libxsmm_dnn_optimizer.c 12.3 KB
Newer Older
lisj's avatar
lisj committed
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
/******************************************************************************
* Copyright (c) Intel Corporation - All rights reserved.                      *
* This file is part of the LIBXSMM library.                                   *
*                                                                             *
* For information on the license, see the LICENSE file.                       *
* Further information: https://github.com/hfp/libxsmm/                        *
* SPDX-License-Identifier: BSD-3-Clause                                       *
******************************************************************************/
/* Alexander Heinecke, Sasikanth Avancha (Intel Corp.)
******************************************************************************/
#include "libxsmm_dnn_optimizer_sgd.h"
#include "libxsmm_main.h"


LIBXSMM_API libxsmm_dnn_optimizer* libxsmm_dnn_create_optimizer(libxsmm_dnn_optimizer_desc optimizer_desc, libxsmm_dnn_err_t* status) {
  libxsmm_dnn_optimizer* handle = 0;

  /* init libxsmm */
  LIBXSMM_INIT

  if ( (optimizer_desc.datatype == LIBXSMM_DNN_DATATYPE_F32) || (optimizer_desc.datatype == LIBXSMM_DNN_DATATYPE_BF16) ) {
    /* zero entire content; not only safer but also sets data and code pointers to NULL */
    handle = (libxsmm_dnn_optimizer*)calloc(1, sizeof(libxsmm_dnn_optimizer));

    if (0 != handle) {
      *status = LIBXSMM_DNN_SUCCESS;
      /* let's make the description persistent */
      handle->desc = optimizer_desc;

      if ( (handle->desc.filter_format & LIBXSMM_DNN_TENSOR_FORMAT_LIBXSMM) > 0 ) {
        /* we need to compute the memory layout given the */
        *status = libxsmm_dnn_get_feature_map_blocks( handle->desc.C, handle->desc.K,
                                                      &(handle->bc), &(handle->bk), &(handle->fm_lp_block),
                                                      handle->desc.datatype, handle->desc.datatype );
        /* compute the outer blocks */
        handle->Bc = handle->desc.C / handle->bc;
        handle->Bk = handle->desc.K / handle->bk;
      } else if ( (handle->desc.filter_format & LIBXSMM_DNN_TENSOR_FORMAT_CKPACKED) > 0 ) {
        if ( optimizer_desc.datatype == LIBXSMM_DNN_DATATYPE_F32 ) {
          handle->fm_lp_block = 1;
        } else if ( optimizer_desc.datatype == LIBXSMM_DNN_DATATYPE_BF16 ) {
          handle->fm_lp_block = 2;
        } else {
        }
        handle->bc = handle->desc.bc;
        handle->bk = handle->desc.bk;
        handle->Bc = handle->desc.C / handle->bc;
        handle->Bk = handle->desc.K / handle->bk;
      } else {
        *status = LIBXSMM_DNN_ERR_CREATE_HANDLE;
        free( handle );
        handle = 0;
        return handle;
      }
      /* create barrier */
      handle->barrier = libxsmm_barrier_create(handle->desc.threads, 1);
      /* calculate scratch size for local optimizer copies of one feature map block per thread */
      handle->scratch_size = 1;
    } else {
      *status = LIBXSMM_DNN_ERR_CREATE_HANDLE;
    }
  } else {
    *status = LIBXSMM_DNN_ERR_UNSUPPORTED_DATATYPE;
  }

  return handle;
}


LIBXSMM_API libxsmm_dnn_err_t libxsmm_dnn_destroy_optimizer(const libxsmm_dnn_optimizer* handle) {
  libxsmm_dnn_err_t status = LIBXSMM_DNN_SUCCESS;

  if (0 != handle) {
    /* Deallocate barrier */
    if (handle->barrier != 0 ) { libxsmm_barrier_release((const libxsmm_barrier*)handle->barrier); }
    /* deallocate handle structure */
    free(/*remove constness*/(libxsmm_dnn_optimizer*)handle);
  } else {
    status = LIBXSMM_DNN_ERR_INVALID_HANDLE;
  }

  return status;
}


LIBXSMM_API libxsmm_dnn_tensor_datalayout* libxsmm_dnn_optimizer_create_tensor_datalayout(const libxsmm_dnn_optimizer* handle, const libxsmm_dnn_tensor_type type, libxsmm_dnn_err_t* status) {
  libxsmm_dnn_tensor_datalayout* layout;

