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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 /*! As we execute nonbonded workload in separate streams, before launching
428 the kernel we need to make sure that he following operations have completed:
429 - atomdata allocation and related H2D transfers (every nstlist step);
430 - pair list H2D transfer (every nstlist step);
431 - shift vector H2D transfer (every nstlist step);
432 - force (+shift force and energy) output clearing (every step).
434 These operations are issued in the local stream at the beginning of the step
435 and therefore always complete before the local kernel launch. The non-local
436 kernel is launched after the local on the same device/context hence it is
437 inherently scheduled after the operations in the local stream (including the
438 above "misc_ops") on pre-GK110 devices with single hardware queue, but on later
439 devices with multiple hardware queues the dependency needs to be enforced.
440 We use the misc_ops_and_local_H2D_done event to record the point where
441 the local x+q H2D (and all preceding) tasks are complete and synchronize
442 with this event in the non-local stream before launching the non-bonded kernel.
444 void gpu_launch_kernel(NbnxmGpu* nb, const gmx::StepWorkload& stepWork, const InteractionLocality iloc)
446 NBAtomData* adat = nb->atdat;
447 NBParamGpu* nbp = nb->nbparam;
448 gpu_plist* plist = nb->plist[iloc];
449 Nbnxm::GpuTimers* timers = nb->timers;
450 const DeviceStream& deviceStream = *nb->deviceStreams[iloc];
452 bool bDoTime = nb->bDoTime;
454 /* Don't launch the non-local kernel if there is no work to do.
455 Doing the same for the local kernel is more complicated, since the
456 local part of the force array also depends on the non-local kernel.
457 So to avoid complicating the code and to reduce the risk of bugs,
458 we always call the local kernel, and later (not in
459 this function) the stream wait, local f copyback and the f buffer
460 clearing. All these operations, except for the local interaction kernel,
461 are needed for the non-local interactions. The skip of the local kernel
462 call is taken care of later in this function. */
463 if (canSkipNonbondedWork(*nb, iloc))
465 plist->haveFreshList = false;
470 if (nbp->useDynamicPruning && plist->haveFreshList)
472 /* Prunes for rlistOuter and rlistInner, sets plist->haveFreshList=false
473 (TODO: ATM that's the way the timing accounting can distinguish between
474 separate prune kernel and combined force+prune, maybe we need a better way?).
476 gpu_launch_kernel_pruneonly(nb, iloc, 1);
479 if (plist->nsci == 0)
481 /* Don't launch an empty local kernel (not allowed with CUDA) */
485 /* beginning of timed nonbonded calculation section */
488 timers->interaction[iloc].nb_k.openTimingRegion(deviceStream);
491 /* Kernel launch config:
492 * - The thread block dimensions match the size of i-clusters, j-clusters,
493 * and j-cluster concurrency, in x, y, and z, respectively.
494 * - The 1D block-grid contains as many blocks as super-clusters.
496 int num_threads_z = 1;
497 if (nb->deviceContext_->deviceInfo().prop.major == 3 && nb->deviceContext_->deviceInfo().prop.minor == 7)
501 int nblock = calc_nb_kernel_nblock(plist->nsci, &nb->deviceContext_->deviceInfo());
504 KernelLaunchConfig config;
505 config.blockSize[0] = c_clSize;
506 config.blockSize[1] = c_clSize;
