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37 * \brief Define CUDA implementation of nbnxn_gpu.h
39 * \author Szilard Pall <pall.szilard@gmail.com>
48 #include "gromacs/nbnxm/nbnxm_gpu.h"
55 #include "nbnxm_cuda.h"
57 #include "gromacs/gpu_utils/gpu_utils.h"
58 #include "gromacs/gpu_utils/gpueventsynchronizer.cuh"
59 #include "gromacs/gpu_utils/typecasts.cuh"
60 #include "gromacs/gpu_utils/vectype_ops.cuh"
61 #include "gromacs/hardware/device_information.h"
62 #include "gromacs/mdtypes/simulation_workload.h"
63 #include "gromacs/nbnxm/atomdata.h"
64 #include "gromacs/nbnxm/gpu_common.h"
65 #include "gromacs/nbnxm/gpu_common_utils.h"
66 #include "gromacs/nbnxm/gpu_data_mgmt.h"
67 #include "gromacs/nbnxm/grid.h"
68 #include "gromacs/nbnxm/nbnxm.h"
69 #include "gromacs/nbnxm/pairlist.h"
70 #include "gromacs/timing/gpu_timing.h"
71 #include "gromacs/utility/cstringutil.h"
72 #include "gromacs/utility/gmxassert.h"
74 #include "nbnxm_buffer_ops_kernels.cuh"
75 #include "nbnxm_cuda_types.h"
77 /***** The kernel declarations/definitions come here *****/
79 /* Top-level kernel declaration generation: will generate through multiple
80 * inclusion the following flavors for all kernel declarations:
81 * - force-only output;
82 * - force and energy output;
83 * - force-only with pair list pruning;
84 * - force and energy output with pair list pruning.
86 #define FUNCTION_DECLARATION_ONLY
88 #include "nbnxm_cuda_kernels.cuh"
89 /** Force & energy **/
91 #include "nbnxm_cuda_kernels.cuh"
94 /*** Pair-list pruning kernels ***/
97 #include "nbnxm_cuda_kernels.cuh"
98 /** Force & energy **/
100 #include "nbnxm_cuda_kernels.cuh"
104 /* Prune-only kernels */
105 #include "nbnxm_cuda_kernel_pruneonly.cuh"
106 #undef FUNCTION_DECLARATION_ONLY
108 /* Now generate the function definitions if we are using a single compilation unit. */
109 #if GMX_CUDA_NB_SINGLE_COMPILATION_UNIT
110 # include "nbnxm_cuda_kernel_F_noprune.cu"
111 # include "nbnxm_cuda_kernel_F_prune.cu"
112 # include "nbnxm_cuda_kernel_VF_noprune.cu"
113 # include "nbnxm_cuda_kernel_VF_prune.cu"
114 # include "nbnxm_cuda_kernel_pruneonly.cu"
115 #endif /* GMX_CUDA_NB_SINGLE_COMPILATION_UNIT */
120 //! Number of CUDA threads in a block
121 // TODO Optimize this through experimentation
122 constexpr static int c_bufOpsThreadsPerBlock = 128;
124 /*! Nonbonded kernel function pointer type */
125 typedef void (*nbnxn_cu_kfunc_ptr_t)(const NBAtomData, const NBParamGpu, const gpu_plist, bool);
127 /*********************************/
129 /*! Returns the number of blocks to be used for the nonbonded GPU kernel. */
130 static inline int calc_nb_kernel_nblock(int nwork_units, const DeviceInformation* deviceInfo)
135 /* CUDA does not accept grid dimension of 0 (which can happen e.g. with an
136 empty domain) and that case should be handled before this point. */
137 assert(nwork_units > 0);
139 max_grid_x_size = deviceInfo->prop.maxGridSize[0];
141 /* do we exceed the grid x dimension limit? */
142 if (nwork_units > max_grid_x_size)
145 "Watch out, the input system is too large to simulate!\n"
146 "The number of nonbonded work units (=number of super-clusters) exceeds the"
147 "maximum grid size in x dimension (%d > %d)!",
156 /* Constant arrays listing all kernel function pointers and enabling selection
157 of a kernel in an elegant manner. */
159 /*! Pointers to the non-bonded kernels organized in 2-dim arrays by:
160 * electrostatics and VDW type.
162 * Note that the row- and column-order of function pointers has to match the
163 * order of corresponding enumerated electrostatics and vdw types, resp.,
164 * defined in nbnxn_cuda_types.h.
