xref: /libCEED/backends/hip-shared/ceed-hip-shared-basis.c (revision 34d146140c2fce42d8bc042f039d47d4ff020864)
1 // Copyright (c) 2017-2024, Lawrence Livermore National Security, LLC and other CEED contributors.
2 // All Rights Reserved. See the top-level LICENSE and NOTICE files for details.
3 //
4 // SPDX-License-Identifier: BSD-2-Clause
5 //
6 // This file is part of CEED:  http://github.com/ceed
7 
8 #include <ceed.h>
9 #include <ceed/backend.h>
10 #include <ceed/jit-tools.h>
11 #include <stdbool.h>
12 #include <stddef.h>
13 #include <hip/hip_runtime.h>
14 
15 #include "../hip/ceed-hip-common.h"
16 #include "../hip/ceed-hip-compile.h"
17 #include "ceed-hip-shared.h"
18 
19 //------------------------------------------------------------------------------
20 // Compute a block size based on required minimum threads
21 //------------------------------------------------------------------------------
22 static CeedInt ComputeBlockSizeFromRequirement(const CeedInt required) {
23   CeedInt maxSize     = 1024;  // Max total threads per block
24   CeedInt currentSize = 64;    // Start with one group
25 
26   while (currentSize < maxSize) {
27     if (currentSize > required) break;
28     else currentSize = currentSize * 2;
29   }
30   return currentSize;
31 }
32 
33 //------------------------------------------------------------------------------
34 // Compute required thread block sizes for basis kernels given P, Q, dim, and
35 // num_comp (num_comp not currently used, but may be again in other basis
36 // parallelization options)
37 //------------------------------------------------------------------------------
38 static int ComputeBasisThreadBlockSizes(const CeedInt dim, const CeedInt P_1d, const CeedInt Q_1d, const CeedInt num_comp, CeedInt *block_sizes) {
39   // Note that this will use the same block sizes for all dimensions when compiling,
40   // but as each basis object is defined for a particular dimension, we will never
41   // call any kernels except the ones for the dimension for which we have computed the
42   // block sizes.
43   const CeedInt thread_1d = CeedIntMax(P_1d, Q_1d);
44 
45   switch (dim) {
46     case 1: {
47       // Interp kernels:
48       block_sizes[0] = 256;
49 
50       // Grad kernels:
51       block_sizes[1] = 256;
52 
53       // Weight kernels:
54       block_sizes[2] = 256;
55     } break;
56     case 2: {
57       // Interp kernels:
58       CeedInt required = thread_1d * thread_1d;
59 
60       block_sizes[0] = CeedIntMax(256, ComputeBlockSizeFromRequirement(required));
61 
62       // Grad kernels: currently use same required minimum threads
63       block_sizes[1] = CeedIntMax(256, ComputeBlockSizeFromRequirement(required));
64 
65       // Weight kernels:
66       required       = CeedIntMax(64, Q_1d * Q_1d);
67       block_sizes[2] = CeedIntMax(256, ComputeBlockSizeFromRequirement(required));
68 
69     } break;
70     case 3: {
71       // Interp kernels:
72       CeedInt required = thread_1d * thread_1d;
73 
74       block_sizes[0] = CeedIntMax(256, ComputeBlockSizeFromRequirement(required));
75 
76       // Grad kernels: currently use same required minimum threads
77       block_sizes[1] = CeedIntMax(256, ComputeBlockSizeFromRequirement(required));
78 
79       // Weight kernels:
80       required       = Q_1d * Q_1d * Q_1d;
81       block_sizes[2] = CeedIntMax(256, ComputeBlockSizeFromRequirement(required));
82     }
83   }
84   return CEED_ERROR_SUCCESS;
85 }
86 
87 //------------------------------------------------------------------------------
88 // Apply basis
89 //------------------------------------------------------------------------------
