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Extensible Simulation Package for Research on Soft Matter Systems
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ReactionKernelBulk_4_double_precision_CUDA.h
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1//======================================================================================================================
2//
3// This file is part of waLBerla. waLBerla is free software: you can
4// redistribute it and/or modify it under the terms of the GNU General Public
5// License as published by the Free Software Foundation, either version 3 of
6// the License, or (at your option) any later version.
7//
8// waLBerla is distributed in the hope that it will be useful, but WITHOUT
9// ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
10// FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
11// for more details.
12//
13// You should have received a copy of the GNU General Public License along
14// with waLBerla (see COPYING.txt). If not, see <http://www.gnu.org/licenses/>.
15//
16//! \\file ReactionKernelBulk_4_double_precision_CUDA.h
17//! \\author pystencils
18//======================================================================================================================
19
20// kernel generated with pystencils v1.4+1.ge851f4e, lbmpy v1.4+1.ge9efe34,
21// sympy v1.12.1, lbmpy_walberla/pystencils_walberla from waLBerla commit
22// 007e77e077ad9d22b5eed6f3d3118240993e553c
23
24#pragma once
25#include "core/DataTypes.h"
26#include "core/logging/Logging.h"
27
28#include "gpu/GPUField.h"
29#include "gpu/GPUWrapper.h"
30
31#include "domain_decomposition/BlockDataID.h"
32#include "domain_decomposition/IBlock.h"
33#include "domain_decomposition/StructuredBlockStorage.h"
34#include "field/SwapableCompare.h"
35
36#include <functional>
37#include <unordered_map>
38
39#ifdef __GNUC__
40#define RESTRICT __restrict__
41#else
42#define RESTRICT
43#endif
44
45#if (defined WALBERLA_CXX_COMPILER_IS_GNU) || \
46 (defined WALBERLA_CXX_COMPILER_IS_CLANG)
47#pragma GCC diagnostic push
48#pragma GCC diagnostic ignored "-Wunused-parameter"
49#pragma GCC diagnostic ignored "-Wreorder"
50#endif
51
52namespace walberla {
53namespace pystencils {
54
56public:
58 BlockDataID rho_0ID_, BlockDataID rho_1ID_, BlockDataID rho_2ID_,
59 BlockDataID rho_3ID_, double order_0, double order_1, double order_2,
60 double order_3, double rate_coefficient, double stoech_0, double stoech_1,
61 double stoech_2, double stoech_3)
62 : rho_0ID(rho_0ID_), rho_1ID(rho_1ID_), rho_2ID(rho_2ID_),
63 rho_3ID(rho_3ID_), order_0_(order_0), order_1_(order_1),
64 order_2_(order_2), order_3_(order_3),
65 rate_coefficient_(rate_coefficient), stoech_0_(stoech_0),
66 stoech_1_(stoech_1), stoech_2_(stoech_2), stoech_3_(stoech_3) {}
67
68 void run(IBlock *block, gpuStream_t stream = nullptr);
69
70 void runOnCellInterval(const shared_ptr<StructuredBlockStorage> &blocks,
71 const CellInterval &globalCellInterval,
72 cell_idx_t ghostLayers, IBlock *block,
73 gpuStream_t stream = nullptr);
74
75 void operator()(IBlock *block, gpuStream_t stream = nullptr) {
77 }
78
79 static std::function<void(IBlock *)> getSweep(
80 const shared_ptr<ReactionKernelBulk_4_double_precision_CUDA> &kernel) {
81 return [kernel](IBlock *b) { kernel->run(b); };
82 }
83
84 static std::function<void(IBlock *, gpuStream_t)> getSweepOnCellInterval(
85 const shared_ptr<ReactionKernelBulk_4_double_precision_CUDA> &kernel,
86 const shared_ptr<StructuredBlockStorage> &blocks,
87 const CellInterval &globalCellInterval, cell_idx_t ghostLayers = 1) {
88 return [kernel, blocks, globalCellInterval,
89 ghostLayers](IBlock *b, gpuStream_t stream = nullptr) {