167 /*! Force-only kernel function pointers. */
168 static const nbnxn_cu_kfunc_ptr_t nb_kfunc_noener_noprune_ptr[c_numElecTypes][c_numVdwTypes] = {
169 { nbnxn_kernel_ElecCut_VdwLJ_F_cuda,
170 nbnxn_kernel_ElecCut_VdwLJCombGeom_F_cuda,
171 nbnxn_kernel_ElecCut_VdwLJCombLB_F_cuda,
172 nbnxn_kernel_ElecCut_VdwLJFsw_F_cuda,
173 nbnxn_kernel_ElecCut_VdwLJPsw_F_cuda,
174 nbnxn_kernel_ElecCut_VdwLJEwCombGeom_F_cuda,
175 nbnxn_kernel_ElecCut_VdwLJEwCombLB_F_cuda },
176 { nbnxn_kernel_ElecRF_VdwLJ_F_cuda,
177 nbnxn_kernel_ElecRF_VdwLJCombGeom_F_cuda,
178 nbnxn_kernel_ElecRF_VdwLJCombLB_F_cuda,
179 nbnxn_kernel_ElecRF_VdwLJFsw_F_cuda,
180 nbnxn_kernel_ElecRF_VdwLJPsw_F_cuda,
181 nbnxn_kernel_ElecRF_VdwLJEwCombGeom_F_cuda,
182 nbnxn_kernel_ElecRF_VdwLJEwCombLB_F_cuda },
183 { nbnxn_kernel_ElecEwQSTab_VdwLJ_F_cuda,
184 nbnxn_kernel_ElecEwQSTab_VdwLJCombGeom_F_cuda,
185 nbnxn_kernel_ElecEwQSTab_VdwLJCombLB_F_cuda,
186 nbnxn_kernel_ElecEwQSTab_VdwLJFsw_F_cuda,
187 nbnxn_kernel_ElecEwQSTab_VdwLJPsw_F_cuda,
188 nbnxn_kernel_ElecEwQSTab_VdwLJEwCombGeom_F_cuda,
189 nbnxn_kernel_ElecEwQSTab_VdwLJEwCombLB_F_cuda },
190 { nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJ_F_cuda,
191 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJCombGeom_F_cuda,
192 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJCombLB_F_cuda,
193 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJFsw_F_cuda,
194 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJPsw_F_cuda,
195 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJEwCombGeom_F_cuda,
196 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJEwCombLB_F_cuda },
197 { nbnxn_kernel_ElecEw_VdwLJ_F_cuda,
198 nbnxn_kernel_ElecEw_VdwLJCombGeom_F_cuda,
199 nbnxn_kernel_ElecEw_VdwLJCombLB_F_cuda,
200 nbnxn_kernel_ElecEw_VdwLJFsw_F_cuda,
201 nbnxn_kernel_ElecEw_VdwLJPsw_F_cuda,
202 nbnxn_kernel_ElecEw_VdwLJEwCombGeom_F_cuda,
203 nbnxn_kernel_ElecEw_VdwLJEwCombLB_F_cuda },
204 { nbnxn_kernel_ElecEwTwinCut_VdwLJ_F_cuda,
205 nbnxn_kernel_ElecEwTwinCut_VdwLJCombGeom_F_cuda,
206 nbnxn_kernel_ElecEwTwinCut_VdwLJCombLB_F_cuda,
207 nbnxn_kernel_ElecEwTwinCut_VdwLJFsw_F_cuda,
208 nbnxn_kernel_ElecEwTwinCut_VdwLJPsw_F_cuda,
209 nbnxn_kernel_ElecEwTwinCut_VdwLJEwCombGeom_F_cuda,
210 nbnxn_kernel_ElecEwTwinCut_VdwLJEwCombLB_F_cuda }
213 /*! Force + energy kernel function pointers. */
214 static const nbnxn_cu_kfunc_ptr_t nb_kfunc_ener_noprune_ptr[c_numElecTypes][c_numVdwTypes] = {
215 { nbnxn_kernel_ElecCut_VdwLJ_VF_cuda,
216 nbnxn_kernel_ElecCut_VdwLJCombGeom_VF_cuda,
217 nbnxn_kernel_ElecCut_VdwLJCombLB_VF_cuda,
218 nbnxn_kernel_ElecCut_VdwLJFsw_VF_cuda,
219 nbnxn_kernel_ElecCut_VdwLJPsw_VF_cuda,
220 nbnxn_kernel_ElecCut_VdwLJEwCombGeom_VF_cuda,
221 nbnxn_kernel_ElecCut_VdwLJEwCombLB_VF_cuda },
222 { nbnxn_kernel_ElecRF_VdwLJ_VF_cuda,
223 nbnxn_kernel_ElecRF_VdwLJCombGeom_VF_cuda,
224 nbnxn_kernel_ElecRF_VdwLJCombLB_VF_cuda,
225 nbnxn_kernel_ElecRF_VdwLJFsw_VF_cuda,
226 nbnxn_kernel_ElecRF_VdwLJPsw_VF_cuda,
227 nbnxn_kernel_ElecRF_VdwLJEwCombGeom_VF_cuda,
228 nbnxn_kernel_ElecRF_VdwLJEwCombLB_VF_cuda },
229 { nbnxn_kernel_ElecEwQSTab_VdwLJ_VF_cuda,
230 nbnxn_kernel_ElecEwQSTab_VdwLJCombGeom_VF_cuda,
231 nbnxn_kernel_ElecEwQSTab_VdwLJCombLB_VF_cuda,
232 nbnxn_kernel_ElecEwQSTab_VdwLJFsw_VF_cuda,
233 nbnxn_kernel_ElecEwQSTab_VdwLJPsw_VF_cuda,
234 nbnxn_kernel_ElecEwQSTab_VdwLJEwCombGeom_VF_cuda,
235 nbnxn_kernel_ElecEwQSTab_VdwLJEwCombLB_VF_cuda },
236 { nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJ_VF_cuda,
237 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJCombGeom_VF_cuda,
238 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJCombLB_VF_cuda,
239 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJFsw_VF_cuda,
240 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJPsw_VF_cuda,
241 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJEwCombGeom_VF_cuda,
242 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJEwCombLB_VF_cuda },
243 { nbnxn_kernel_ElecEw_VdwLJ_VF_cuda,
244 nbnxn_kernel_ElecEw_VdwLJCombGeom_VF_cuda,
245 nbnxn_kernel_ElecEw_VdwLJCombLB_VF_cuda,
246 nbnxn_kernel_ElecEw_VdwLJFsw_VF_cuda,