90 int CeedBasisApplyTensor_Hip_shared(CeedBasis basis, const CeedInt num_elem, CeedTransposeMode t_mode, CeedEvalMode eval_mode, CeedVector u,
91                                     CeedVector v) {
92   Ceed                  ceed;
93   Ceed_Hip             *ceed_Hip;
94   CeedInt               dim, num_comp;
95   const CeedScalar     *d_u;
96   CeedScalar           *d_v;
97   CeedBasis_Hip_shared *data;
98 
99   CeedCallBackend(CeedBasisGetCeed(basis, &ceed));
100   CeedCallBackend(CeedGetData(ceed, &ceed_Hip));
101   CeedCallBackend(CeedBasisGetData(basis, &data));
102   CeedCallBackend(CeedBasisGetDimension(basis, &dim));
103   CeedCallBackend(CeedBasisGetNumComponents(basis, &num_comp));
104 
105   // Get read/write access to u, v
106   if (u != CEED_VECTOR_NONE) CeedCallBackend(CeedVectorGetArrayRead(u, CEED_MEM_DEVICE, &d_u));
107   else CeedCheck(eval_mode == CEED_EVAL_WEIGHT, ceed, CEED_ERROR_BACKEND, "An input vector is required for this CeedEvalMode");
108   CeedCallBackend(CeedVectorGetArrayWrite(v, CEED_MEM_DEVICE, &d_v));
109 
110   // Apply basis operation
111   switch (eval_mode) {
112     case CEED_EVAL_INTERP: {
113       CeedInt P_1d, Q_1d;
114       CeedInt block_size = data->block_sizes[0];
115 
116       CeedCallBackend(CeedBasisGetNumNodes1D(basis, &P_1d));
117       CeedCallBackend(CeedBasisGetNumQuadraturePoints1D(basis, &Q_1d));
118       CeedInt thread_1d     = CeedIntMax(Q_1d, P_1d);
119       void   *interp_args[] = {(void *)&num_elem, &data->d_interp_1d, &d_u, &d_v};
120 
121       if (dim == 1) {
122         CeedInt elems_per_block = 64 * thread_1d > 256 ? 256 / thread_1d : 64;
123         elems_per_block         = elems_per_block > 0 ? elems_per_block : 1;
124         CeedInt grid            = num_elem / elems_per_block + ((num_elem / elems_per_block * elems_per_block < num_elem) ? 1 : 0);
125         CeedInt shared_mem      = elems_per_block * thread_1d * sizeof(CeedScalar);
126 
127         if (t_mode == CEED_TRANSPOSE) {
128           CeedCallBackend(CeedRunKernelDimShared_Hip(ceed, data->InterpTranspose, grid, thread_1d, 1, elems_per_block, shared_mem, interp_args));
129         } else {
130           CeedCallBackend(CeedRunKernelDimShared_Hip(ceed, data->Interp, grid, thread_1d, 1, elems_per_block, shared_mem, interp_args));
131         }
132       } else if (dim == 2) {
133         // Check if required threads is small enough to do multiple elems
134         const CeedInt elems_per_block = CeedIntMax(block_size / (thread_1d * thread_1d), 1);
135         CeedInt       grid            = num_elem / elems_per_block + ((num_elem / elems_per_block * elems_per_block < num_elem) ? 1 : 0);
136         CeedInt       shared_mem      = elems_per_block * thread_1d * thread_1d * sizeof(CeedScalar);
137 
138         if (t_mode == CEED_TRANSPOSE) {
139           CeedCallBackend(
140               CeedRunKernelDimShared_Hip(ceed, data->InterpTranspose, grid, thread_1d, thread_1d, elems_per_block, shared_mem, interp_args));
141         } else {
142           CeedCallBackend(CeedRunKernelDimShared_Hip(ceed, data->Interp, grid, thread_1d, thread_1d, elems_per_block, shared_mem, interp_args));
143         }
144       } else if (dim == 3) {
145         const CeedInt elems_per_block = CeedIntMax(block_size / (thread_1d * thread_1d), 1);
146         CeedInt       grid            = num_elem / elems_per_block + ((num_elem / elems_per_block * elems_per_block < num_elem) ? 1 : 0);
147         CeedInt       shared_mem      = elems_per_block * thread_1d * thread_1d * sizeof(CeedScalar);
148 
149         if (t_mode == CEED_TRANSPOSE) {
150           CeedCallBackend(
