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Extensible Simulation Package for Research on Soft Matter Systems
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StreamCollideSweepThermalizedSinglePrecisionCUDA.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 StreamCollideSweepThermalizedSinglePrecisionCUDA.h
17//! \\author pystencils
18//======================================================================================================================
19
20// kernel generated with pystencils v1.3.7+13.gdfd203a, lbmpy
21// v1.3.7+10.gd3f6236, sympy v1.12.1, lbmpy_walberla/pystencils_walberla from
22// waLBerla commit c69cb11d6a95d32b2280544d3d9abde1fe5fdbb5
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#elif _MSC_VER
42#define RESTRICT __restrict
43#else
44#define RESTRICT
45#endif
46
47#if (defined WALBERLA_CXX_COMPILER_IS_GNU) || \
48 (defined WALBERLA_CXX_COMPILER_IS_CLANG)
49#pragma GCC diagnostic push
50#pragma GCC diagnostic ignored "-Wunused-parameter"
51#pragma GCC diagnostic ignored "-Wreorder"
52#endif
53
54namespace walberla {
55namespace pystencils {
56
58public:
60 BlockDataID forceID_, BlockDataID pdfsID_, float kT, float omega_bulk,
61 float omega_even, float omega_odd, float omega_shear, uint32_t seed,
62 uint32_t time_step)
63 : forceID(forceID_), pdfsID(pdfsID_), kT_(kT), omega_bulk_(omega_bulk),
64 omega_even_(omega_even), omega_odd_(omega_odd),
65 omega_shear_(omega_shear), seed_(seed), time_step_(time_step),
66 block_offset_0_(uint32_t(0)), block_offset_1_(uint32_t(0)),
67 block_offset_2_(uint32_t(0)), configured_(false) {}
68
70 for (auto p : cache_pdfs_) {
71 delete p.second;
72 }
73 }
74
75 void run(IBlock *block, gpuStream_t stream = nullptr);
76
77 void runOnCellInterval(const shared_ptr<StructuredBlockStorage> &blocks,
78 const CellInterval &globalCellInterval,
79 cell_idx_t ghostLayers, IBlock *block,
80 gpuStream_t stream = nullptr);
81
82 void operator()(IBlock *block, gpuStream_t stream = nullptr) {
84 }
85
86 static std::function<void(IBlock *)>
87 getSweep(const shared_ptr<StreamCollideSweepThermalizedSinglePrecisionCUDA>
88 &kernel) {
89 return [kernel](IBlock *b) { kernel->run(b); };
90 }
91
92 static std::function<void(IBlock *, gpuStream_t)> getSweepOnCellInterval(
93 const shared_ptr<StreamCollideSweepThermalizedSinglePrecisionCUDA>
94 &kernel,
95 const shared_ptr<StructuredBlockStorage> &blocks,
96 const CellInterval &globalCellInterval, cell_idx_t ghostLayers = 1) {
97 return [kernel, blocks, globalCellInterval,
98 ghostLayers](IBlock *b, gpuStream_t stream = nullptr) {
99 kernel->runOnCellInterval(blocks, globalCellInterval, ghostLayers, b,
100 stream);
101 };
102 }
103
104 std::function<void(IBlock *)> getSweep(gpuStream_t stream = nullptr) {
105 return [this, stream](IBlock *b) { this->run(b, stream); };
106 }
107
108 std::function<void(IBlock *)>
109 getSweepOnCellInterval(const shared_ptr<StructuredBlockStorage> &blocks,
110 const CellInterval &globalCellInterval,
111 cell_idx_t ghostLayers = 1,
112 gpuStream_t stream = nullptr) {
113 return [this, blocks, globalCellInterval, ghostLayers, stream](IBlock *b) {
114 this->runOnCellInterval(blocks, globalCellInterval, ghostLayers, b,
115 stream);
116 };
117 }
118
119 void configure(const shared_ptr<StructuredBlockStorage> &blocks,
120 IBlock *block) {
121 Cell BlockCellBB = blocks->getBlockCellBB(*block).min();
