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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 /*! As we execute nonbonded workload in separate streams, before launching
451 the kernel we need to make sure that he following operations have completed:
452 - atomdata allocation and related H2D transfers (every nstlist step);
453 - pair list H2D transfer (every nstlist step);
454 - shift vector H2D transfer (every nstlist step);
455 - force (+shift force and energy) output clearing (every step).
457 These operations are issued in the local stream at the beginning of the step
458 and therefore always complete before the local kernel launch. The non-local
459 kernel is launched after the local on the same device/context hence it is
460 inherently scheduled after the operations in the local stream (including the
461 above "misc_ops") on pre-GK110 devices with single hardware queue, but on later
462 devices with multiple hardware queues the dependency needs to be enforced.
463 We use the misc_ops_and_local_H2D_done event to record the point where
464 the local x+q H2D (and all preceding) tasks are complete and synchronize
465 with this event in the non-local stream before launching the non-bonded kernel.
467 void gpu_launch_kernel(NbnxmGpu* nb, const gmx::StepWorkload& stepWork, const InteractionLocality iloc)
469 NBAtomData* adat = nb->atdat;
470 NBParamGpu* nbp = nb->nbparam;
471 gpu_plist* plist = nb->plist[iloc];
472 Nbnxm::GpuTimers* timers = nb->timers;
473 const DeviceStream& deviceStream = *nb->deviceStreams[iloc];
475 bool bDoTime = nb->bDoTime;
477 /* Don't launch the non-local kernel if there is no work to do.
478 Doing the same for the local kernel is more complicated, since the
479 local part of the force array also depends on the non-local kernel.
480 So to avoid complicating the code and to reduce the risk of bugs,
481 we always call the local kernel, and later (not in
482 this function) the stream wait, local f copyback and the f buffer
483 clearing. All these operations, except for the local interaction kernel,
484 are needed for the non-local interactions. The skip of the local kernel
485 call is taken care of later in this function. */
486 if (canSkipNonbondedWork(*nb, iloc))
488 plist->haveFreshList = false;
493 if (nbp->useDynamicPruning && plist->haveFreshList)
495 /* Prunes for rlistOuter and rlistInner, sets plist->haveFreshList=false
496 (TODO: ATM that's the way the timing accounting can distinguish between
497 separate prune kernel and combined force+prune, maybe we need a better way?).
499 gpu_launch_kernel_pruneonly(nb, iloc, 1);
502 if (plist->nsci == 0)
504 /* Don't launch an empty local kernel (not allowed with CUDA) */
508 /* beginning of timed nonbonded calculation section */
511 timers->interaction[iloc].nb_k.openTimingRegion(deviceStream);
514 /* Kernel launch config:
515 * - The thread block dimensions match the size of i-clusters, j-clusters,
516 * and j-cluster concurrency, in x, y, and z, respectively.
517 * - The 1D block-grid contains as many blocks as super-clusters.
519 int num_threads_z = 1;
520 if (nb->deviceContext_->deviceInfo().prop.major == 3 && nb->deviceContext_->deviceInfo().prop.minor == 7)
524 int nblock = calc_nb_kernel_nblock(plist->nsci, &nb->deviceContext_->deviceInfo());
527 KernelLaunchConfig config;
528 config.blockSize[0] = c_clSize;
529 config.blockSize[1] = c_clSize;