151               CeedRunKernelDimShared_Hip(ceed, data->InterpTranspose, grid, thread_1d, thread_1d, elems_per_block, shared_mem, interp_args));
152         } else {
153           CeedCallBackend(CeedRunKernelDimShared_Hip(ceed, data->Interp, grid, thread_1d, thread_1d, elems_per_block, shared_mem, interp_args));
154         }
155       }
156     } break;
157     case CEED_EVAL_GRAD: {
158       CeedInt P_1d, Q_1d;
159       CeedInt block_size = data->block_sizes[1];
160 
161       CeedCallBackend(CeedBasisGetNumNodes1D(basis, &P_1d));
162       CeedCallBackend(CeedBasisGetNumQuadraturePoints1D(basis, &Q_1d));
163       CeedInt     thread_1d = CeedIntMax(Q_1d, P_1d);
164       CeedScalar *d_grad_1d = data->d_grad_1d;
165 
166       if (data->d_collo_grad_1d) {
167         d_grad_1d = data->d_collo_grad_1d;
168       }
169       void *grad_args[] = {(void *)&num_elem, &data->d_interp_1d, &d_grad_1d, &d_u, &d_v};
170       if (dim == 1) {
171         CeedInt elems_per_block = 64 * thread_1d > 256 ? 256 / thread_1d : 64;
172         elems_per_block         = elems_per_block > 0 ? elems_per_block : 1;
173         CeedInt grid            = num_elem / elems_per_block + ((num_elem / elems_per_block * elems_per_block < num_elem) ? 1 : 0);
174         CeedInt shared_mem      = elems_per_block * thread_1d * sizeof(CeedScalar);
175 
176         if (t_mode == CEED_TRANSPOSE) {
177           CeedCallBackend(CeedRunKernelDimShared_Hip(ceed, data->GradTranspose, grid, thread_1d, 1, elems_per_block, shared_mem, grad_args));
178         } else {
179           CeedCallBackend(CeedRunKernelDimShared_Hip(ceed, data->Grad, grid, thread_1d, 1, elems_per_block, shared_mem, grad_args));
180         }
181       } else if (dim == 2) {
182         // Check if required threads is small enough to do multiple elems
183         const CeedInt elems_per_block = CeedIntMax(block_size / (thread_1d * thread_1d), 1);
184         CeedInt       grid            = num_elem / elems_per_block + ((num_elem / elems_per_block * elems_per_block < num_elem) ? 1 : 0);
185         CeedInt       shared_mem      = elems_per_block * thread_1d * thread_1d * sizeof(CeedScalar);
186 
187         if (t_mode == CEED_TRANSPOSE) {
188           CeedCallBackend(CeedRunKernelDimShared_Hip(ceed, data->GradTranspose, grid, thread_1d, thread_1d, elems_per_block, shared_mem, grad_args));
189         } else {
190           CeedCallBackend(CeedRunKernelDimShared_Hip(ceed, data->Grad, grid, thread_1d, thread_1d, elems_per_block, shared_mem, grad_args));
191         }
192       } else if (dim == 3) {
193         const CeedInt elems_per_block = CeedIntMax(block_size / (thread_1d * thread_1d), 1);
194         CeedInt       grid            = num_elem / elems_per_block + ((num_elem / elems_per_block * elems_per_block < num_elem) ? 1 : 0);
195         CeedInt       shared_mem      = elems_per_block * thread_1d * thread_1d * sizeof(CeedScalar);
196 
197         if (t_mode == CEED_TRANSPOSE) {
198           CeedCallBackend(CeedRunKernelDimShared_Hip(ceed, data->GradTranspose, grid, thread_1d, thread_1d, elems_per_block, shared_mem, grad_args));
199         } else {
200           CeedCallBackend(CeedRunKernelDimShared_Hip(ceed, data->Grad, grid, thread_1d, thread_1d, elems_per_block, shared_mem, grad_args));
201         }
202       }
203     } break;
204     case CEED_EVAL_WEIGHT: {
205       CeedInt Q_1d;
206       CeedInt block_size = data->block_sizes[2];
207 
208       CeedCheck(data->d_q_weight_1d, ceed, CEED_ERROR_BACKEND, "%s not supported; q_weights_1d not set", CeedEvalModes[eval_mode]);
209       CeedCallBackend(CeedBasisGetNumQuadraturePoints1D(basis, &Q_1d));
210       void *weight_args[] = {(void *)&num_elem, (void *)&data->d_q_weight_1d, &d_v};
