[petsc-users] issue of MatCreateDense in the CUDA codes

[刘浪天]

Hi Junchao, I check it, I haven't use cuda when install pure cpu version of petsc. The configure.log has been attached. Thank you for your reply. Best wishes, -------------------- Langtian Liu Institute for Theorectical Physics, Justus-Liebig-University Giessen Heinrich-Buff-Ring 16, 35392 Giessen Germany email: langtian.liu at icloud.com Tel: (+49)641 99 33342 On Oct 2, 2024, at 5:05 PM, Junchao Zhang <junchao.zhang at gmail.com> wrote: On Wed, Oct 2, 2024 at 3:57 AM 刘浪天 via petsc-users < petsc-users at mcs.anl.gov > wrote: Hi all, I am using the PETSc and SLEPc to solve the Faddeev equation of baryons. I encounter a problem of function MatCreateDense when changing from CPU to CPU-GPU computations. At first, I write the codes in purely CPU computation in the following way and it works. ``` Eigen :: MatrixXcd H_KER ; Eigen :: MatrixXcd G0 ; printf( " \n Compute the propagator matrix. \n " ) ; prop_matrix_nucleon_sc_av( Mn , pp_nodes , cos1_nodes) ; printf( " \n Compute the propagator matrix done. \n " ) ; printf( " \n Compute the kernel matrix. \n " ) ; bse_kernel_nucleon_sc_av( Mn , pp_nodes , pp_weights , cos1_nodes , cos1_weights) ; printf( " \n Compute the kernel matrix done. \n " ) ; printf( " \n Compute the full kernel matrix by multiplying kernel and propagator matrix. \n " ) ; MatrixXcd kernel_temp = H_KER * G0 ; printf( " \n Compute the full kernel matrix done. \n " ) ; // Solve the eigen system with SLEPc printf( " \n Solve the eigen system in the rest frame. \n " ) ; // Get the size of the Eigen matrix int nRows = ( int ) kernel_temp. rows () ; int nCols = ( int ) kernel_temp. cols () ; // Create PETSc matrix and share the data of kernel_temp Mat kernel ; PetscCall(MatCreateDense(PETSC_COMM_WORLD , PETSC_DECIDE , PETSC_DECIDE , nRows , nCols , kernel_temp.data() , &kernel)) ; PetscCall(MatAssemblyBegin(kernel , MAT_FINAL_ASSEMBLY)) ; PetscCall(MatAssemblyEnd(kernel , MAT_FINAL_ASSEMBLY)) ; ``` Now I change to compute the propagator and kernel matrices in GPU and then compute the largest eigenvalues in CPU using SLEPc in the ways below. ``` cuDoubleComplex * h_propmat ; cuDoubleComplex * h_kernelmat ; int dim = EIGHT * NP * NZ ; printf( " \n Compute the propagator matrix. \n " ) ; prop_matrix_nucleon_sc_av_cuda( Mn , pp_nodes .data() , cos1_nodes .data()) ; printf( " \n Compute the propagator matrix done. \n " ) ; printf( " \n Compute the kernel matrix. \n " ) ; kernel_matrix_nucleon_sc_av_cuda( Mn , pp_nodes .data() , pp_weights .data() , cos1_nodes .data() , cos1_weights .data()) ; printf( " \n Compute the kernel matrix done. \n " ) ; printf( " \n Compute the full kernel matrix by multiplying kernel and propagator matrix. \n " ) ; // Map the raw arrays to Eigen matrices (column-major order) auto * h_kernel_temp = new cuDoubleComplex [ dim * dim ] ; matmul_cublas_cuDoubleComplex( h_kernelmat , h_propmat , h_kernel_temp , dim , dim , dim ) ; printf( " \n Compute the full kernel matrix done. \n " ) ; // Solve the eigen system with SLEPc printf( " \n Solve the eigen system in the rest frame. \n " ) ; int nRows = dim ; int nCols = dim ; // Create PETSc matrix and share the data of kernel_temp Mat kernel ; auto * h_kernel = ( std :: complex < double >*)( h_kernel_temp ) ; PetscCall (MatCreateDense( PETSC_COMM_WORLD , PETSC_DECIDE , PETSC_DECIDE , nRows , nCols , h_kernel_temp , & kernel )) ; PetscCall (MatAssemblyBegin( kernel , MAT_FINAL_ASSEMBLY )) ; PetscCall (MatAssemblyEnd( kernel , MAT_FINAL_ASSEMBLY )) ; But in this case, the compiler told me that the MatCreateDense function uses the data pointer as type of "thrust::complex<double>" instead of "std::complex<double>". I am sure I only configured and install PETSc in purely CPU without GPU and this codes are written in the host function. Please double check that your PETSc was purely CPU configured. You can find it at the end of your configure.log to see if petsc is configured with CUDA. Since thrust::complex<double> is a result of a petsc/cuda configuration, I have this doubt. Why the function changes its behavior? Did you also meet this problem when writing the cuda codes and how to solve this problem. I tried to copy the data to a new thrust::complex<double> matrix but this is very time consuming since my matrix is very big. Is there a way to create the Mat from the original data without changing the data type to thrust::complex<double> in the cuda applications? Any response will be appreciated. Thank you! Best wishes, Langtian Liu ------ Institute for Theorectical Physics, Justus-Liebig-University Giessen Heinrich-Buff-Ring 16, 35392 Giessen Germany
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