  *status = LIBXSMM_DNN_SUCCESS;
  layout = 0;

  if (handle != 0) {
    /* zero entire content; not only safer but also sets data and code pointers to NULL */
    layout = (libxsmm_dnn_tensor_datalayout*)calloc(1, sizeof(libxsmm_dnn_tensor_datalayout));

    if (layout != 0) {
      layout->format = handle->desc.filter_format;

      if ( (type == LIBXSMM_DNN_REGULAR_FILTER) || (type == LIBXSMM_DNN_GRADIENT_FILTER) || (type == LIBXSMM_DNN_MASTER_FILTER) ) {
        if ( ((handle->desc.filter_format & LIBXSMM_DNN_TENSOR_FORMAT_LIBXSMM) > 0) || ((handle->desc.filter_format & LIBXSMM_DNN_TENSOR_FORMAT_CKPACKED) > 0) ) {
          if ( handle->desc.datatype == LIBXSMM_DNN_DATATYPE_F32 ) {
            layout->datatype = handle->desc.datatype;
            layout->dim_type = (libxsmm_dnn_tensor_dimtype*) malloc(4*sizeof(libxsmm_dnn_tensor_dimtype));
            layout->dim_size = (unsigned int*) malloc(4*sizeof(unsigned int));

            if (0 != layout->dim_type && 0 != layout->dim_size) {
              layout->num_dims = 4;
              layout->dim_type[0] = LIBXSMM_DNN_TENSOR_DIMTYPE_K;
              layout->dim_type[1] = LIBXSMM_DNN_TENSOR_DIMTYPE_C;
              layout->dim_type[2] = LIBXSMM_DNN_TENSOR_DIMTYPE_C;
              layout->dim_type[3] = LIBXSMM_DNN_TENSOR_DIMTYPE_K;
              layout->dim_size[0] = handle->bk;
              layout->dim_size[1] = handle->bc;
              layout->dim_size[2] = handle->Bc;
              layout->dim_size[3] = handle->Bk;
            } else {
              free(layout);
              layout = 0; /* make sure a NULL is returned */
              *status = LIBXSMM_DNN_ERR_CREATE_LAYOUT_ARRAYS;
            }
          } else if ( handle->desc.datatype == LIBXSMM_DNN_DATATYPE_BF16 ) {
            layout->datatype = handle->desc.datatype;
            layout->dim_type = (libxsmm_dnn_tensor_dimtype*) malloc(5*sizeof(libxsmm_dnn_tensor_dimtype));
            layout->dim_size = (unsigned int*) malloc(5*sizeof(unsigned int));

            if (0 != layout->dim_type && 0 != layout->dim_size) {
              layout->num_dims = 5;
              layout->dim_type[0] = LIBXSMM_DNN_TENSOR_DIMTYPE_C;
              layout->dim_type[1] = LIBXSMM_DNN_TENSOR_DIMTYPE_K;
              layout->dim_type[2] = LIBXSMM_DNN_TENSOR_DIMTYPE_C;
              layout->dim_type[3] = LIBXSMM_DNN_TENSOR_DIMTYPE_C;
              layout->dim_type[4] = LIBXSMM_DNN_TENSOR_DIMTYPE_K;
              layout->dim_size[0] = handle->fm_lp_block;
              layout->dim_size[1] = handle->bk;
              layout->dim_size[2] = handle->bc/handle->fm_lp_block;
              layout->dim_size[3] = handle->Bc;
              layout->dim_size[4] = handle->Bk;
            } else {
              free(layout);
              layout = 0; /* make sure a NULL is returned */
              *status = LIBXSMM_DNN_ERR_CREATE_LAYOUT_ARRAYS;
            }
          } else {
            free(layout);
            layout = 0; /* make sure a NULL is returned */
            *status = LIBXSMM_DNN_ERR_UNSUPPORTED_DATATYPE;
          }
        } else {
          free(layout);
          layout = 0; /* make sure a NULL is returned */
          *status = LIBXSMM_DNN_ERR_INVALID_FORMAT_GENERAL;
        }
      } else {
        free(layout);
        layout = 0; /* make sure a NULL is returned */
        *status = LIBXSMM_DNN_ERR_UNKNOWN_TENSOR_TYPE;
      }
    } else {
      *status = LIBXSMM_DNN_ERR_CREATE_LAYOUT;
    }
  }
  else {
    *status = LIBXSMM_DNN_ERR_INVALID_HANDLE;
  }

