ReactionKernelBulk_2_single_precision.cpp

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//======================================================================================================================
//
//  This file is part of waLBerla. waLBerla is free software: you can
//  redistribute it and/or modify it under the terms of the GNU General Public
//  License as published by the Free Software Foundation, either version 3 of
//  the License, or (at your option) any later version.
//
//  waLBerla is distributed in the hope that it will be useful, but WITHOUT
//  ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
//  FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
//  for more details.
//
//  You should have received a copy of the GNU General Public License along
//  with waLBerla (see COPYING.txt). If not, see <http://www.gnu.org/licenses/>.
//
//! \\file ReactionKernelBulk_2_single_precision.cpp
//! \\author pystencils
//======================================================================================================================
 
// kernel generated with pystencils v1.3.3, lbmpy v1.3.3, lbmpy_walberla/pystencils_walberla from waLBerla commit b0842e1a493ce19ef1bbb8d2cf382fc343970a7f
 
#include <cmath>
 
#include "ReactionKernelBulk_2_single_precision.h"
#include "core/DataTypes.h"
#include "core/Macros.h"
 
#define FUNC_PREFIX
 
#if (defined WALBERLA_CXX_COMPILER_IS_GNU) || (defined WALBERLA_CXX_COMPILER_IS_CLANG)
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wfloat-equal"
#pragma GCC diagnostic ignored "-Wshadow"
#pragma GCC diagnostic ignored "-Wconversion"
#pragma GCC diagnostic ignored "-Wunused-variable"
#endif
 
#if (defined WALBERLA_CXX_COMPILER_IS_INTEL)
#pragma warning push
#pragma warning(disable : 1599)
#endif
 
using namespace std;
 
namespace walberla {
namespace pystencils {
 
namespace internal_6de92b64acc501777cd14903620af26b {
static FUNC_PREFIX void reactionkernelbulk_2_single_precision_reactionkernelbulk_2_single_precision(float *RESTRICT _data_rho_0, float *RESTRICT _data_rho_1, int64_t const _size_rho_0_0, int64_t const _size_rho_0_1, int64_t const _size_rho_0_2, int64_t const _stride_rho_0_0, int64_t const _stride_rho_0_1, int64_t const _stride_rho_0_2, int64_t const _stride_rho_1_0, int64_t const _stride_rho_1_1, int64_t const _stride_rho_1_2, float order_0, float order_1, float rate_coefficient, float stoech_0, float stoech_1) {
  for (int64_t ctr_2 = 0; ctr_2 < _size_rho_0_2; ctr_2 += 1) {
    for (int64_t ctr_1 = 0; ctr_1 < _size_rho_0_1; ctr_1 += 1) {
      for (int64_t ctr_0 = 0; ctr_0 < _size_rho_0_0; ctr_0 += 1) {
        const float local_rho_0 = _data_rho_0[_stride_rho_0_0 * ctr_0 + _stride_rho_0_1 * ctr_1 + _stride_rho_0_2 * ctr_2];
        const float local_rho_1 = _data_rho_1[_stride_rho_1_0 * ctr_0 + _stride_rho_1_1 * ctr_1 + _stride_rho_1_2 * ctr_2];
        const float rate_factor = rate_coefficient * powf(local_rho_0, order_0) * powf(local_rho_1, order_1);
        _data_rho_0[_stride_rho_0_0 * ctr_0 + _stride_rho_0_1 * ctr_1 + _stride_rho_0_2 * ctr_2] = local_rho_0 + rate_factor * stoech_0;
        _data_rho_1[_stride_rho_1_0 * ctr_0 + _stride_rho_1_1 * ctr_1 + _stride_rho_1_2 * ctr_2] = local_rho_1 + rate_factor * stoech_1;
      }
    }
  }
}
} // namespace internal_6de92b64acc501777cd14903620af26b
 
void ReactionKernelBulk_2_single_precision::run(IBlock *block) {
 
  auto rho_1 = block->getData<field::GhostLayerField<float, 1>>(rho_1ID);
  auto rho_0 = block->getData<field::GhostLayerField<float, 1>>(rho_0ID);
 
  auto &stoech_0 = this->stoech_0_;
  auto &rate_coefficient = this->rate_coefficient_;
  auto &order_0 = this->order_0_;
  auto &order_1 = this->order_1_;
  auto &stoech_1 = this->stoech_1_;
  WALBERLA_ASSERT_GREATER_EQUAL(0, -int_c(rho_0->nrOfGhostLayers()))
  float *RESTRICT _data_rho_0 = rho_0->dataAt(0, 0, 0, 0);
  WALBERLA_ASSERT_GREATER_EQUAL(0, -int_c(rho_1->nrOfGhostLayers()))
  float *RESTRICT _data_rho_1 = rho_1->dataAt(0, 0, 0, 0);
  WALBERLA_ASSERT_GREATER_EQUAL(rho_0->xSizeWithGhostLayer(), int64_t(int64_c(rho_0->xSize()) + 0))
  const int64_t _size_rho_0_0 = int64_t(int64_c(rho_0->xSize()) + 0);
  WALBERLA_ASSERT_GREATER_EQUAL(rho_0->ySizeWithGhostLayer(), int64_t(int64_c(rho_0->ySize()) + 0))
  const int64_t _size_rho_0_1 = int64_t(int64_c(rho_0->ySize()) + 0);
  WALBERLA_ASSERT_GREATER_EQUAL(rho_0->zSizeWithGhostLayer(), int64_t(int64_c(rho_0->zSize()) + 0))
  const int64_t _size_rho_0_2 = int64_t(int64_c(rho_0->zSize()) + 0);
  const int64_t _stride_rho_0_0 = int64_t(rho_0->xStride());
  const int64_t _stride_rho_0_1 = int64_t(rho_0->yStride());
  const int64_t _stride_rho_0_2 = int64_t(rho_0->zStride());
  const int64_t _stride_rho_1_0 = int64_t(rho_1->xStride());
  const int64_t _stride_rho_1_1 = int64_t(rho_1->yStride());
  const int64_t _stride_rho_1_2 = int64_t(rho_1->zStride());
  internal_6de92b64acc501777cd14903620af26b::reactionkernelbulk_2_single_precision_reactionkernelbulk_2_single_precision(_data_rho_0, _data_rho_1, _size_rho_0_0, _size_rho_0_1, _size_rho_0_2, _stride_rho_0_0, _stride_rho_0_1, _stride_rho_0_2, _stride_rho_1_0, _stride_rho_1_1, _stride_rho_1_2, order_0, order_1, rate_coefficient, stoech_0, stoech_1);
}
 
