATUS_SUCCESS);
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#endif
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#ifdef GRID_CUDA
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cublasOperation_t hOpA;
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cublasOperation_t hOpB;
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if ( OpA == GridBLAS_OP_N ) hOpA = CUBLAS_OP_N;
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if ( OpA == GridBLAS_OP_T ) hOpA = CUBLAS_OP_T;
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if ( OpA == GridBLAS_OP_C ) hOpA = CUBLAS_OP_C;
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if ( OpB == GridBLAS_OP_N ) hOpB = CUBLAS_OP_N;
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if ( OpB == GridBLAS_OP_T ) hOpB = CUBLAS_OP_T;
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if ( OpB == GridBLAS_OP_C ) hOpB = CUBLAS_OP_C;
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auto err = cublasCgemmBatched(gridblasHandle,
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CUBLAS_OP_N,
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CUBLAS_OP_N,
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hOpA,
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hOpB,
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m,n,k,
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(cuComplex *) &alpha_p[0],
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(cuComplex **)&Amk[0], lda,
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@ -282,16 +363,15 @@ public:
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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(ComplexF)*(m*k+k*n+m*n)*batchCount;
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// std::cout <<GridLogPerformance<< " batched Blas copy "<<(t0-t2)/1.e3 <<" ms "<<std::endl;
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// std::cout <<GridLogPerformance<< " batched Blas call "<<m<<","<<n<<","<<k<<" "<< flops/(t1-t0)/1.e3 <<" GF/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
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// std::cout <<GridLogPerformance<< " batched Blas call "<<m<<","<<n<<","<<k<<" "<< bytes/(t1-t0)/1.e3 <<" GB/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
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}
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///////////////////////////////////////////////////////////////////////////
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// Single precision real GEMM
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///////////////////////////////////////////////////////////////////////////
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void gemmBatched(int m,int n, int k,
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void gemmBatched(GridBLASOperation_t OpA,
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GridBLASOperation_t OpB,
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int m,int n, int k,
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RealF alpha,
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deviceVector<RealF*> &Amk, // pointer list to matrices
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deviceVector<RealF*> &Bkn,
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@ -300,23 +380,35 @@ public:
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{
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RealD t2=usecond();
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int32_t batchCount = Amk.size();
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// Use C-row major storage, so transpose calls
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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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lda = k;
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if(OpB!=GridBLAS_OP_N)
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ldb = n;
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static deviceVector<RealF> alpha_p(1);
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static deviceVector<RealF> beta_p(1);
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// can prestore the 1 and the zero on device
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acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(RealF));
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acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(RealF));
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RealD t0=usecond();