247 nbnxn_kernel_ElecEw_VdwLJPsw_VF_cuda,
248 nbnxn_kernel_ElecEw_VdwLJEwCombGeom_VF_cuda,
249 nbnxn_kernel_ElecEw_VdwLJEwCombLB_VF_cuda },
250 { nbnxn_kernel_ElecEwTwinCut_VdwLJ_VF_cuda,
251 nbnxn_kernel_ElecEwTwinCut_VdwLJCombGeom_VF_cuda,
252 nbnxn_kernel_ElecEwTwinCut_VdwLJCombLB_VF_cuda,
253 nbnxn_kernel_ElecEwTwinCut_VdwLJFsw_VF_cuda,
254 nbnxn_kernel_ElecEwTwinCut_VdwLJPsw_VF_cuda,
255 nbnxn_kernel_ElecEwTwinCut_VdwLJEwCombGeom_VF_cuda,
256 nbnxn_kernel_ElecEwTwinCut_VdwLJEwCombLB_VF_cuda }
259 /*! Force + pruning kernel function pointers. */
260 static const nbnxn_cu_kfunc_ptr_t nb_kfunc_noener_prune_ptr[c_numElecTypes][c_numVdwTypes] = {
261 { nbnxn_kernel_ElecCut_VdwLJ_F_prune_cuda,
262 nbnxn_kernel_ElecCut_VdwLJCombGeom_F_prune_cuda,
263 nbnxn_kernel_ElecCut_VdwLJCombLB_F_prune_cuda,
264 nbnxn_kernel_ElecCut_VdwLJFsw_F_prune_cuda,
265 nbnxn_kernel_ElecCut_VdwLJPsw_F_prune_cuda,
266 nbnxn_kernel_ElecCut_VdwLJEwCombGeom_F_prune_cuda,
267 nbnxn_kernel_ElecCut_VdwLJEwCombLB_F_prune_cuda },
268 { nbnxn_kernel_ElecRF_VdwLJ_F_prune_cuda,
269 nbnxn_kernel_ElecRF_VdwLJCombGeom_F_prune_cuda,
270 nbnxn_kernel_ElecRF_VdwLJCombLB_F_prune_cuda,
271 nbnxn_kernel_ElecRF_VdwLJFsw_F_prune_cuda,
272 nbnxn_kernel_ElecRF_VdwLJPsw_F_prune_cuda,
273 nbnxn_kernel_ElecRF_VdwLJEwCombGeom_F_prune_cuda,
274 nbnxn_kernel_ElecRF_VdwLJEwCombLB_F_prune_cuda },
275 { nbnxn_kernel_ElecEwQSTab_VdwLJ_F_prune_cuda,
276 nbnxn_kernel_ElecEwQSTab_VdwLJCombGeom_F_prune_cuda,
277 nbnxn_kernel_ElecEwQSTab_VdwLJCombLB_F_prune_cuda,
278 nbnxn_kernel_ElecEwQSTab_VdwLJFsw_F_prune_cuda,
279 nbnxn_kernel_ElecEwQSTab_VdwLJPsw_F_prune_cuda,
280 nbnxn_kernel_ElecEwQSTab_VdwLJEwCombGeom_F_prune_cuda,
281 nbnxn_kernel_ElecEwQSTab_VdwLJEwCombLB_F_prune_cuda },
282 { nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJ_F_prune_cuda,
283 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJCombGeom_F_prune_cuda,
284 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJCombLB_F_prune_cuda,
285 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJFsw_F_prune_cuda,
286 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJPsw_F_prune_cuda,
287 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJEwCombGeom_F_prune_cuda,
288 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJEwCombLB_F_prune_cuda },
289 { nbnxn_kernel_ElecEw_VdwLJ_F_prune_cuda,
290 nbnxn_kernel_ElecEw_VdwLJCombGeom_F_prune_cuda,
291 nbnxn_kernel_ElecEw_VdwLJCombLB_F_prune_cuda,
292 nbnxn_kernel_ElecEw_VdwLJFsw_F_prune_cuda,
293 nbnxn_kernel_ElecEw_VdwLJPsw_F_prune_cuda,
294 nbnxn_kernel_ElecEw_VdwLJEwCombGeom_F_prune_cuda,
295 nbnxn_kernel_ElecEw_VdwLJEwCombLB_F_prune_cuda },
296 { nbnxn_kernel_ElecEwTwinCut_VdwLJ_F_prune_cuda,
297 nbnxn_kernel_ElecEwTwinCut_VdwLJCombGeom_F_prune_cuda,
298 nbnxn_kernel_ElecEwTwinCut_VdwLJCombLB_F_prune_cuda,
299 nbnxn_kernel_ElecEwTwinCut_VdwLJFsw_F_prune_cuda,
300 nbnxn_kernel_ElecEwTwinCut_VdwLJPsw_F_prune_cuda,
301 nbnxn_kernel_ElecEwTwinCut_VdwLJEwCombGeom_F_prune_cuda,
302 nbnxn_kernel_ElecEwTwinCut_VdwLJEwCombLB_F_prune_cuda }
305 /*! Force + energy + pruning kernel function pointers. */
306 static const nbnxn_cu_kfunc_ptr_t nb_kfunc_ener_prune_ptr[c_numElecTypes][c_numVdwTypes] = {
307 { nbnxn_kernel_ElecCut_VdwLJ_VF_prune_cuda,
308 nbnxn_kernel_ElecCut_VdwLJCombGeom_VF_prune_cuda,
309 nbnxn_kernel_ElecCut_VdwLJCombLB_VF_prune_cuda,
310 nbnxn_kernel_ElecCut_VdwLJFsw_VF_prune_cuda,
311 nbnxn_kernel_ElecCut_VdwLJPsw_VF_prune_cuda,
312 nbnxn_kernel_ElecCut_VdwLJEwCombGeom_VF_prune_cuda,
313 nbnxn_kernel_ElecCut_VdwLJEwCombLB_VF_prune_cuda },
314 { nbnxn_kernel_ElecRF_VdwLJ_VF_prune_cuda,
315 nbnxn_kernel_ElecRF_VdwLJCombGeom_VF_prune_cuda,
316 nbnxn_kernel_ElecRF_VdwLJCombLB_VF_prune_cuda,
317 nbnxn_kernel_ElecRF_VdwLJFsw_VF_prune_cuda,
318 nbnxn_kernel_ElecRF_VdwLJPsw_VF_prune_cuda,
319 nbnxn_kernel_ElecRF_VdwLJEwCombGeom_VF_prune_cuda,
320 nbnxn_kernel_ElecRF_VdwLJEwCombLB_VF_prune_cuda },
321 { nbnxn_kernel_ElecEwQSTab_VdwLJ_VF_prune_cuda,
322 nbnxn_kernel_ElecEwQSTab_VdwLJCombGeom_VF_prune_cuda,
323 nbnxn_kernel_ElecEwQSTab_VdwLJCombLB_VF_prune_cuda,