void ReactionKernelBulk_2_single_precision::runOnCellInterval(const shared_ptr<StructuredBlockStorage> &blocks, const CellInterval &globalCellInterval, cell_idx_t ghostLayers, IBlock *block) {
 
  CellInterval ci = globalCellInterval;
  CellInterval blockBB = blocks->getBlockCellBB(*block);
  blockBB.expand(ghostLayers);
  ci.intersect(blockBB);
  blocks->transformGlobalToBlockLocalCellInterval(ci, *block);
  if (ci.empty())
    return;
 
  auto rho_1 = block->getData<field::GhostLayerField<float, 1>>(rho_1ID);
  auto rho_0 = block->getData<field::GhostLayerField<float, 1>>(rho_0ID);
 
  auto &stoech_0 = this->stoech_0_;
  auto &rate_coefficient = this->rate_coefficient_;
  auto &order_0 = this->order_0_;
  auto &order_1 = this->order_1_;
  auto &stoech_1 = this->stoech_1_;
  WALBERLA_ASSERT_GREATER_EQUAL(ci.xMin(), -int_c(rho_0->nrOfGhostLayers()))
  WALBERLA_ASSERT_GREATER_EQUAL(ci.yMin(), -int_c(rho_0->nrOfGhostLayers()))
  WALBERLA_ASSERT_GREATER_EQUAL(ci.zMin(), -int_c(rho_0->nrOfGhostLayers()))
  float *RESTRICT _data_rho_0 = rho_0->dataAt(ci.xMin(), ci.yMin(), ci.zMin(), 0);
  WALBERLA_ASSERT_GREATER_EQUAL(ci.xMin(), -int_c(rho_1->nrOfGhostLayers()))
  WALBERLA_ASSERT_GREATER_EQUAL(ci.yMin(), -int_c(rho_1->nrOfGhostLayers()))
  WALBERLA_ASSERT_GREATER_EQUAL(ci.zMin(), -int_c(rho_1->nrOfGhostLayers()))
  float *RESTRICT _data_rho_1 = rho_1->dataAt(ci.xMin(), ci.yMin(), ci.zMin(), 0);
  WALBERLA_ASSERT_GREATER_EQUAL(rho_0->xSizeWithGhostLayer(), int64_t(int64_c(ci.xSize()) + 0))
  const int64_t _size_rho_0_0 = int64_t(int64_c(ci.xSize()) + 0);
  WALBERLA_ASSERT_GREATER_EQUAL(rho_0->ySizeWithGhostLayer(), int64_t(int64_c(ci.ySize()) + 0))
  const int64_t _size_rho_0_1 = int64_t(int64_c(ci.ySize()) + 0);
  WALBERLA_ASSERT_GREATER_EQUAL(rho_0->zSizeWithGhostLayer(), int64_t(int64_c(ci.zSize()) + 0))
  const int64_t _size_rho_0_2 = int64_t(int64_c(ci.zSize()) + 0);
  const int64_t _stride_rho_0_0 = int64_t(rho_0->xStride());
  const int64_t _stride_rho_0_1 = int64_t(rho_0->yStride());
  const int64_t _stride_rho_0_2 = int64_t(rho_0->zStride());
  const int64_t _stride_rho_1_0 = int64_t(rho_1->xStride());
  const int64_t _stride_rho_1_1 = int64_t(rho_1->yStride());
  const int64_t _stride_rho_1_2 = int64_t(rho_1->zStride());
  internal_6de92b64acc501777cd14903620af26b::reactionkernelbulk_2_single_precision_reactionkernelbulk_2_single_precision(_data_rho_0, _data_rho_1, _size_rho_0_0, _size_rho_0_1, _size_rho_0_2, _stride_rho_0_0, _stride_rho_0_1, _stride_rho_0_2, _stride_rho_1_0, _stride_rho_1_1, _stride_rho_1_2, order_0, order_1, rate_coefficient, stoech_0, stoech_1);
}
 
} // namespace pystencils
} // namespace walberla
 
#if (defined WALBERLA_CXX_COMPILER_IS_GNU) || (defined WALBERLA_CXX_COMPILER_IS_CLANG)
#pragma GCC diagnostic pop
#endif
 
#if (defined WALBERLA_CXX_COMPILER_IS_INTEL)
#pragma warning pop
#endif