xref: /libCEED/include/ceed/jit-source/cuda/cuda-ref-operator-assemble.h (revision 07b31e0ef78c1ae2337ae2e7912515a2998488a7)

// 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 <ceed/ceed.h>

//------------------------------------------------------------------------------
// 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
}

//------------------------------------------------------------------------------