324 nbnxn_kernel_ElecEwQSTab_VdwLJFsw_VF_prune_cuda,
325 nbnxn_kernel_ElecEwQSTab_VdwLJPsw_VF_prune_cuda,
326 nbnxn_kernel_ElecEwQSTab_VdwLJEwCombGeom_VF_prune_cuda,
327 nbnxn_kernel_ElecEwQSTab_VdwLJEwCombLB_VF_prune_cuda },
328 { nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJ_VF_prune_cuda,
329 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJCombGeom_VF_prune_cuda,
330 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJCombLB_VF_prune_cuda,
331 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJFsw_VF_prune_cuda,
332 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJPsw_VF_prune_cuda,
333 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJEwCombGeom_VF_prune_cuda,
334 nbnxn_kernel_ElecEwQSTabTwinCut_VdwLJEwCombLB_VF_prune_cuda },
335 { nbnxn_kernel_ElecEw_VdwLJ_VF_prune_cuda,
336 nbnxn_kernel_ElecEw_VdwLJCombGeom_VF_prune_cuda,
337 nbnxn_kernel_ElecEw_VdwLJCombLB_VF_prune_cuda,
338 nbnxn_kernel_ElecEw_VdwLJFsw_VF_prune_cuda,
339 nbnxn_kernel_ElecEw_VdwLJPsw_VF_prune_cuda,
340 nbnxn_kernel_ElecEw_VdwLJEwCombGeom_VF_prune_cuda,
341 nbnxn_kernel_ElecEw_VdwLJEwCombLB_VF_prune_cuda },
342 { nbnxn_kernel_ElecEwTwinCut_VdwLJ_VF_prune_cuda,
343 nbnxn_kernel_ElecEwTwinCut_VdwLJCombGeom_VF_prune_cuda,
344 nbnxn_kernel_ElecEwTwinCut_VdwLJCombLB_VF_prune_cuda,
345 nbnxn_kernel_ElecEwTwinCut_VdwLJFsw_VF_prune_cuda,
346 nbnxn_kernel_ElecEwTwinCut_VdwLJPsw_VF_prune_cuda,
347 nbnxn_kernel_ElecEwTwinCut_VdwLJEwCombGeom_VF_prune_cuda,
348 nbnxn_kernel_ElecEwTwinCut_VdwLJEwCombLB_VF_prune_cuda }
351 /*! Return a pointer to the kernel version to be executed at the current step. */
352 static inline nbnxn_cu_kfunc_ptr_t select_nbnxn_kernel(enum ElecType elecType,
353 enum VdwType vdwType,
356 const DeviceInformation gmx_unused* deviceInfo)
358 const int elecTypeIdx = static_cast<int>(elecType);
359 const int vdwTypeIdx = static_cast<int>(vdwType);
361 GMX_ASSERT(elecTypeIdx < c_numElecTypes,
362 "The electrostatics type requested is not implemented in the CUDA kernels.");
363 GMX_ASSERT(vdwTypeIdx < c_numVdwTypes,
364 "The VdW type requested is not implemented in the CUDA kernels.");
366 /* assert assumptions made by the kernels */
367 GMX_ASSERT(c_nbnxnGpuClusterSize * c_nbnxnGpuClusterSize / c_nbnxnGpuClusterpairSplit
368 == deviceInfo->prop.warpSize,
369 "The CUDA kernels require the "
370 "cluster_size_i*cluster_size_j/nbnxn_gpu_clusterpair_split to match the warp size "
371 "of the architecture targeted.");
377 return nb_kfunc_ener_prune_ptr[elecTypeIdx][vdwTypeIdx];
381 return nb_kfunc_ener_noprune_ptr[elecTypeIdx][vdwTypeIdx];
388 return nb_kfunc_noener_prune_ptr[elecTypeIdx][vdwTypeIdx];
392 return nb_kfunc_noener_noprune_ptr[elecTypeIdx][vdwTypeIdx];
397 /*! \brief Calculates the amount of shared memory required by the nonbonded kernel in use. */
398 static inline int calc_shmem_required_nonbonded(const int num_threads_z,
399 const DeviceInformation gmx_unused* deviceInfo,
400 const NBParamGpu* nbp)
406 /* size of shmem (force-buffers/xq/atom type preloading) */
407 /* NOTE: with the default kernel on sm3.0 we need shmem only for pre-loading */
408 /* i-atom x+q in shared memory */
409 shmem = c_nbnxnGpuNumClusterPerSupercluster * c_clSize * sizeof(float4);
410 /* cj in shared memory, for each warp separately */
411 shmem += num_threads_z * c_nbnxnGpuClusterpairSplit * c_nbnxnGpuJgroupSize * sizeof(int);
413 if (nbp->vdwType == VdwType::CutCombGeom || nbp->vdwType == VdwType::CutCombLB)
415 /* i-atom LJ combination parameters in shared memory */
416 shmem += c_nbnxnGpuNumClusterPerSupercluster * c_clSize * sizeof(float2);
420 /* i-atom types in shared memory */
421 shmem += c_nbnxnGpuNumClusterPerSupercluster * c_clSize * sizeof(int);
427 void nbnxnInsertNonlocalGpuDependency(NbnxmGpu* nb, const InteractionLocality interactionLocality)
429 const DeviceStream& deviceStream = *nb->deviceStreams[interactionLocality];
431 /* When we get here all misc operations issued in the local stream as well as
432 the local xq H2D are done,
433 so we record that in the local stream and wait for it in the nonlocal one.