530 config.blockSize[2] = num_threads_z;
531 config.gridSize[0] = nblock;
532 config.sharedMemorySize =
533 calc_shmem_required_nonbonded(num_threads_z, &nb->deviceContext_->deviceInfo(), nbp);
538 "Non-bonded GPU launch configuration:\n\tThread block: %zux%zux%zu\n\t"
539 "\tGrid: %zux%zu\n\t#Super-clusters/clusters: %d/%d (%d)\n"
546 plist->nsci * c_nbnxnGpuNumClusterPerSupercluster,
547 c_nbnxnGpuNumClusterPerSupercluster,
549 config.sharedMemorySize);
552 auto* timingEvent = bDoTime ? timers->interaction[iloc].nb_k.fetchNextEvent() : nullptr;
554 select_nbnxn_kernel(nbp->elecType,
556 stepWork.computeEnergy,
557 (plist->haveFreshList && !nb->timers->interaction[iloc].didPrune),
558 &nb->deviceContext_->deviceInfo());
559 const auto kernelArgs =
560 prepareGpuKernelArguments(kernel, config, adat, nbp, plist, &stepWork.computeVirial);
561 launchGpuKernel(kernel, config, deviceStream, timingEvent, "k_calc_nb", kernelArgs);
565 timers->interaction[iloc].nb_k.closeTimingRegion(deviceStream);
568 if (GMX_NATIVE_WINDOWS)
570 /* Windows: force flushing WDDM queue */
571 cudaStreamQuery(deviceStream.stream());
575 /*! Calculates the amount of shared memory required by the CUDA kernel in use. */
576 static inline int calc_shmem_required_prune(const int num_threads_z)
580 /* i-atom x in shared memory */
581 shmem = c_nbnxnGpuNumClusterPerSupercluster * c_clSize * sizeof(float4);
582 /* cj in shared memory, for each warp separately */
583 shmem += num_threads_z * c_nbnxnGpuClusterpairSplit * c_nbnxnGpuJgroupSize * sizeof(int);
588 void gpu_launch_kernel_pruneonly(NbnxmGpu* nb, const InteractionLocality iloc, const int numParts)
590 NBAtomData* adat = nb->atdat;
591 NBParamGpu* nbp = nb->nbparam;
592 gpu_plist* plist = nb->plist[iloc];
593 Nbnxm::GpuTimers* timers = nb->timers;
594 const DeviceStream& deviceStream = *nb->deviceStreams[iloc];
596 bool bDoTime = nb->bDoTime;
598 if (plist->haveFreshList)
600 GMX_ASSERT(numParts == 1, "With first pruning we expect 1 part");
602 /* Set rollingPruningNumParts to signal that it is not set */
603 plist->rollingPruningNumParts = 0;
604 plist->rollingPruningPart = 0;
608 if (plist->rollingPruningNumParts == 0)
610 plist->rollingPruningNumParts = numParts;
614 GMX_ASSERT(numParts == plist->rollingPruningNumParts,
615 "It is not allowed to change numParts in between list generation steps");
619 /* Use a local variable for part and update in plist, so we can return here
620 * without duplicating the part increment code.
622 int part = plist->rollingPruningPart;
624 plist->rollingPruningPart++;
625 if (plist->rollingPruningPart >= plist->rollingPruningNumParts)
627 plist->rollingPruningPart = 0;
630 /* Compute the number of list entries to prune in this pass */
631 int numSciInPart = (plist->nsci - part) / numParts;
633 /* Don't launch the kernel if there is no work to do (not allowed with CUDA) */
634 if (numSciInPart <= 0)
636 plist->haveFreshList = false;
641 GpuRegionTimer* timer = nullptr;
644 timer = &(plist->haveFreshList ? timers->interaction[iloc].prune_k
645 : timers->interaction[iloc].rollingPrune_k);
648 /* beginning of timed prune calculation section */
651 timer->openTimingRegion(deviceStream);
654 /* Kernel launch config:
655 * - The thread block dimensions match the size of i-clusters, j-clusters,
656 * and j-cluster concurrency, in x, y, and z, respectively.
657 * - The 1D block-grid contains as many blocks as super-clusters.