507 config.blockSize[2] = num_threads_z;
508 config.gridSize[0] = nblock;
509 config.sharedMemorySize =
510 calc_shmem_required_nonbonded(num_threads_z, &nb->deviceContext_->deviceInfo(), nbp);
515 "Non-bonded GPU launch configuration:\n\tThread block: %zux%zux%zu\n\t"
516 "\tGrid: %zux%zu\n\t#Super-clusters/clusters: %d/%d (%d)\n"
523 plist->nsci * c_nbnxnGpuNumClusterPerSupercluster,
524 c_nbnxnGpuNumClusterPerSupercluster,
526 config.sharedMemorySize);
529 auto* timingEvent = bDoTime ? timers->interaction[iloc].nb_k.fetchNextEvent() : nullptr;
531 select_nbnxn_kernel(nbp->elecType,
533 stepWork.computeEnergy,
534 (plist->haveFreshList && !nb->timers->interaction[iloc].didPrune),
535 &nb->deviceContext_->deviceInfo());
536 const auto kernelArgs =
537 prepareGpuKernelArguments(kernel, config, adat, nbp, plist, &stepWork.computeVirial);
538 launchGpuKernel(kernel, config, deviceStream, timingEvent, "k_calc_nb", kernelArgs);
542 timers->interaction[iloc].nb_k.closeTimingRegion(deviceStream);
545 if (GMX_NATIVE_WINDOWS)
547 /* Windows: force flushing WDDM queue */
548 cudaStreamQuery(deviceStream.stream());
552 /*! Calculates the amount of shared memory required by the CUDA kernel in use. */
553 static inline int calc_shmem_required_prune(const int num_threads_z)
557 /* i-atom x in shared memory */
558 shmem = c_nbnxnGpuNumClusterPerSupercluster * c_clSize * sizeof(float4);
559 /* cj in shared memory, for each warp separately */
560 shmem += num_threads_z * c_nbnxnGpuClusterpairSplit * c_nbnxnGpuJgroupSize * sizeof(int);
565 void gpu_launch_kernel_pruneonly(NbnxmGpu* nb, const InteractionLocality iloc, const int numParts)
567 NBAtomData* adat = nb->atdat;
568 NBParamGpu* nbp = nb->nbparam;
569 gpu_plist* plist = nb->plist[iloc];
570 Nbnxm::GpuTimers* timers = nb->timers;
571 const DeviceStream& deviceStream = *nb->deviceStreams[iloc];
573 bool bDoTime = nb->bDoTime;
575 if (plist->haveFreshList)
577 GMX_ASSERT(numParts == 1, "With first pruning we expect 1 part");
579 /* Set rollingPruningNumParts to signal that it is not set */
580 plist->rollingPruningNumParts = 0;
581 plist->rollingPruningPart = 0;
585 if (plist->rollingPruningNumParts == 0)
587 plist->rollingPruningNumParts = numParts;
591 GMX_ASSERT(numParts == plist->rollingPruningNumParts,
592 "It is not allowed to change numParts in between list generation steps");
596 /* Use a local variable for part and update in plist, so we can return here
597 * without duplicating the part increment code.
599 int part = plist->rollingPruningPart;
601 plist->rollingPruningPart++;
602 if (plist->rollingPruningPart >= plist->rollingPruningNumParts)
604 plist->rollingPruningPart = 0;
607 /* Compute the number of list entries to prune in this pass */
608 int numSciInPart = (plist->nsci - part) / numParts;
610 /* Don't launch the kernel if there is no work to do (not allowed with CUDA) */
611 if (numSciInPart <= 0)
613 plist->haveFreshList = false;
618 GpuRegionTimer* timer = nullptr;
621 timer = &(plist->haveFreshList ? timers->interaction[iloc].prune_k
622 : timers->interaction[iloc].rollingPrune_k);
625 /* beginning of timed prune calculation section */
628 timer->openTimingRegion(deviceStream);
631 /* Kernel launch config:
632 * - The thread block dimensions match the size of i-clusters, j-clusters,
633 * and j-cluster concurrency, in x, y, and z, respectively.
634 * - The 1D block-grid contains as many blocks as super-clusters.