434 This wait needs to precede any PP tasks, bonded or nonbonded, that may
435 compute on interactions between local and nonlocal atoms.
437 if (nb->bUseTwoStreams)
439 if (interactionLocality == InteractionLocality::Local)
441 nb->misc_ops_and_local_H2D_done.markEvent(deviceStream);
445 nb->misc_ops_and_local_H2D_done.enqueueWaitEvent(deviceStream);
450 /*! \brief Launch asynchronously the xq buffer host to device copy. */
451 void gpu_copy_xq_to_gpu(NbnxmGpu* nb, const nbnxn_atomdata_t* nbatom, const AtomLocality atomLocality)
453 GMX_ASSERT(nb, "Need a valid nbnxn_gpu object");
455 const InteractionLocality iloc = gpuAtomToInteractionLocality(atomLocality);
458 NBAtomData* adat = nb->atdat;
459 gpu_plist* plist = nb->plist[iloc];
460 Nbnxm::GpuTimers* timers = nb->timers;
461 const DeviceStream& deviceStream = *nb->deviceStreams[iloc];
463 bool bDoTime = nb->bDoTime;
465 /* Don't launch the non-local H2D copy if there is no dependent
466 work to do: neither non-local nor other (e.g. bonded) work
467 to do that has as input the nbnxn coordaintes.
468 Doing the same for the local kernel is more complicated, since the
469 local part of the force array also depends on the non-local kernel.
470 So to avoid complicating the code and to reduce the risk of bugs,
471 we always call the local local x+q copy (and the rest of the local
472 work in nbnxn_gpu_launch_kernel().
474 if ((iloc == InteractionLocality::NonLocal) && !haveGpuShortRangeWork(*nb, iloc))
476 plist->haveFreshList = false;
478 // The event is marked for Local interactions unconditionally,
479 // so it has to be released here because of the early return
480 // for NonLocal interactions.
481 nb->misc_ops_and_local_H2D_done.reset();
486 /* local/nonlocal offset and length used for xq and f */
487 auto atomsRange = getGpuAtomRange(adat, atomLocality);
489 /* beginning of timed HtoD section */
492 timers->xf[atomLocality].nb_h2d.openTimingRegion(deviceStream);
496 static_assert(sizeof(adat->xq[0]) == sizeof(Float4),
497 "The size of the xyzq buffer element should be equal to the size of float4.");
498 copyToDeviceBuffer(&adat->xq,
499 reinterpret_cast<const Float4*>(nbatom->x().data()) + atomsRange.begin(),
503 GpuApiCallBehavior::Async,
508 timers->xf[atomLocality].nb_h2d.closeTimingRegion(deviceStream);
511 /* When we get here all misc operations issued in the local stream as well as
512 the local xq H2D are done,
513 so we record that in the local stream and wait for it in the nonlocal one.
514 This wait needs to precede any PP tasks, bonded or nonbonded, that may
515 compute on interactions between local and nonlocal atoms.
517 nbnxnInsertNonlocalGpuDependency(nb, iloc);
520 /*! As we execute nonbonded workload in separate streams, before launching
521 the kernel we need to make sure that he following operations have completed:
522 - atomdata allocation and related H2D transfers (every nstlist step);
523 - pair list H2D transfer (every nstlist step);
524 - shift vector H2D transfer (every nstlist step);
525 - force (+shift force and energy) output clearing (every step).
527 These operations are issued in the local stream at the beginning of the step
528 and therefore always complete before the local kernel launch. The non-local
529 kernel is launched after the local on the same device/context hence it is
530 inherently scheduled after the operations in the local stream (including the
531 above "misc_ops") on pre-GK110 devices with single hardware queue, but on later
532 devices with multiple hardware queues the dependency needs to be enforced.
533 We use the misc_ops_and_local_H2D_done event to record the point where
534 the local x+q H2D (and all preceding) tasks are complete and synchronize
535 with this event in the non-local stream before launching the non-bonded kernel.