211 
212       if (dim == 1) {
213         const CeedInt opt_elems       = block_size / Q_1d;
214         const CeedInt elems_per_block = opt_elems > 0 ? opt_elems : 1;
215         const CeedInt grid_size       = num_elem / elems_per_block + ((num_elem / elems_per_block * elems_per_block < num_elem) ? 1 : 0);
216 
217         CeedCallBackend(CeedRunKernelDim_Hip(ceed, data->Weight, grid_size, Q_1d, elems_per_block, 1, weight_args));
218       } else if (dim == 2) {
219         const CeedInt opt_elems       = block_size / (Q_1d * Q_1d);
220         const CeedInt elems_per_block = opt_elems > 0 ? opt_elems : 1;
221         const CeedInt grid_size       = num_elem / elems_per_block + ((num_elem / elems_per_block * elems_per_block < num_elem) ? 1 : 0);
222 
223         CeedCallBackend(CeedRunKernelDim_Hip(ceed, data->Weight, grid_size, Q_1d, Q_1d, elems_per_block, weight_args));
224       } else if (dim == 3) {
225         const CeedInt opt_elems       = block_size / (Q_1d * Q_1d);
226         const CeedInt elems_per_block = opt_elems > 0 ? opt_elems : 1;
227         const CeedInt grid_size       = num_elem / elems_per_block + ((num_elem / elems_per_block * elems_per_block < num_elem) ? 1 : 0);
228 
229         CeedCallBackend(CeedRunKernelDim_Hip(ceed, data->Weight, grid_size, Q_1d, Q_1d, elems_per_block, weight_args));
230       }
231     } break;
232     case CEED_EVAL_NONE: /* handled separately below */
233       break;
234     // LCOV_EXCL_START
235     case CEED_EVAL_DIV:
236     case CEED_EVAL_CURL:
237       return CeedError(ceed, CEED_ERROR_BACKEND, "%s not supported", CeedEvalModes[eval_mode]);
238       // LCOV_EXCL_STOP
239   }
240 
241   // Restore vectors, cover CEED_EVAL_NONE
242   CeedCallBackend(CeedVectorRestoreArray(v, &d_v));
243   if (eval_mode == CEED_EVAL_NONE) CeedCallBackend(CeedVectorSetArray(v, CEED_MEM_DEVICE, CEED_COPY_VALUES, (CeedScalar *)d_u));
244   if (eval_mode != CEED_EVAL_WEIGHT) CeedCallBackend(CeedVectorRestoreArrayRead(u, &d_u));
245   return CEED_ERROR_SUCCESS;
246 }
247 
248 //------------------------------------------------------------------------------
249 // Destroy basis
250 //------------------------------------------------------------------------------
251 static int CeedBasisDestroy_Hip_shared(CeedBasis basis) {
252   Ceed                  ceed;
253   CeedBasis_Hip_shared *data;
254 
255   CeedCallBackend(CeedBasisGetCeed(basis, &ceed));
256   CeedCallBackend(CeedBasisGetData(basis, &data));
257   CeedCallHip(ceed, hipModuleUnload(data->module));
258   if (data->d_q_weight_1d) CeedCallHip(ceed, hipFree(data->d_q_weight_1d));
259   CeedCallHip(ceed, hipFree(data->d_interp_1d));
260   CeedCallHip(ceed, hipFree(data->d_grad_1d));
261   CeedCallHip(ceed, hipFree(data->d_collo_grad_1d));
262   CeedCallBackend(CeedFree(&data));
263   return CEED_ERROR_SUCCESS;
264 }
265 
266 //------------------------------------------------------------------------------
267 // Create tensor basis
268 //------------------------------------------------------------------------------
269 int CeedBasisCreateTensorH1_Hip_shared(CeedInt dim, CeedInt P_1d, CeedInt Q_1d, const CeedScalar *interp_1d, const CeedScalar *grad_1d,
270                                        const CeedScalar *q_ref_1d, const CeedScalar *q_weight_1d, CeedBasis basis) {
271   Ceed                  ceed;
272   char                 *basis_kernel_source;
273   const char           *basis_kernel_path;
274   CeedInt               num_comp;
275   const CeedInt         q_bytes      = Q_1d * sizeof(CeedScalar);
276   const CeedInt         interp_bytes = q_bytes * P_1d;
277   CeedBasis_Hip_shared *data;
278 