122 block_offset_0_ = uint32_t(BlockCellBB[0]);
123 block_offset_1_ = uint32_t(BlockCellBB[1]);
124 block_offset_2_ = uint32_t(BlockCellBB[2]);
125 configured_ = true;
126 }
127
128 inline uint32_t getBlock_offset_0() const { return block_offset_0_; }
129 inline uint32_t getBlock_offset_1() const { return block_offset_1_; }
130 inline uint32_t getBlock_offset_2() const { return block_offset_2_; }
131 inline float getKt() const { return kT_; }
132 inline float getOmega_bulk() const { return omega_bulk_; }
133 inline float getOmega_even() const { return omega_even_; }
134 inline float getOmega_odd() const { return omega_odd_; }
135 inline float getOmega_shear() const { return omega_shear_; }
136 inline uint32_t getSeed() const { return seed_; }
137 inline uint32_t getTime_step() const { return time_step_; }
138 inline void setBlock_offset_0(const uint32_t value) {
139 block_offset_0_ = value;
140 }
141 inline void setBlock_offset_1(const uint32_t value) {
142 block_offset_1_ = value;
143 }
144 inline void setBlock_offset_2(const uint32_t value) {
145 block_offset_2_ = value;
146 }
147 inline void setKt(const float value) { kT_ = value; }
148 inline void setOmega_bulk(const float value) { omega_bulk_ = value; }
149 inline void setOmega_even(const float value) { omega_even_ = value; }
150 inline void setOmega_odd(const float value) { omega_odd_ = value; }
151 inline void setOmega_shear(const float value) { omega_shear_ = value; }
152 inline void setSeed(const uint32_t value) { seed_ = value; }
153 inline void setTime_step(const uint32_t value) { time_step_ = value; }
154
155private:
156 BlockDataID forceID;
157 BlockDataID pdfsID;
158 uint32_t block_offset_0_;
159 uint32_t block_offset_1_;
160 uint32_t block_offset_2_;
161 float kT_;
162 float omega_bulk_;
163 float omega_even_;
164 float omega_odd_;
165 float omega_shear_;
166 uint32_t seed_;
167 uint32_t time_step_;
168 std::unordered_map<IBlock *, gpu::GPUField<float> *> cache_pdfs_;
169
170 bool configured_;
171};
172
173} // namespace pystencils
174} // namespace walberla
175
176#if (defined WALBERLA_CXX_COMPILER_IS_GNU) || \
177 (defined WALBERLA_CXX_COMPILER_IS_CLANG)
178#pragma GCC diagnostic pop
179#endif
Definition Cell.hpp:96
void runOnCellInterval(const shared_ptr< StructuredBlockStorage > &blocks, const CellInterval &globalCellInterval, cell_idx_t ghostLayers, IBlock *block, gpuStream_t stream=nullptr)
void configure(const shared_ptr< StructuredBlockStorage > &blocks, IBlock *block)
std::function< void(IBlock *)> getSweepOnCellInterval(const shared_ptr< StructuredBlockStorage > &blocks, const CellInterval &globalCellInterval, cell_idx_t ghostLayers=1, gpuStream_t stream=nullptr)
static std::function< void(IBlock *)> getSweep(const shared_ptr< StreamCollideSweepThermalizedSinglePrecisionCUDA > &kernel)
StreamCollideSweepThermalizedSinglePrecisionCUDA(BlockDataID forceID_, BlockDataID pdfsID_, float kT, float omega_bulk, float omega_even, float omega_odd, float omega_shear, uint32_t seed, uint32_t time_step)
static std::function< void(IBlock *, gpuStream_t)> getSweepOnCellInterval(const shared_ptr< StreamCollideSweepThermalizedSinglePrecisionCUDA > &kernel, const shared_ptr< StructuredBlockStorage > &blocks, const CellInterval &globalCellInterval, cell_idx_t ghostLayers=1)
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