537 void gpu_launch_kernel(NbnxmGpu* nb, const gmx::StepWorkload& stepWork, const InteractionLocality iloc)
539 NBAtomData* adat = nb->atdat;
540 NBParamGpu* nbp = nb->nbparam;
541 gpu_plist* plist = nb->plist[iloc];
542 Nbnxm::GpuTimers* timers = nb->timers;
543 const DeviceStream& deviceStream = *nb->deviceStreams[iloc];
545 bool bDoTime = nb->bDoTime;
547 /* Don't launch the non-local kernel if there is no work to do.
548 Doing the same for the local kernel is more complicated, since the
549 local part of the force array also depends on the non-local kernel.
550 So to avoid complicating the code and to reduce the risk of bugs,
551 we always call the local kernel, and later (not in
552 this function) the stream wait, local f copyback and the f buffer
553 clearing. All these operations, except for the local interaction kernel,
554 are needed for the non-local interactions. The skip of the local kernel
555 call is taken care of later in this function. */
556 if (canSkipNonbondedWork(*nb, iloc))
558 plist->haveFreshList = false;
563 if (nbp->useDynamicPruning && plist->haveFreshList)
565 /* Prunes for rlistOuter and rlistInner, sets plist->haveFreshList=false
566 (TODO: ATM that's the way the timing accounting can distinguish between
567 separate prune kernel and combined force+prune, maybe we need a better way?).
569 gpu_launch_kernel_pruneonly(nb, iloc, 1);
572 if (plist->nsci == 0)
574 /* Don't launch an empty local kernel (not allowed with CUDA) */
578 /* beginning of timed nonbonded calculation section */
581 timers->interaction[iloc].nb_k.openTimingRegion(deviceStream);
584 /* Kernel launch config:
585 * - The thread block dimensions match the size of i-clusters, j-clusters,
586 * and j-cluster concurrency, in x, y, and z, respectively.
587 * - The 1D block-grid contains as many blocks as super-clusters.
589 int num_threads_z = 1;
590 if (nb->deviceContext_->deviceInfo().prop.major == 3 && nb->deviceContext_->deviceInfo().prop.minor == 7)
594 int nblock = calc_nb_kernel_nblock(plist->nsci, &nb->deviceContext_->deviceInfo());
597 KernelLaunchConfig config;
598 config.blockSize[0] = c_clSize;
599 config.blockSize[1] = c_clSize;
600 config.blockSize[2] = num_threads_z;
601 config.gridSize[0] = nblock;
602 config.sharedMemorySize =
603 calc_shmem_required_nonbonded(num_threads_z, &nb->deviceContext_->deviceInfo(), nbp);
608 "Non-bonded GPU launch configuration:\n\tThread block: %zux%zux%zu\n\t"
609 "\tGrid: %zux%zu\n\t#Super-clusters/clusters: %d/%d (%d)\n"
616 plist->nsci * c_nbnxnGpuNumClusterPerSupercluster,
617 c_nbnxnGpuNumClusterPerSupercluster,
619 config.sharedMemorySize);
622 auto* timingEvent = bDoTime ? timers->interaction[iloc].nb_k.fetchNextEvent() : nullptr;
624 select_nbnxn_kernel(nbp->elecType,
626 stepWork.computeEnergy,
627 (plist->haveFreshList && !nb->timers->interaction[iloc].didPrune),
628 &nb->deviceContext_->deviceInfo());
629 const auto kernelArgs =
630 prepareGpuKernelArguments(kernel, config, adat, nbp, plist, &stepWork.computeVirial);
631 launchGpuKernel(kernel, config, deviceStream, timingEvent, "k_calc_nb", kernelArgs);
635 timers->interaction[iloc].nb_k.closeTimingRegion(deviceStream);
638 if (GMX_NATIVE_WINDOWS)
640 /* Windows: force flushing WDDM queue */
641 cudaStreamQuery(deviceStream.stream());
645 /*! Calculates the amount of shared memory required by the CUDA kernel in use. */
646 static inline int calc_shmem_required_prune(const int num_threads_z)
650 /* i-atom x in shared memory */
651 shmem = c_nbnxnGpuNumClusterPerSupercluster * c_clSize * sizeof(float4);
652 /* cj in shared memory, for each warp separately */
653 shmem += num_threads_z * c_nbnxnGpuClusterpairSplit * c_nbnxnGpuJgroupSize * sizeof(int);
658 void gpu_launch_kernel_pruneonly(NbnxmGpu* nb, const InteractionLocality iloc, const int numParts)
660 NBAtomData* adat = nb->atdat;
661 NBParamGpu* nbp = nb->nbparam;
662 gpu_plist* plist = nb->plist[iloc];
663 Nbnxm::GpuTimers* timers = nb->timers;
664 const DeviceStream& deviceStream = *nb->deviceStreams[iloc];
666 bool bDoTime = nb->bDoTime;
668 if (plist->haveFreshList)
670 GMX_ASSERT(numParts == 1, "With first pruning we expect 1 part");
672 /* Set rollingPruningNumParts to signal that it is not set */
673 plist->rollingPruningNumParts = 0;
674 plist->rollingPruningPart = 0;
678 if (plist->rollingPruningNumParts == 0)
680 plist->rollingPruningNumParts = numParts;
684 GMX_ASSERT(numParts == plist->rollingPruningNumParts,
685 "It is not allowed to change numParts in between list generation steps");
689 /* Use a local variable for part and update in plist, so we can return here
690 * without duplicating the part increment code.