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// std::cout << "hipblasZgemmBatched mnk "<<m<<","<<n<<","<<k<<" count "<<batchCount<<std::endl;
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assert(Bkn.size()==batchCount);
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assert(Cmn.size()==batchCount);
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#ifdef GRID_HIP
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hipblasOperation_t hOpA;
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hipblasOperation_t hOpB;
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if ( OpA == GridBLAS_OP_N ) hOpA = HIPBLAS_OP_N;
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if ( OpA == GridBLAS_OP_T ) hOpA = HIPBLAS_OP_T;
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if ( OpA == GridBLAS_OP_C ) hOpA = HIPBLAS_OP_C;
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if ( OpB == GridBLAS_OP_N ) hOpB = HIPBLAS_OP_N;
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if ( OpB == GridBLAS_OP_T ) hOpB = HIPBLAS_OP_T;
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if ( OpB == GridBLAS_OP_C ) hOpB = HIPBLAS_OP_C;
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auto err = hipblasSgemmBatched(gridblasHandle,
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HIPBLAS_OP_N,
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HIPBLAS_OP_N,
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hOpA,
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hOpB,
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m,n,k,
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(float *) &alpha_p[0],
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(float **)&Amk[0], lda,
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@ -327,9 +419,17 @@ public:
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assert(err==HIPBLAS_STATUS_SUCCESS);
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#endif
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#ifdef GRID_CUDA
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cublasOperation_t hOpA;
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cublasOperation_t hOpB;
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if ( OpA == GridBLAS_OP_N ) hOpA = CUBLAS_OP_N;
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if ( OpA == GridBLAS_OP_T ) hOpA = CUBLAS_OP_T;
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if ( OpA == GridBLAS_OP_C ) hOpA = CUBLAS_OP_C;
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if ( OpB == GridBLAS_OP_N ) hOpB = CUBLAS_OP_N;
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if ( OpB == GridBLAS_OP_T ) hOpB = CUBLAS_OP_T;
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if ( OpB == GridBLAS_OP_C ) hOpB = CUBLAS_OP_C;
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auto err = cublasSgemmBatched(gridblasHandle,
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CUBLAS_OP_N,
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CUBLAS_OP_N,
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hOpA,
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hOpB,
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m,n,k,
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(float *) &alpha_p[0],
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(float **)&Amk[0], lda,
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@ -359,9 +459,6 @@ public:
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RealD t1=usecond();
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RealD flops = 2.0*m*n*k*batchCount;
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RealD bytes = 1.0*sizeof(RealF)*(m*k+k*n+m*n)*batchCount;
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// std::cout <<GridLogPerformance<< " batched Blas copy "<<(t0-t2)/1.e3 <<" ms "<<std::endl;
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// std::cout <<GridLogPerformance<< " batched Blas call "<<m<<","<<n<<","<<k<<" "<< flops/(t1-t0)/1.e3 <<" GF/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
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// std::cout <<GridLogPerformance<< " batched Blas call "<<m<<","<<n<<","<<k<<" "<< bytes/(t1-t0)/1.e3 <<" GB/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
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}
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@ -369,7 +466,9 @@ public:
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// Double precision real GEMM
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///////////////////////////////////////////////////////////////////////////