279   CeedCallBackend(CeedBasisGetCeed(basis, &ceed));
280   CeedCallBackend(CeedCalloc(1, &data));
281 
282   // Copy basis data to GPU
283   if (q_weight_1d) {
284     CeedCallHip(ceed, hipMalloc((void **)&data->d_q_weight_1d, q_bytes));
285     CeedCallHip(ceed, hipMemcpy(data->d_q_weight_1d, q_weight_1d, q_bytes, hipMemcpyHostToDevice));
286   }
287   CeedCallHip(ceed, hipMalloc((void **)&data->d_interp_1d, interp_bytes));
288   CeedCallHip(ceed, hipMemcpy(data->d_interp_1d, interp_1d, interp_bytes, hipMemcpyHostToDevice));
289   CeedCallHip(ceed, hipMalloc((void **)&data->d_grad_1d, interp_bytes));
290   CeedCallHip(ceed, hipMemcpy(data->d_grad_1d, grad_1d, interp_bytes, hipMemcpyHostToDevice));
291 
292   // Compute collocated gradient and copy to GPU
293   data->d_collo_grad_1d    = NULL;
294   bool has_collocated_grad = dim == 3 && Q_1d >= P_1d;
295 
296   if (has_collocated_grad) {
297     CeedScalar *collo_grad_1d;
298 
299     CeedCallBackend(CeedMalloc(Q_1d * Q_1d, &collo_grad_1d));
300     CeedCallBackend(CeedBasisGetCollocatedGrad(basis, collo_grad_1d));
301     CeedCallHip(ceed, hipMalloc((void **)&data->d_collo_grad_1d, q_bytes * Q_1d));
302     CeedCallHip(ceed, hipMemcpy(data->d_collo_grad_1d, collo_grad_1d, q_bytes * Q_1d, hipMemcpyHostToDevice));
303     CeedCallBackend(CeedFree(&collo_grad_1d));
304   }
305 
306   // Set number of threads per block for basis kernels
307   CeedCallBackend(CeedBasisGetNumComponents(basis, &num_comp));
308   CeedCallBackend(ComputeBasisThreadBlockSizes(dim, P_1d, Q_1d, num_comp, data->block_sizes));
309 
310   // Compile basis kernels
311   CeedCallBackend(CeedGetJitAbsolutePath(ceed, "ceed/jit-source/hip/hip-shared-basis-tensor.h", &basis_kernel_path));
312   CeedDebug256(ceed, CEED_DEBUG_COLOR_SUCCESS, "----- Loading Basis Kernel Source -----\n");
313   CeedCallBackend(CeedLoadSourceToBuffer(ceed, basis_kernel_path, &basis_kernel_source));
314   CeedDebug256(ceed, CEED_DEBUG_COLOR_SUCCESS, "----- Loading Basis Kernel Source Complete! -----\n");
315   CeedCallBackend(CeedCompile_Hip(ceed, basis_kernel_source, &data->module, 11, "BASIS_Q_1D", Q_1d, "BASIS_P_1D", P_1d, "T_1D",
316                                   CeedIntMax(Q_1d, P_1d), "BASIS_DIM", dim, "BASIS_NUM_COMP", num_comp, "BASIS_NUM_NODES", CeedIntPow(P_1d, dim),
317                                   "BASIS_NUM_QPTS", CeedIntPow(Q_1d, dim), "BASIS_INTERP_BLOCK_SIZE", data->block_sizes[0], "BASIS_GRAD_BLOCK_SIZE",
318                                   data->block_sizes[1], "BASIS_WEIGHT_BLOCK_SIZE", data->block_sizes[2], "BASIS_HAS_COLLOCATED_GRAD",
319                                   has_collocated_grad));
320   CeedCallBackend(CeedGetKernel_Hip(ceed, data->module, "Interp", &data->Interp));
321   CeedCallBackend(CeedGetKernel_Hip(ceed, data->module, "InterpTranspose", &data->InterpTranspose));
322   CeedCallBackend(CeedGetKernel_Hip(ceed, data->module, "Grad", &data->Grad));
323   CeedCallBackend(CeedGetKernel_Hip(ceed, data->module, "GradTranspose", &data->GradTranspose));
324   CeedCallBackend(CeedGetKernel_Hip(ceed, data->module, "Weight", &data->Weight));
325   CeedCallBackend(CeedFree(&basis_kernel_path));
326   CeedCallBackend(CeedFree(&basis_kernel_source));
327 
328   CeedCallBackend(CeedBasisSetData(basis, data));
329 
330   // Register backend functions
331   CeedCallBackend(CeedSetBackendFunction(ceed, "Basis", basis, "Apply", CeedBasisApplyTensor_Hip_shared));
332   CeedCallBackend(CeedSetBackendFunction(ceed, "Basis", basis, "Destroy", CeedBasisDestroy_Hip_shared));
333   return CEED_ERROR_SUCCESS;
334 }
335 
336 //------------------------------------------------------------------------------
337