692 int part = plist->rollingPruningPart;
694 plist->rollingPruningPart++;
695 if (plist->rollingPruningPart >= plist->rollingPruningNumParts)
697 plist->rollingPruningPart = 0;
700 /* Compute the number of list entries to prune in this pass */
701 int numSciInPart = (plist->nsci - part) / numParts;
703 /* Don't launch the kernel if there is no work to do (not allowed with CUDA) */
704 if (numSciInPart <= 0)
706 plist->haveFreshList = false;
711 GpuRegionTimer* timer = nullptr;
714 timer = &(plist->haveFreshList ? timers->interaction[iloc].prune_k
715 : timers->interaction[iloc].rollingPrune_k);
718 /* beginning of timed prune calculation section */
721 timer->openTimingRegion(deviceStream);
724 /* Kernel launch config:
725 * - The thread block dimensions match the size of i-clusters, j-clusters,
726 * and j-cluster concurrency, in x, y, and z, respectively.
727 * - The 1D block-grid contains as many blocks as super-clusters.
729 int num_threads_z = c_pruneKernelJ4Concurrency;
730 int nblock = calc_nb_kernel_nblock(numSciInPart, &nb->deviceContext_->deviceInfo());
731 KernelLaunchConfig config;
732 config.blockSize[0] = c_clSize;
733 config.blockSize[1] = c_clSize;
734 config.blockSize[2] = num_threads_z;
735 config.gridSize[0] = nblock;
736 config.sharedMemorySize = calc_shmem_required_prune(num_threads_z);
741 "Pruning GPU kernel launch configuration:\n\tThread block: %zux%zux%zu\n\t"
742 "\tGrid: %zux%zu\n\t#Super-clusters/clusters: %d/%d (%d)\n"
749 numSciInPart * c_nbnxnGpuNumClusterPerSupercluster,
750 c_nbnxnGpuNumClusterPerSupercluster,
752 config.sharedMemorySize);
755 auto* timingEvent = bDoTime ? timer->fetchNextEvent() : nullptr;
756 constexpr char kernelName[] = "k_pruneonly";
758 plist->haveFreshList ? nbnxn_kernel_prune_cuda<true> : nbnxn_kernel_prune_cuda<false>;
759 const auto kernelArgs = prepareGpuKernelArguments(kernel, config, adat, nbp, plist, &numParts, &part);
760 launchGpuKernel(kernel, config, deviceStream, timingEvent, kernelName, kernelArgs);
762 /* TODO: consider a more elegant way to track which kernel has been called
763 (combined or separate 1st pass prune, rolling prune). */
764 if (plist->haveFreshList)
766 plist->haveFreshList = false;
767 /* Mark that pruning has been done */
768 nb->timers->interaction[iloc].didPrune = true;
772 /* Mark that rolling pruning has been done */
773 nb->timers->interaction[iloc].didRollingPrune = true;
778 timer->closeTimingRegion(deviceStream);
781 if (GMX_NATIVE_WINDOWS)
783 /* Windows: force flushing WDDM queue */
784 cudaStreamQuery(deviceStream.stream());
788 void gpu_launch_cpyback(NbnxmGpu* nb,
789 nbnxn_atomdata_t* nbatom,
790 const gmx::StepWorkload& stepWork,
791 const AtomLocality atomLocality)
793 GMX_ASSERT(nb, "Need a valid nbnxn_gpu object");
795 /* determine interaction locality from atom locality */
796 const InteractionLocality iloc = gpuAtomToInteractionLocality(atomLocality);
797 GMX_ASSERT(iloc == InteractionLocality::Local
798 || (iloc == InteractionLocality::NonLocal && nb->bNonLocalStreamDoneMarked == false),
799 "Non-local stream is indicating that the copy back event is enqueued at the "
800 "beginning of the copy back function.");
802 /* extract the data */
803 NBAtomData* adat = nb->atdat;
804 Nbnxm::GpuTimers* timers = nb->timers;
805 bool bDoTime = nb->bDoTime;
806 const DeviceStream& deviceStream = *nb->deviceStreams[iloc];
808 /* don't launch non-local copy-back if there was no non-local work to do */
809 if ((iloc == InteractionLocality::NonLocal) && !haveGpuShortRangeWork(*nb, iloc))
811 nb->bNonLocalStreamDoneMarked = false;
815 /* local/nonlocal offset and length used for xq and f */
816 auto atomsRange = getGpuAtomRange(adat, atomLocality);
818 /* beginning of timed D2H section */
821 timers->xf[atomLocality].nb_d2h.openTimingRegion(deviceStream);
824 /* With DD the local D2H transfer can only start after the non-local
825 kernel has finished. */
826 if (iloc == InteractionLocality::Local && nb->bNonLocalStreamDoneMarked)
828 nb->nonlocal_done.enqueueWaitEvent(deviceStream);
829 nb->bNonLocalStreamDoneMarked = false;
833 * Skip if buffer ops / reduction is offloaded to the GPU.