  return layout;
}


LIBXSMM_API size_t libxsmm_dnn_optimizer_get_scratch_size(const libxsmm_dnn_optimizer* handle, libxsmm_dnn_err_t* status) {
  size_t l_scratch_size = 0;
  *status = LIBXSMM_DNN_SUCCESS;

  if (0 != handle) {
    l_scratch_size = handle->scratch_size + 64; /* 64 byte extra in case the user code does not care about alignment */
  } else {
    *status = LIBXSMM_DNN_ERR_INVALID_HANDLE;
  }

  return l_scratch_size;
}


LIBXSMM_API void* libxsmm_dnn_optimizer_get_scratch_ptr(const libxsmm_dnn_optimizer* handle, libxsmm_dnn_err_t* status)
{
  *status = LIBXSMM_DNN_SUCCESS;

  if (0 != handle) {
    return handle->scratch;
  } else {
    *status = LIBXSMM_DNN_ERR_INVALID_HANDLE;
  }

  return 0;
}


LIBXSMM_API libxsmm_dnn_err_t libxsmm_dnn_optimizer_bind_scratch(libxsmm_dnn_optimizer* handle, const void* scratch) {
  libxsmm_dnn_err_t status = LIBXSMM_DNN_SUCCESS;
  uintptr_t address = (uintptr_t)scratch;
  size_t offset = 0;

  if (scratch == 0) {
    status = LIBXSMM_DNN_ERR_SCRATCH_NOT_ALLOCED;
    return status;
  }

  if (0 != handle) {
    /* align the internal scratch buffer if needed */
    if (address % 64 == 0) {
      handle->scratch = (void*)address;
    } else {
      offset = (64 - address % 64);
      handle->scratch = (void*)(address+offset);
    }
  } else {
    status = LIBXSMM_DNN_ERR_INVALID_HANDLE;
  }

  return status;
}


LIBXSMM_API libxsmm_dnn_err_t libxsmm_dnn_optimizer_release_scratch(libxsmm_dnn_optimizer* handle) {
  libxsmm_dnn_err_t status = LIBXSMM_DNN_SUCCESS;

  if (0 != handle) {
    handle->scratch = 0;
  } else {
    status = LIBXSMM_DNN_ERR_INVALID_HANDLE;
  }

  return status;
}


LIBXSMM_API libxsmm_dnn_err_t libxsmm_dnn_optimizer_bind_tensor(libxsmm_dnn_optimizer* handle, const libxsmm_dnn_tensor* tensor, const libxsmm_dnn_tensor_type type) {
  libxsmm_dnn_err_t status = LIBXSMM_DNN_SUCCESS;

  /* check for tensor type */
  if ( (type != LIBXSMM_DNN_REGULAR_FILTER) && (type != LIBXSMM_DNN_GRADIENT_FILTER) && (type != LIBXSMM_DNN_MASTER_FILTER) ) {
    status = LIBXSMM_DNN_ERR_UNKNOWN_TENSOR_TYPE;
    return status;
  }

  if (handle != 0 && tensor != 0) {
    libxsmm_dnn_tensor_datalayout* handle_layout = libxsmm_dnn_optimizer_create_tensor_datalayout(handle, type, &status);