659 int num_threads_z = c_pruneKernelJ4Concurrency;
660 int nblock = calc_nb_kernel_nblock(numSciInPart, &nb->deviceContext_->deviceInfo());
661 KernelLaunchConfig config;
662 config.blockSize[0] = c_clSize;
663 config.blockSize[1] = c_clSize;
664 config.blockSize[2] = num_threads_z;
665 config.gridSize[0] = nblock;
666 config.sharedMemorySize = calc_shmem_required_prune(num_threads_z);
671 "Pruning GPU kernel launch configuration:\n\tThread block: %zux%zux%zu\n\t"
672 "\tGrid: %zux%zu\n\t#Super-clusters/clusters: %d/%d (%d)\n"
679 numSciInPart * c_nbnxnGpuNumClusterPerSupercluster,
680 c_nbnxnGpuNumClusterPerSupercluster,
682 config.sharedMemorySize);
685 auto* timingEvent = bDoTime ? timer->fetchNextEvent() : nullptr;
686 constexpr char kernelName[] = "k_pruneonly";
688 plist->haveFreshList ? nbnxn_kernel_prune_cuda<true> : nbnxn_kernel_prune_cuda<false>;
689 const auto kernelArgs = prepareGpuKernelArguments(kernel, config, adat, nbp, plist, &numParts, &part);
690 launchGpuKernel(kernel, config, deviceStream, timingEvent, kernelName, kernelArgs);
692 /* TODO: consider a more elegant way to track which kernel has been called
693 (combined or separate 1st pass prune, rolling prune). */
694 if (plist->haveFreshList)
696 plist->haveFreshList = false;
697 /* Mark that pruning has been done */
698 nb->timers->interaction[iloc].didPrune = true;
702 /* Mark that rolling pruning has been done */
703 nb->timers->interaction[iloc].didRollingPrune = true;
708 timer->closeTimingRegion(deviceStream);
711 if (GMX_NATIVE_WINDOWS)
713 /* Windows: force flushing WDDM queue */
714 cudaStreamQuery(deviceStream.stream());
718 void gpu_launch_cpyback(NbnxmGpu* nb,
719 nbnxn_atomdata_t* nbatom,
720 const gmx::StepWorkload& stepWork,
721 const AtomLocality atomLocality)
723 GMX_ASSERT(nb, "Need a valid nbnxn_gpu object");
725 /* determine interaction locality from atom locality */
726 const InteractionLocality iloc = gpuAtomToInteractionLocality(atomLocality);
727 GMX_ASSERT(iloc == InteractionLocality::Local
728 || (iloc == InteractionLocality::NonLocal && nb->bNonLocalStreamDoneMarked == false),
729 "Non-local stream is indicating that the copy back event is enqueued at the "
730 "beginning of the copy back function.");
732 /* extract the data */
733 NBAtomData* adat = nb->atdat;
734 Nbnxm::GpuTimers* timers = nb->timers;
735 bool bDoTime = nb->bDoTime;
736 const DeviceStream& deviceStream = *nb->deviceStreams[iloc];
738 /* don't launch non-local copy-back if there was no non-local work to do */
739 if ((iloc == InteractionLocality::NonLocal) && !haveGpuShortRangeWork(*nb, iloc))
741 nb->bNonLocalStreamDoneMarked = false;
745 /* local/nonlocal offset and length used for xq and f */
746 auto atomsRange = getGpuAtomRange(adat, atomLocality);
748 /* beginning of timed D2H section */
751 timers->xf[atomLocality].nb_d2h.openTimingRegion(deviceStream);
754 /* With DD the local D2H transfer can only start after the non-local
755 kernel has finished. */
756 if (iloc == InteractionLocality::Local && nb->bNonLocalStreamDoneMarked)
758 nb->nonlocal_done.enqueueWaitEvent(deviceStream);
759 nb->bNonLocalStreamDoneMarked = false;
763 * Skip if buffer ops / reduction is offloaded to the GPU.
765 if (!stepWork.useGpuFBufferOps)
768 sizeof(adat->f[0]) == sizeof(Float3),
769 "The size of the force buffer element should be equal to the size of float3.");
770 copyFromDeviceBuffer(reinterpret_cast<Float3*>(nbatom->out[0].f.data()) + atomsRange.begin(),
775 GpuApiCallBehavior::Async,
779 /* After the non-local D2H is launched the nonlocal_done event can be
780 recorded which signals that the local D2H can proceed. This event is not
781 placed after the non-local kernel because we want the non-local data
783 if (iloc == InteractionLocality::NonLocal)
785 nb->nonlocal_done.markEvent(deviceStream);
786 nb->bNonLocalStreamDoneMarked = true;
789 /* only transfer energies in the local stream */