636 int num_threads_z = c_pruneKernelJ4Concurrency;
637 int nblock = calc_nb_kernel_nblock(numSciInPart, &nb->deviceContext_->deviceInfo());
638 KernelLaunchConfig config;
639 config.blockSize[0] = c_clSize;
640 config.blockSize[1] = c_clSize;
641 config.blockSize[2] = num_threads_z;
642 config.gridSize[0] = nblock;
643 config.sharedMemorySize = calc_shmem_required_prune(num_threads_z);
648 "Pruning GPU kernel launch configuration:\n\tThread block: %zux%zux%zu\n\t"
649 "\tGrid: %zux%zu\n\t#Super-clusters/clusters: %d/%d (%d)\n"
656 numSciInPart * c_nbnxnGpuNumClusterPerSupercluster,
657 c_nbnxnGpuNumClusterPerSupercluster,
659 config.sharedMemorySize);
662 auto* timingEvent = bDoTime ? timer->fetchNextEvent() : nullptr;
663 constexpr char kernelName[] = "k_pruneonly";
665 plist->haveFreshList ? nbnxn_kernel_prune_cuda<true> : nbnxn_kernel_prune_cuda<false>;
666 const auto kernelArgs = prepareGpuKernelArguments(kernel, config, adat, nbp, plist, &numParts, &part);
667 launchGpuKernel(kernel, config, deviceStream, timingEvent, kernelName, kernelArgs);
669 /* TODO: consider a more elegant way to track which kernel has been called
670 (combined or separate 1st pass prune, rolling prune). */
671 if (plist->haveFreshList)
673 plist->haveFreshList = false;
674 /* Mark that pruning has been done */
675 nb->timers->interaction[iloc].didPrune = true;
679 /* Mark that rolling pruning has been done */
680 nb->timers->interaction[iloc].didRollingPrune = true;
685 timer->closeTimingRegion(deviceStream);
688 if (GMX_NATIVE_WINDOWS)
690 /* Windows: force flushing WDDM queue */
691 cudaStreamQuery(deviceStream.stream());
695 void gpu_launch_cpyback(NbnxmGpu* nb,
696 nbnxn_atomdata_t* nbatom,
697 const gmx::StepWorkload& stepWork,
698 const AtomLocality atomLocality)
700 GMX_ASSERT(nb, "Need a valid nbnxn_gpu object");
702 /* determine interaction locality from atom locality */
703 const InteractionLocality iloc = gpuAtomToInteractionLocality(atomLocality);
704 GMX_ASSERT(iloc == InteractionLocality::Local
705 || (iloc == InteractionLocality::NonLocal && nb->bNonLocalStreamDoneMarked == false),
706 "Non-local stream is indicating that the copy back event is enqueued at the "
707 "beginning of the copy back function.");
709 /* extract the data */
710 NBAtomData* adat = nb->atdat;
711 Nbnxm::GpuTimers* timers = nb->timers;
712 bool bDoTime = nb->bDoTime;
713 const DeviceStream& deviceStream = *nb->deviceStreams[iloc];
715 /* don't launch non-local copy-back if there was no non-local work to do */
716 if ((iloc == InteractionLocality::NonLocal) && !haveGpuShortRangeWork(*nb, iloc))
718 nb->bNonLocalStreamDoneMarked = false;
722 /* local/nonlocal offset and length used for xq and f */
723 auto atomsRange = getGpuAtomRange(adat, atomLocality);
725 /* beginning of timed D2H section */
728 timers->xf[atomLocality].nb_d2h.openTimingRegion(deviceStream);
731 /* With DD the local D2H transfer can only start after the non-local
732 kernel has finished. */
733 if (iloc == InteractionLocality::Local && nb->bNonLocalStreamDoneMarked)
735 nb->nonlocal_done.enqueueWaitEvent(deviceStream);
736 nb->bNonLocalStreamDoneMarked = false;
740 * Skip if buffer ops / reduction is offloaded to the GPU.
742 if (!stepWork.useGpuFBufferOps)
745 sizeof(adat->f[0]) == sizeof(Float3),
746 "The size of the force buffer element should be equal to the size of float3.");
747 copyFromDeviceBuffer(reinterpret_cast<Float3*>(nbatom->out[0].f.data()) + atomsRange.begin(),
752 GpuApiCallBehavior::Async,
756 /* After the non-local D2H is launched the nonlocal_done event can be
757 recorded which signals that the local D2H can proceed. This event is not
758 placed after the non-local kernel because we want the non-local data
760 if (iloc == InteractionLocality::NonLocal)
762 nb->nonlocal_done.markEvent(deviceStream);
763 nb->bNonLocalStreamDoneMarked = true;
766 /* only transfer energies in the local stream */