90 kernel->runOnCellInterval(blocks, globalCellInterval, ghostLayers, b,
91 stream);
92 };
93 }
94
95 std::function<void(IBlock *)> getSweep(gpuStream_t stream = nullptr) {
96 return [this, stream](IBlock *b) { this->run(b, stream); };
97 }
98
99 std::function<void(IBlock *)>
100 getSweepOnCellInterval(const shared_ptr<StructuredBlockStorage> &blocks,
101 const CellInterval &globalCellInterval,
102 cell_idx_t ghostLayers = 1,
103 gpuStream_t stream = nullptr) {
104 return [this, blocks, globalCellInterval, ghostLayers, stream](IBlock *b) {
105 this->runOnCellInterval(blocks, globalCellInterval, ghostLayers, b,
106 stream);
107 };
108 }
109
110 void configure(const shared_ptr<StructuredBlockStorage> & /*blocks*/,
111 IBlock * /*block*/) {}
112
113 inline double getOrder_0() const { return order_0_; }
114 inline double getOrder_1() const { return order_1_; }
115 inline double getOrder_2() const { return order_2_; }
116 inline double getOrder_3() const { return order_3_; }
117 inline double getRate_coefficient() const { return rate_coefficient_; }
118 inline double getStoech_0() const { return stoech_0_; }
119 inline double getStoech_1() const { return stoech_1_; }
120 inline double getStoech_2() const { return stoech_2_; }
121 inline double getStoech_3() const { return stoech_3_; }
122 inline void setOrder_0(const double value) { order_0_ = value; }
123 inline void setOrder_1(const double value) { order_1_ = value; }
124 inline void setOrder_2(const double value) { order_2_ = value; }
125 inline void setOrder_3(const double value) { order_3_ = value; }
126 inline void setRate_coefficient(const double value) {
127 rate_coefficient_ = value;
128 }
129 inline void setStoech_0(const double value) { stoech_0_ = value; }
130 inline void setStoech_1(const double value) { stoech_1_ = value; }
131 inline void setStoech_2(const double value) { stoech_2_ = value; }
132 inline void setStoech_3(const double value) { stoech_3_ = value; }
133
134private:
135 BlockDataID rho_0ID;
136 BlockDataID rho_1ID;
137 BlockDataID rho_2ID;
138 BlockDataID rho_3ID;
139 double order_0_;
140 double order_1_;
141 double order_2_;
142 double order_3_;
143 double rate_coefficient_;
144 double stoech_0_;
145 double stoech_1_;
146 double stoech_2_;
147 double stoech_3_;
148};
149
150} // namespace pystencils
151} // namespace walberla
152
153#if (defined WALBERLA_CXX_COMPILER_IS_GNU) || \
154 (defined WALBERLA_CXX_COMPILER_IS_CLANG)
155#pragma GCC diagnostic pop
156#endif
static std::function< void(IBlock *, gpuStream_t)> getSweepOnCellInterval(const shared_ptr< ReactionKernelBulk_4_double_precision_CUDA > &kernel, const shared_ptr< StructuredBlockStorage > &blocks, const CellInterval &globalCellInterval, cell_idx_t ghostLayers=1)
static std::function< void(IBlock *)> getSweep(const shared_ptr< ReactionKernelBulk_4_double_precision_CUDA > &kernel)
void runOnCellInterval(const shared_ptr< StructuredBlockStorage > &blocks, const CellInterval &globalCellInterval, cell_idx_t ghostLayers, IBlock *block, gpuStream_t stream=nullptr)
ReactionKernelBulk_4_double_precision_CUDA(BlockDataID rho_0ID_, BlockDataID rho_1ID_, BlockDataID rho_2ID_, BlockDataID rho_3ID_, double order_0, double order_1, double order_2, double order_3, double rate_coefficient, double stoech_0, double stoech_1, double stoech_2, double stoech_3)
std::function< void(IBlock *)> getSweepOnCellInterval(const shared_ptr< StructuredBlockStorage > &blocks, const CellInterval &globalCellInterval, cell_idx_t ghostLayers=1, gpuStream_t stream=nullptr)
cudaStream_t stream[1]
CUDA streams for parallel computing on CPU and GPU.
static double * block(double *p, std::size_t index, std::size_t size)
Definition elc.cpp:176
\file PackInfoPdfDoublePrecision.cpp \author pystencils