790 if (iloc == InteractionLocality::Local)
792 /* DtoH fshift when virial is needed */
793 if (stepWork.computeVirial)
795 static_assert(sizeof(nb->nbst.fShift[0]) == sizeof(adat->fShift[0]),
796 "Sizes of host- and device-side shift vectors should be the same.");
797 copyFromDeviceBuffer(
798 nb->nbst.fShift, &adat->fShift, 0, SHIFTS, deviceStream, GpuApiCallBehavior::Async, nullptr);
802 if (stepWork.computeEnergy)
804 static_assert(sizeof(nb->nbst.eLJ[0]) == sizeof(adat->eLJ[0]),
805 "Sizes of host- and device-side LJ energy terms should be the same.");
806 copyFromDeviceBuffer(
807 nb->nbst.eLJ, &adat->eLJ, 0, 1, deviceStream, GpuApiCallBehavior::Async, nullptr);
808 static_assert(sizeof(nb->nbst.eElec[0]) == sizeof(adat->eElec[0]),
809 "Sizes of host- and device-side electrostatic energy terms should be the "
811 copyFromDeviceBuffer(
812 nb->nbst.eElec, &adat->eElec, 0, 1, deviceStream, GpuApiCallBehavior::Async, nullptr);
818 timers->xf[atomLocality].nb_d2h.closeTimingRegion(deviceStream);
822 void cuda_set_cacheconfig()
826 for (int i = 0; i < c_numElecTypes; i++)
828 for (int j = 0; j < c_numVdwTypes; j++)
830 /* Default kernel 32/32 kB Shared/L1 */
831 cudaFuncSetCacheConfig(nb_kfunc_ener_prune_ptr[i][j], cudaFuncCachePreferEqual);
832 cudaFuncSetCacheConfig(nb_kfunc_ener_noprune_ptr[i][j], cudaFuncCachePreferEqual);
833 cudaFuncSetCacheConfig(nb_kfunc_noener_prune_ptr[i][j], cudaFuncCachePreferEqual);
834 stat = cudaFuncSetCacheConfig(nb_kfunc_noener_noprune_ptr[i][j], cudaFuncCachePreferEqual);
835 CU_RET_ERR(stat, "cudaFuncSetCacheConfig failed");
840 /* X buffer operations on GPU: performs conversion from rvec to nb format. */
841 void nbnxn_gpu_x_to_nbat_x(const Nbnxm::Grid& grid,
843 DeviceBuffer<gmx::RVec> d_x,
844 GpuEventSynchronizer* xReadyOnDevice,
845 const Nbnxm::AtomLocality locality,
849 GMX_ASSERT(nb, "Need a valid nbnxn_gpu object");
851 NBAtomData* adat = nb->atdat;
853 const int numColumns = grid.numColumns();
854 const int cellOffset = grid.cellOffset();
855 const int numAtomsPerCell = grid.numAtomsPerCell();
856 Nbnxm::InteractionLocality interactionLoc = gpuAtomToInteractionLocality(locality);
858 const DeviceStream& deviceStream = *nb->deviceStreams[interactionLoc];
860 int numAtoms = grid.srcAtomEnd() - grid.srcAtomBegin();
861 // avoid empty kernel launch, skip to inserting stream dependency
864 // TODO: This will only work with CUDA
865 GMX_ASSERT(d_x, "Need a valid device pointer");
867 // ensure that coordinates are ready on the device before launching the kernel
868 GMX_ASSERT(xReadyOnDevice, "Need a valid GpuEventSynchronizer object");
869 xReadyOnDevice->enqueueWaitEvent(deviceStream);
871 KernelLaunchConfig config;
872 config.blockSize[0] = c_bufOpsThreadsPerBlock;
873 config.blockSize[1] = 1;
874 config.blockSize[2] = 1;
875 config.gridSize[0] = (grid.numCellsColumnMax() * numAtomsPerCell + c_bufOpsThreadsPerBlock - 1)
876 / c_bufOpsThreadsPerBlock;
877 config.gridSize[1] = numColumns;
878 config.gridSize[2] = 1;
879 GMX_ASSERT(config.gridSize[0] > 0,
880 "Can not have empty grid, early return above avoids this");
881 config.sharedMemorySize = 0;
883 auto kernelFn = nbnxn_gpu_x_to_nbat_x_kernel;
884 float4* d_xq = adat->xq;
885 float3* d_xFloat3 = asFloat3(d_x);
886 const int* d_atomIndices = nb->atomIndices;
887 const int* d_cxy_na = &nb->cxy_na[numColumnsMax * gridId];
888 const int* d_cxy_ind = &nb->cxy_ind[numColumnsMax * gridId];
889 const auto kernelArgs = prepareGpuKernelArguments(kernelFn,
899 launchGpuKernel(kernelFn, config, deviceStream, nullptr, "XbufferOps", kernelArgs);
902 // TODO: note that this is not necessary when there are no local atoms, that is:
903 // (numAtoms == 0 && interactionLoc == InteractionLocality::Local)
904 // but for now we avoid that optimization
905 nbnxnInsertNonlocalGpuDependency(nb, interactionLoc);
908 void* getGpuForces(NbnxmGpu* nb)