767 if (iloc == InteractionLocality::Local)
769 /* DtoH fshift when virial is needed */
770 if (stepWork.computeVirial)
772 static_assert(sizeof(nb->nbst.fShift[0]) == sizeof(adat->fShift[0]),
773 "Sizes of host- and device-side shift vectors should be the same.");
774 copyFromDeviceBuffer(
775 nb->nbst.fShift, &adat->fShift, 0, SHIFTS, deviceStream, GpuApiCallBehavior::Async, nullptr);
779 if (stepWork.computeEnergy)
781 static_assert(sizeof(nb->nbst.eLJ[0]) == sizeof(adat->eLJ[0]),
782 "Sizes of host- and device-side LJ energy terms should be the same.");
783 copyFromDeviceBuffer(
784 nb->nbst.eLJ, &adat->eLJ, 0, 1, deviceStream, GpuApiCallBehavior::Async, nullptr);
785 static_assert(sizeof(nb->nbst.eElec[0]) == sizeof(adat->eElec[0]),
786 "Sizes of host- and device-side electrostatic energy terms should be the "
788 copyFromDeviceBuffer(
789 nb->nbst.eElec, &adat->eElec, 0, 1, deviceStream, GpuApiCallBehavior::Async, nullptr);
795 timers->xf[atomLocality].nb_d2h.closeTimingRegion(deviceStream);
799 void cuda_set_cacheconfig()
803 for (int i = 0; i < c_numElecTypes; i++)
805 for (int j = 0; j < c_numVdwTypes; j++)
807 /* Default kernel 32/32 kB Shared/L1 */
808 cudaFuncSetCacheConfig(nb_kfunc_ener_prune_ptr[i][j], cudaFuncCachePreferEqual);
809 cudaFuncSetCacheConfig(nb_kfunc_ener_noprune_ptr[i][j], cudaFuncCachePreferEqual);
810 cudaFuncSetCacheConfig(nb_kfunc_noener_prune_ptr[i][j], cudaFuncCachePreferEqual);
811 stat = cudaFuncSetCacheConfig(nb_kfunc_noener_noprune_ptr[i][j], cudaFuncCachePreferEqual);
812 CU_RET_ERR(stat, "cudaFuncSetCacheConfig failed");
817 /* X buffer operations on GPU: performs conversion from rvec to nb format. */
818 void nbnxn_gpu_x_to_nbat_x(const Nbnxm::Grid& grid,
820 DeviceBuffer<gmx::RVec> d_x,
821 GpuEventSynchronizer* xReadyOnDevice,
822 const Nbnxm::AtomLocality locality,
826 GMX_ASSERT(nb, "Need a valid nbnxn_gpu object");
828 NBAtomData* adat = nb->atdat;
830 const int numColumns = grid.numColumns();
831 const int cellOffset = grid.cellOffset();
832 const int numAtomsPerCell = grid.numAtomsPerCell();
833 Nbnxm::InteractionLocality interactionLoc = gpuAtomToInteractionLocality(locality);
835 const DeviceStream& deviceStream = *nb->deviceStreams[interactionLoc];
837 int numAtoms = grid.srcAtomEnd() - grid.srcAtomBegin();
838 // avoid empty kernel launch, skip to inserting stream dependency
841 // TODO: This will only work with CUDA
842 GMX_ASSERT(d_x, "Need a valid device pointer");
844 // ensure that coordinates are ready on the device before launching the kernel
845 GMX_ASSERT(xReadyOnDevice, "Need a valid GpuEventSynchronizer object");
846 xReadyOnDevice->enqueueWaitEvent(deviceStream);
848 KernelLaunchConfig config;
849 config.blockSize[0] = c_bufOpsThreadsPerBlock;
850 config.blockSize[1] = 1;
851 config.blockSize[2] = 1;
852 config.gridSize[0] = (grid.numCellsColumnMax() * numAtomsPerCell + c_bufOpsThreadsPerBlock - 1)
853 / c_bufOpsThreadsPerBlock;
854 config.gridSize[1] = numColumns;
855 config.gridSize[2] = 1;
856 GMX_ASSERT(config.gridSize[0] > 0,
857 "Can not have empty grid, early return above avoids this");
858 config.sharedMemorySize = 0;
860 auto kernelFn = nbnxn_gpu_x_to_nbat_x_kernel;
861 float4* d_xq = adat->xq;
862 float3* d_xFloat3 = asFloat3(d_x);
863 const int* d_atomIndices = nb->atomIndices;
864 const int* d_cxy_na = &nb->cxy_na[numColumnsMax * gridId];
865 const int* d_cxy_ind = &nb->cxy_ind[numColumnsMax * gridId];
866 const auto kernelArgs = prepareGpuKernelArguments(kernelFn,
876 launchGpuKernel(kernelFn, config, deviceStream, nullptr, "XbufferOps", kernelArgs);
879 // TODO: note that this is not necessary when there are no local atoms, that is:
880 // (numAtoms == 0 && interactionLoc == InteractionLocality::Local)
881 // but for now we avoid that optimization
882 nbnxnInsertNonlocalGpuDependency(nb, interactionLoc);
885 void* getGpuForces(NbnxmGpu* nb)