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void gemmBatched(int m,int n, int k,
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void gemmBatched(GridBLASOperation_t OpA,
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GridBLASOperation_t OpB,
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int m,int n, int k,
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RealD alpha,
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deviceVector<RealD*> &Amk, // pointer list to matrices
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deviceVector<RealD*> &Bkn,
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@ -378,20 +477,33 @@ public:
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{
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RealD t2=usecond();
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int32_t batchCount = Amk.size();
|
||||
// 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
|
||||
if(OpA!=GridBLAS_OP_N)
|
||||
lda = k;
|
||||
if(OpB!=GridBLAS_OP_N)
|
||||
ldb = n;
|
||||
|
||||
static deviceVector<RealD> alpha_p(1);
|
||||
static deviceVector<RealD> beta_p(1);
|
||||
// can prestore the 1 and the zero on device
|
||||
acceleratorCopyToDevice((void *)&alpha,(void *)&alpha_p[0],sizeof(RealD));
|
||||
acceleratorCopyToDevice((void *)&beta ,(void *)&beta_p[0],sizeof(RealD));
|
||||
RealD t0=usecond();
|
||||
// std::cout << "hipblasZgemmBatched mnk "<<m<<","<<n<<","<<k<<" count "<<batchCount<<std::endl;
|
||||
|
||||
assert(Bkn.size()==batchCount);
|
||||
assert(Cmn.size()==batchCount);
|
||||
#ifdef GRID_HIP
|
||||
hipblasOperation_t hOpA;
|
||||
hipblasOperation_t hOpB;
|
||||
if ( OpA == GridBLAS_OP_N ) hOpA = HIPBLAS_OP_N;
|
||||
if ( OpA == GridBLAS_OP_T ) hOpA = HIPBLAS_OP_T;
|
||||
if ( OpA == GridBLAS_OP_C ) hOpA = HIPBLAS_OP_C;
|
||||
if ( OpB == GridBLAS_OP_N ) hOpB = HIPBLAS_OP_N;
|
||||
if ( OpB == GridBLAS_OP_T ) hOpB = HIPBLAS_OP_T;
|
||||
if ( OpB == GridBLAS_OP_C ) hOpB = HIPBLAS_OP_C;
|
||||
auto err = hipblasDgemmBatched(gridblasHandle,
|
||||
HIPBLAS_OP_N,
|
||||
HIPBLAS_OP_N,
|
||||
@ -405,9 +517,17 @@ public:
|
||||
assert(err==HIPBLAS_STATUS_SUCCESS);
|
||||
#endif
|
||||
#ifdef GRID_CUDA
|
||||
cublasOperation_t hOpA;
|
||||
cublasOperation_t hOpB;
|
||||
if ( OpA == GridBLAS_OP_N ) hOpA = CUBLAS_OP_N;
|
||||
if ( OpA == GridBLAS_OP_T ) hOpA = CUBLAS_OP_T;
|
||||
if ( OpA == GridBLAS_OP_C ) hOpA = CUBLAS_OP_C;
|
||||
if ( OpB == GridBLAS_OP_N ) hOpB = CUBLAS_OP_N;
|
||||
if ( OpB == GridBLAS_OP_T ) hOpB = CUBLAS_OP_T;
|
||||
if ( OpB == GridBLAS_OP_C ) hOpB = CUBLAS_OP_C;
|
||||
auto err = cublasDgemmBatched(gridblasHandle,
|
||||
CUBLAS_OP_N,
|
||||
CUBLAS_OP_N,
|
||||
hOpA,
|
||||
hOpB,
|
||||
m,n,k,
|
||||
(double *) &alpha_p[0],
|
||||
(double **)&Amk[0], lda,
|
||||
@ -453,9 +573,6 @@ public:
|
||||
RealD t1=usecond();
|
||||
RealD flops = 2.0*m*n*k*batchCount;
|
||||
RealD bytes = 1.0*sizeof(RealD)*(m*k+k*n+m*n)*batchCount;
|
||||
// std::cout <<GridLogPerformance<< " batched Blas copy "<<(t0-t2)/1.e3 <<" ms "<<std::endl;
|
||||
// std::cout <<GridLogPerformance<< " batched Blas call "<<m<<","<<n<<","<<k<<" "<< flops/(t1-t0)/1.e3 <<" GF/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
|
||||
// std::cout <<GridLogPerformance<< " batched Blas call "<<m<<","<<n<<","<<k<<" "<< bytes/(t1-t0)/1.e3 <<" GB/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
|
||||
}
|
||||
|
||||
|
||||
@ -530,6 +647,36 @@ public:
|
||||
#endif
|
||||
}
|
||||
|
||||
void benchmark(int nbasis, int nrhs, int coarseVol, int nstencil)
|
||||
{
|
||||
int32_t N_A = nbasis*nbasis*coarseVol*nstencil;
|
||||
int32_t N_B = nbasis*nrhs*coarseVol*nstencil; // One leg of stencil at a time
|
||||
int32_t N_C = nbasis*nrhs*coarseVol*nstencil;
|
||||
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);
|
||||
for(int i=0;i<10;i++){
|
||||
RealD t0 = usecond();
|
||||
for(int s=0;s<nstencil;s++){
|
||||
gemmStridedBatched(nbasis,nrhs,nbasis,
|
||||
alpha,
|
||||
&A[0], // m x k
|
||||
&B[0], // k x n
|
||||
beta,
|
||||
&C[0], // m x n
|
||||
coarseVol);
|
||||
}
|
||||
synchronise();
|
||||
RealD t1 = usecond();
|
||||
RealD flops = 8.0*nbasis*nbasis*nrhs*coarseVol*nstencil;
|
||||
RealD bytes = 1.0*sizeof(ComplexD)*(nbasis*nbasis+nbasis*nrhs*3)*coarseVol*nstencil;
|
||||
std::cout << " batched Blas call "<<i<<" "<< flops/(t1-t0)/1.e3 <<" GF/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
|
||||
std::cout << " batched Blas call "<<i<<" "<< bytes/(t1-t0)/1.e3 <<" GB/s "<<(t1-t0)/1.e3<<" ms "<<std::endl;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user