835 if (!stepWork.useGpuFBufferOps)
838 sizeof(adat->f[0]) == sizeof(Float3),
839 "The size of the force buffer element should be equal to the size of float3.");
840 copyFromDeviceBuffer(reinterpret_cast<Float3*>(nbatom->out[0].f.data()) + atomsRange.begin(),
845 GpuApiCallBehavior::Async,
849 /* After the non-local D2H is launched the nonlocal_done event can be
850 recorded which signals that the local D2H can proceed. This event is not
851 placed after the non-local kernel because we want the non-local data
853 if (iloc == InteractionLocality::NonLocal)
855 nb->nonlocal_done.markEvent(deviceStream);
856 nb->bNonLocalStreamDoneMarked = true;
859 /* only transfer energies in the local stream */
860 if (iloc == InteractionLocality::Local)
862 /* DtoH fshift when virial is needed */
863 if (stepWork.computeVirial)
865 static_assert(sizeof(nb->nbst.fShift[0]) == sizeof(adat->fShift[0]),
866 "Sizes of host- and device-side shift vectors should be the same.");
867 copyFromDeviceBuffer(
868 nb->nbst.fShift, &adat->fShift, 0, SHIFTS, deviceStream, GpuApiCallBehavior::Async, nullptr);
872 if (stepWork.computeEnergy)
874 static_assert(sizeof(nb->nbst.eLJ[0]) == sizeof(adat->eLJ[0]),
875 "Sizes of host- and device-side LJ energy terms should be the same.");
876 copyFromDeviceBuffer(
877 nb->nbst.eLJ, &adat->eLJ, 0, 1, deviceStream, GpuApiCallBehavior::Async, nullptr);
878 static_assert(sizeof(nb->nbst.eElec[0]) == sizeof(adat->eElec[0]),
879 "Sizes of host- and device-side electrostatic energy terms should be the "
881 copyFromDeviceBuffer(
882 nb->nbst.eElec, &adat->eElec, 0, 1, deviceStream, GpuApiCallBehavior::Async, nullptr);
888 timers->xf[atomLocality].nb_d2h.closeTimingRegion(deviceStream);
892 void cuda_set_cacheconfig()
896 for (int i = 0; i < c_numElecTypes; i++)
898 for (int j = 0; j < c_numVdwTypes; j++)
900 /* Default kernel 32/32 kB Shared/L1 */
901 cudaFuncSetCacheConfig(nb_kfunc_ener_prune_ptr[i][j], cudaFuncCachePreferEqual);
902 cudaFuncSetCacheConfig(nb_kfunc_ener_noprune_ptr[i][j], cudaFuncCachePreferEqual);
903 cudaFuncSetCacheConfig(nb_kfunc_noener_prune_ptr[i][j], cudaFuncCachePreferEqual);
904 stat = cudaFuncSetCacheConfig(nb_kfunc_noener_noprune_ptr[i][j], cudaFuncCachePreferEqual);
905 CU_RET_ERR(stat, "cudaFuncSetCacheConfig failed");
910 /* X buffer operations on GPU: performs conversion from rvec to nb format. */
911 void nbnxn_gpu_x_to_nbat_x(const Nbnxm::Grid& grid,
912 bool setFillerCoords,
914 DeviceBuffer<gmx::RVec> d_x,
915 GpuEventSynchronizer* xReadyOnDevice,
916 const Nbnxm::AtomLocality locality,
920 GMX_ASSERT(nb, "Need a valid nbnxn_gpu object");
922 NBAtomData* adat = nb->atdat;
924 const int numColumns = grid.numColumns();
925 const int cellOffset = grid.cellOffset();
926 const int numAtomsPerCell = grid.numAtomsPerCell();
927 Nbnxm::InteractionLocality interactionLoc = gpuAtomToInteractionLocality(locality);
929 const DeviceStream& deviceStream = *nb->deviceStreams[interactionLoc];
931 int numAtoms = grid.srcAtomEnd() - grid.srcAtomBegin();
932 // avoid empty kernel launch, skip to inserting stream dependency
935 // TODO: This will only work with CUDA
936 GMX_ASSERT(d_x, "Need a valid device pointer");
938 // ensure that coordinates are ready on the device before launching the kernel
939 GMX_ASSERT(xReadyOnDevice, "Need a valid GpuEventSynchronizer object");
940 xReadyOnDevice->enqueueWaitEvent(deviceStream);
942 KernelLaunchConfig config;
943 config.blockSize[0] = c_bufOpsThreadsPerBlock;
944 config.blockSize[1] = 1;
945 config.blockSize[2] = 1;
946 config.gridSize[0] = (grid.numCellsColumnMax() * numAtomsPerCell + c_bufOpsThreadsPerBlock - 1)
947 / c_bufOpsThreadsPerBlock;
948 config.gridSize[1] = numColumns;
949 config.gridSize[2] = 1;
950 GMX_ASSERT(config.gridSize[0] > 0,
951 "Can not have empty grid, early return above avoids this");
952 config.sharedMemorySize = 0;
954 auto kernelFn = setFillerCoords ? nbnxn_gpu_x_to_nbat_x_kernel<true>
955 : nbnxn_gpu_x_to_nbat_x_kernel<false>;
956 float4* d_xq = adat->xq;
957 float3* d_xFloat3 = asFloat3(d_x);
958 const int* d_atomIndices = nb->atomIndices;
959 const int* d_cxy_na = &nb->cxy_na[numColumnsMax * gridId];
960 const int* d_cxy_ind = &nb->cxy_ind[numColumnsMax * gridId];
961 const auto kernelArgs = prepareGpuKernelArguments(kernelFn,
971 launchGpuKernel(kernelFn, config, deviceStream, nullptr, "XbufferOps", kernelArgs);
974 // TODO: note that this is not necessary when there are no local atoms, that is:
975 // (numAtoms == 0 && interactionLoc == InteractionLocality::Local)
976 // but for now we avoid that optimization
977 nbnxnInsertNonlocalGpuDependency(nb, interactionLoc);
980 void* getGpuForces(NbnxmGpu* nb)