    if ( libxsmm_dnn_compare_tensor_datalayout(handle_layout, tensor->layout, &status) == 0 ) {
      if ( type == LIBXSMM_DNN_REGULAR_FILTER ) {
        handle->reg_filter = (libxsmm_dnn_tensor*)tensor;
      } else if ( type == LIBXSMM_DNN_GRADIENT_FILTER ) {
        handle->grad_filter = (libxsmm_dnn_tensor*)tensor;
      } else if ( type == LIBXSMM_DNN_MASTER_FILTER ) {
        handle->master_filter = (libxsmm_dnn_tensor*)tensor;
      } else {
        /* cannot happen */
      }
    } else {
      status = LIBXSMM_DNN_ERR_MISMATCH_TENSOR;
    }

    libxsmm_dnn_destroy_tensor_datalayout( handle_layout );
  }
  else {
    status = LIBXSMM_DNN_ERR_INVALID_HANDLE_TENSOR;
  }

  return status;
}


LIBXSMM_API libxsmm_dnn_tensor* libxsmm_dnn_optimizer_get_tensor(libxsmm_dnn_optimizer* handle, const libxsmm_dnn_tensor_type type, libxsmm_dnn_err_t* status) {
  libxsmm_dnn_tensor* return_tensor = 0;

  *status = LIBXSMM_DNN_SUCCESS;

  /* check for tensor type */
  if ( (type != LIBXSMM_DNN_REGULAR_FILTER) && (type != LIBXSMM_DNN_GRADIENT_FILTER) && (type != LIBXSMM_DNN_MASTER_FILTER) ) {
    *status = LIBXSMM_DNN_ERR_UNKNOWN_TENSOR_TYPE;
    return return_tensor;
  }

  if (handle != 0) {
    if ( type == LIBXSMM_DNN_REGULAR_FILTER ) {
      return_tensor = handle->reg_filter;
    } else if ( type == LIBXSMM_DNN_GRADIENT_FILTER ) {
      return_tensor = handle->grad_filter;
    } else if ( type == LIBXSMM_DNN_MASTER_FILTER ) {
      return_tensor = handle->master_filter;
    } else {
      /* cannot happen */
    }
  } else {
    *status = LIBXSMM_DNN_ERR_INVALID_HANDLE;
  }

  return return_tensor;
}


LIBXSMM_API libxsmm_dnn_err_t libxsmm_dnn_optimizer_release_tensor(libxsmm_dnn_optimizer* handle, const libxsmm_dnn_tensor_type type) {
  libxsmm_dnn_err_t status = LIBXSMM_DNN_SUCCESS;

  /* check for tensor type */
  if ( (type != LIBXSMM_DNN_REGULAR_FILTER) && (type != LIBXSMM_DNN_GRADIENT_FILTER) && (type != LIBXSMM_DNN_MASTER_FILTER) ) {
    status = LIBXSMM_DNN_ERR_UNKNOWN_TENSOR_TYPE;
    return status;
  }

  if (handle != 0) {
    if ( type == LIBXSMM_DNN_REGULAR_FILTER ) {
      handle->reg_filter = 0;
    } else if ( type == LIBXSMM_DNN_GRADIENT_FILTER ) {
      handle->grad_filter = 0;
    } else if ( type == LIBXSMM_DNN_MASTER_FILTER ) {
      handle->master_filter = 0;
    } else {
      /* cannot happen */
    }
  } else {
    status = LIBXSMM_DNN_ERR_INVALID_HANDLE;
  }

  return status;
}


LIBXSMM_API libxsmm_dnn_err_t libxsmm_dnn_optimizer_execute_st(libxsmm_dnn_optimizer* handle, /*unsigned*/int start_thread, /*unsigned*/int tid) {
  libxsmm_dnn_err_t status = LIBXSMM_DNN_SUCCESS;

  if (0 != handle) {
    if (handle->desc.opt_type == LIBXSMM_DNN_OPTIMIZER_SGD) {
      libxsmm_dnn_optimizer_sgd_st( handle, start_thread, tid );
    } else {
      status = LIBXSMM_DNN_ERR_INVALID_HANDLE;
    }
  }
  else {
    status = LIBXSMM_DNN_ERR_INVALID_HANDLE;
  }

  return status;
}