// Copyright (c) 2017-2022, Lawrence Livermore National Security, LLC and other CEED contributors. // All Rights Reserved. See the top-level LICENSE and NOTICE files for details. // // SPDX-License-Identifier: BSD-2-Clause // // This file is part of CEED: http://github.com/ceed #include //------------------------------------------------------------------------------ // Matrix assembly kernel for low-order elements (2D thread block) //------------------------------------------------------------------------------ extern "C" __launch_bounds__(BLOCK_SIZE) __global__ void linearAssemble(const CeedScalar *B_in, const CeedScalar *B_out, const CeedScalar *__restrict__ qf_array, CeedScalar *__restrict__ values_array) { // This kernel assumes B_in and B_out have the same number of quadrature points and // basis points. // TODO: expand to more general cases const int i = threadIdx.x; // The output row index of each B^TDB operation const int l = threadIdx.y; // The output column index of each B^TDB operation // such that we have (Bout^T)_ij D_jk Bin_kl = C_il // Strides for final output ordering, determined by the reference (interface) implementation of // the symbolic assembly, slowest --> fastest: element, comp_in, comp_out, node_row, node_col const CeedInt comp_out_stride = NNODES * NNODES; const CeedInt comp_in_stride = comp_out_stride * NCOMP; const CeedInt e_stride = comp_in_stride * NCOMP; // Strides for QF array, slowest --> fastest: emode_in, comp_in, emode_out, comp_out, elem, qpt const CeedInt qe_stride = NQPTS; const CeedInt qcomp_out_stride = NELEM * qe_stride; const CeedInt qemode_out_stride = qcomp_out_stride * NCOMP; const CeedInt qcomp_in_stride = qemode_out_stride * NUMEMODEOUT; const CeedInt qemode_in_stride = qcomp_in_stride * NCOMP; // Loop over each element (if necessary) for (CeedInt e = blockIdx.x * blockDim.z + threadIdx.z; e < NELEM; e += gridDim.x * blockDim.z) { for (CeedInt comp_in = 0; comp_in < NCOMP; comp_in++) { for (CeedInt comp_out = 0; comp_out < NCOMP; comp_out++) { CeedScalar result = 0.0; CeedInt qf_index_comp = qcomp_in_stride * comp_in + qcomp_out_stride * comp_out + qe_stride * e; for (CeedInt emode_in = 0; emode_in < NUMEMODEIN; emode_in++) { CeedInt b_in_index = emode_in * NQPTS * NNODES; for (CeedInt emode_out = 0; emode_out < NUMEMODEOUT; emode_out++) { CeedInt b_out_index = emode_out * NQPTS * NNODES; CeedInt qf_index = qf_index_comp + qemode_out_stride * emode_out + qemode_in_stride * emode_in; // Perform the B^T D B operation for this 'chunk' of D (the qf_array) for (CeedInt j = 0; j < NQPTS; j++) { result += B_out[b_out_index + j * NNODES + i] * qf_array[qf_index + j] * B_in[b_in_index + j * NNODES + l]; } } // end of emode_out } // end of emode_in CeedInt val_index = comp_in_stride * comp_in + comp_out_stride * comp_out + e_stride * e + NNODES * i + l; values_array[val_index] = result; } // end of out component } // end of in component } // end of element loop } //------------------------------------------------------------------------------ // Fallback kernel for larger orders (1D thread block) //------------------------------------------------------------------------------ extern "C" __launch_bounds__(BLOCK_SIZE) __global__ void linearAssembleFallback(const CeedScalar *B_in, const CeedScalar *B_out, const CeedScalar *__restrict__ qf_array, CeedScalar *__restrict__ values_array) { // This kernel assumes B_in and B_out have the same number of quadrature points and // basis points. // TODO: expand to more general cases const int l = threadIdx.x; // The output column index of each B^TDB operation // such that we have (Bout^T)_ij D_jk Bin_kl = C_il // Strides for final output ordering, determined by the reference (interface) implementation of // the symbolic assembly, slowest --> fastest: element, comp_in, comp_out, node_row, node_col const CeedInt comp_out_stride = NNODES * NNODES; const CeedInt comp_in_stride = comp_out_stride * NCOMP; const CeedInt e_stride = comp_in_stride * NCOMP; // Strides for QF array, slowest --> fastest: emode_in, comp_in, emode_out, comp_out, elem, qpt const CeedInt qe_stride = NQPTS; const CeedInt qcomp_out_stride = NELEM * qe_stride; const CeedInt qemode_out_stride = qcomp_out_stride * NCOMP; const CeedInt qcomp_in_stride = qemode_out_stride * NUMEMODEOUT; const CeedInt qemode_in_stride = qcomp_in_stride * NCOMP; // Loop over each element (if necessary) for (CeedInt e = blockIdx.x * blockDim.z + threadIdx.z; e < NELEM; e += gridDim.x * blockDim.z) { for (CeedInt comp_in = 0; comp_in < NCOMP; comp_in++) { for (CeedInt comp_out = 0; comp_out < NCOMP; comp_out++) { for (CeedInt i = 0; i < NNODES; i++) { CeedScalar result = 0.0; CeedInt qf_index_comp = qcomp_in_stride * comp_in + qcomp_out_stride * comp_out + qe_stride * e; for (CeedInt emode_in = 0; emode_in < NUMEMODEIN; emode_in++) { CeedInt b_in_index = emode_in * NQPTS * NNODES; for (CeedInt emode_out = 0; emode_out < NUMEMODEOUT; emode_out++) { CeedInt b_out_index = emode_out * NQPTS * NNODES; CeedInt qf_index = qf_index_comp + qemode_out_stride * emode_out + qemode_in_stride * emode_in; // Perform the B^T D B operation for this 'chunk' of D (the qf_array) for (CeedInt j = 0; j < NQPTS; j++) { result += B_out[b_out_index + j * NNODES + i] * qf_array[qf_index + j] * B_in[b_in_index + j * NNODES + l]; } } // end of emode_out } // end of emode_in CeedInt val_index = comp_in_stride * comp_in + comp_out_stride * comp_out + e_stride * e + NNODES * i + l; values_array[val_index] = result; } // end of loop over element node index, i } // end of out component } // end of in component } // end of element loop } //------------------------------------------------------------------------------