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CollideSweepDoublePrecisionThermalizedCUDA.h
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1//======================================================================================================================
2//
3// This file is part of waLBerla. waLBerla is free software: you can
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5// License as published by the Free Software Foundation, either version 3 of
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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.
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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 CollideSweepDoublePrecisionThermalizedCUDA.h
17//! \\author pystencils
18//======================================================================================================================
19
20// kernel generated with pystencils v1.3.7, lbmpy v1.3.7, sympy v1.12.1,
21// lbmpy_walberla/pystencils_walberla from waLBerla commit
22// f36fa0a68bae59f0b516f6587ea8fa7c24a41141
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_, double kT, double omega_bulk,
61 double omega_even, double omega_odd, double 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
69 void run(IBlock *block, gpuStream_t stream = nullptr);
70
71 void runOnCellInterval(const shared_ptr<StructuredBlockStorage> &blocks,
72 const CellInterval &globalCellInterval,
73 cell_idx_t ghostLayers, IBlock *block,
74 gpuStream_t stream = nullptr);
75
76 void operator()(IBlock *block, gpuStream_t stream = nullptr) {
78 }
79
80 static std::function<void(IBlock *)> getSweep(
81 const shared_ptr<CollideSweepDoublePrecisionThermalizedCUDA> &kernel) {
82 return [kernel](IBlock *b) { kernel->run(b); };
83 }
84
85 static std::function<void(IBlock *, gpuStream_t)> getSweepOnCellInterval(
86 const shared_ptr<CollideSweepDoublePrecisionThermalizedCUDA> &kernel,
87 const shared_ptr<StructuredBlockStorage> &blocks,
88 const CellInterval &globalCellInterval, cell_idx_t ghostLayers = 1) {
89 return [kernel, blocks, globalCellInterval,
90 ghostLayers](IBlock *b, gpuStream_t stream = nullptr) {
91 kernel->runOnCellInterval(blocks, globalCellInterval, ghostLayers, b,
92 stream);
93 };
94 }
95
96 std::function<void(IBlock *)> getSweep(gpuStream_t stream = nullptr) {
97 return [this, stream](IBlock *b) { this->run(b, stream); };
98 }
99
100 std::function<void(IBlock *)>
101 getSweepOnCellInterval(const shared_ptr<StructuredBlockStorage> &blocks,
102 const CellInterval &globalCellInterval,
103 cell_idx_t ghostLayers = 1,
104 gpuStream_t stream = nullptr) {
105 return [this, blocks, globalCellInterval, ghostLayers, stream](IBlock *b) {
106 this->runOnCellInterval(blocks, globalCellInterval, ghostLayers, b,
107 stream);
108 };
109 }
110
111 void configure(const shared_ptr<StructuredBlockStorage> &blocks,
112 IBlock *block) {
113 Cell BlockCellBB = blocks->getBlockCellBB(*block).min();
114 block_offset_0_ = uint32_t(BlockCellBB[0]);
115 block_offset_1_ = uint32_t(BlockCellBB[1]);
116 block_offset_2_ = uint32_t(BlockCellBB[2]);
117 configured_ = true;
118 }
119
120 inline uint32_t getBlock_offset_0() const { return block_offset_0_; }
121 inline uint32_t getBlock_offset_1() const { return block_offset_1_; }
122 inline uint32_t getBlock_offset_2() const { return block_offset_2_; }
123 inline double getKt() const { return kT_; }
124 inline double getOmega_bulk() const { return omega_bulk_; }
125 inline double getOmega_even() const { return omega_even_; }
126 inline double getOmega_odd() const { return omega_odd_; }
127 inline double getOmega_shear() const { return omega_shear_; }
128 inline uint32_t getSeed() const { return seed_; }
129 inline uint32_t getTime_step() const { return time_step_; }
130 inline void setBlock_offset_0(const uint32_t value) {
131 block_offset_0_ = value;
132 }
133 inline void setBlock_offset_1(const uint32_t value) {
134 block_offset_1_ = value;
135 }
136 inline void setBlock_offset_2(const uint32_t value) {
137 block_offset_2_ = value;
138 }
139 inline void setKt(const double value) { kT_ = value; }
140 inline void setOmega_bulk(const double value) { omega_bulk_ = value; }
141 inline void setOmega_even(const double value) { omega_even_ = value; }
142 inline void setOmega_odd(const double value) { omega_odd_ = value; }
143 inline void setOmega_shear(const double value) { omega_shear_ = value; }
144 inline void setSeed(const uint32_t value) { seed_ = value; }
145 inline void setTime_step(const uint32_t value) { time_step_ = value; }
146
147private:
148 BlockDataID forceID;
149 BlockDataID pdfsID;
150 uint32_t block_offset_0_;
151 uint32_t block_offset_1_;
152 uint32_t block_offset_2_;
153 double kT_;
154 double omega_bulk_;
155 double omega_even_;
156 double omega_odd_;
157 double omega_shear_;
158 uint32_t seed_;
159 uint32_t time_step_;
160
161 bool configured_;
162};
163
164} // namespace pystencils
165} // namespace walberla
166
167#if (defined WALBERLA_CXX_COMPILER_IS_GNU) || \
168 (defined WALBERLA_CXX_COMPILER_IS_CLANG)
169#pragma GCC diagnostic pop
170#endif
Definition Cell.hpp:96
static std::function< void(IBlock *)> getSweep(const shared_ptr< CollideSweepDoublePrecisionThermalizedCUDA > &kernel)
void runOnCellInterval(const shared_ptr< StructuredBlockStorage > &blocks, const CellInterval &globalCellInterval, cell_idx_t ghostLayers, IBlock *block, gpuStream_t stream=nullptr)
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 *, gpuStream_t)> getSweepOnCellInterval(const shared_ptr< CollideSweepDoublePrecisionThermalizedCUDA > &kernel, const shared_ptr< StructuredBlockStorage > &blocks, const CellInterval &globalCellInterval, cell_idx_t ghostLayers=1)
void configure(const shared_ptr< StructuredBlockStorage > &blocks, IBlock *block)
CollideSweepDoublePrecisionThermalizedCUDA(BlockDataID forceID_, BlockDataID pdfsID_, double kT, double omega_bulk, double omega_even, double omega_odd, double omega_shear, uint32_t seed, uint32_t time_step)
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:172
\file PackInfoPdfDoublePrecision.cpp \author pystencils