-
Notifications
You must be signed in to change notification settings - Fork 50
/
extension_interface.h
467 lines (439 loc) · 20.6 KB
/
extension_interface.h
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
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
/***************************************************************************
*
* @license
* Copyright (C) Codeplay Software Limited
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* For your convenience, a copy of the License has been included in this
* repository.
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* portBLAS: BLAS implementation using SYCL
*
* @filename reduction_interface.h
*
**************************************************************************/
#ifndef PORTBLAS_EXTENSION_INTERFACE_H
#define PORTBLAS_EXTENSION_INTERFACE_H
#include "operations/extension/reduction.h"
#include "operations/extension/transpose.h"
#include "sb_handle/portblas_handle.h"
namespace blas {
namespace internal {
/**
* \brief COPY Matrix in to out with scaling factor of alpha
*
* Copy Matrix to out_memory, it can be out of place if out_memory is different
* from in_memory. The increment within the same column can be different from 1
* and specified by inc and inc_out argument.
*
*
* @tparam sb_handle_t SB_Handle type
* @tparam element_t Scaling factor type
* @tparam index_t Index type
* @tparam in_t Buffer Iterator or USM Pointer
* @tparam out_t Buffer Iterator or USM Pointer
* @param sb_handle SB_Handle
* @param trans compute matrix transpose or not.
* @param m rows of matrix
* @param n cols of matrix
* @param alpha Scaling factor
* @param in_memory BufferIterator or USM Pointer of input
* @param ld_in leading dimension of in_matrix
* @param inc_in internal increment for the in_matrix
* @param matrix_out BufferIterator or USM Pointer of output
* @param ld_out leading dimention of out_matrix
* @param inc_out internal increment for the out_matrix
*/
template <bool in_place, typename sb_handle_t, typename element_t,
typename index_t, typename in_t, typename out_t>
typename sb_handle_t::event_t _matcopy(
sb_handle_t& sb_handle, char trans, index_t m, index_t n, element_t alpha,
in_t in_memory, index_t ld_in, index_t inc_in, out_t out_memory,
index_t ld_out, index_t inc_out,
const typename sb_handle_t::event_t& _dependencies);
template <typename sb_handle_t, typename element_t, typename index_t,
typename container_0_t, typename container_1_t,
typename container_2_t>
typename sb_handle_t::event_t _omatadd(
sb_handle_t& sb_handle, char trans_a, char trans_b, index_t m, index_t n,
element_t alpha, container_0_t a, index_t lda, element_t beta,
container_1_t b, index_t ldb, container_2_t c, index_t ldc,
const typename sb_handle_t::event_t& _dependencies);
template <bool in_place, typename element_t, typename sb_handle_t,
typename index_t, typename in_t, typename out_t>
typename sb_handle_t::event_t _transpose(
sb_handle_t& sb_handle, index_t m, index_t n, in_t A, index_t ld_a, out_t B,
index_t ld_b, const typename sb_handle_t::event_t& _dependencies);
template <bool in_place, typename sb_handle_t, typename element_t,
typename index_t, typename in_t, typename out_t>
typename sb_handle_t::event_t _matcopy_batch(
sb_handle_t& sb_handle, char trans, index_t m, index_t n, element_t alpha,
in_t in_memory, index_t ld_in, index_t stride_in, out_t out_memory,
index_t ld_out, index_t stride_out, index_t batch_size,
const typename sb_handle_t::event_t& _dependencies);
template <uint32_t TileSize, int TilePerWG, typename sb_handle_t,
typename element_t, typename index_t, typename in_t, typename out_t>
typename sb_handle_t::event_t _matcopy_batch_impl(
sb_handle_t& sb_handle, index_t m, index_t n, element_t alpha, in_t memory,
index_t ld_in, index_t in_stride, out_t out_memory, index_t ld_out,
index_t out_stride, index_t batch_size,
const typename sb_handle_t::event_t& _dependencies);
template <typename sb_handle_t, typename element_t, typename index_t,
typename container_0_t, typename container_1_t,
typename container_2_t>
typename sb_handle_t::event_t _omatadd_batch(
sb_handle_t& sb_handle, char trans_a, char trans_b, index_t m, index_t n,
element_t alpha, container_0_t a, index_t lda, index_t stride_a,
element_t beta, container_1_t b, index_t ldb, index_t stride_b,
container_2_t c, index_t ldc, index_t stride_c, index_t batch_size,
const typename sb_handle_t::event_t& _dependencies);
template <uint32_t TileSize, int TilePerWG, typename sb_handle_t,
typename element_t, typename index_t, typename container_0_t,
typename container_1_t, typename container_2_t>
typename sb_handle_t::event_t _omatadd_batch_impl(
sb_handle_t& sb_handle, index_t m, index_t n, element_t alpha,
container_0_t A, index_t lda, index_t stride_a, element_t beta,
container_1_t B, index_t ldb, index_t stride_b, container_2_t C,
index_t ldc, index_t stride_c, index_t batch_size,
const typename sb_handle_t::event_t& _dependencies);
template <typename operator_t, typename element_t, typename sb_handle_t,
typename input_t, typename output_t, typename index_t>
typename sb_handle_t::event_t _reduction(
sb_handle_t& sb_handle, input_t buffer_in, index_t ld, output_t buffer_out,
index_t rows, index_t cols, reduction_dim_t reduction_dim,
const typename sb_handle_t::event_t& _dependencies);
template <int Tile_size, int wg_size, int cl_size, bool local_memory,
typename sb_handle_t, typename container_0_t, typename container_1_t,
typename element_t, typename index_t>
typename sb_handle_t::event_t _transpose_outplace_impl(
sb_handle_t& sb_handle, index_t _M, index_t _N, element_t _alpha,
container_0_t in_, index_t _ld_in, index_t _inc_in, index_t _stride_in,
container_1_t out_, index_t _ld_out, index_t _inc_out, index_t _stride_out,
index_t _batch_size, const typename sb_handle_t::event_t& _dependencies);
template <bool both_trans, int Tile_size, int wg_size, int cl_size,
bool local_memory, typename sb_handle_t, typename container_0_t,
typename container_1_t, typename container_2_t, typename element_t,
typename index_t>
typename sb_handle_t::event_t _transpose_add_impl(
sb_handle_t& sb_handle, index_t _M, index_t _N, element_t _alpha,
container_0_t a_, index_t _lda, index_t _nrows_a, index_t _ncols_a,
index_t _stride_a, element_t _beta, container_1_t b_, index_t _ldb,
index_t _nrows_b, index_t _ncols_b, index_t _stride_b, container_2_t c_,
index_t _ldc, index_t _stride_c, index_t _batch_size,
const typename sb_handle_t::event_t& _dependencies);
template <typename sb_handle_t, typename container_0_t, typename container_1_t,
typename element_t, typename index_t>
typename sb_handle_t::event_t _axpy_batch(
sb_handle_t& sb_handle, index_t _N, element_t _alpha, container_0_t _vx,
index_t _incx, index_t _stride_x, container_1_t _vy, index_t _incy,
index_t _stride_y, index_t _batch_size,
const typename sb_handle_t::event_t& _dependencies);
template <int localSize, int maxBlockPerBatch, typename sb_handle_t,
typename container_0_t, typename container_1_t, typename element_t,
typename index_t>
typename sb_handle_t::event_t _axpy_batch_impl(
sb_handle_t& sb_handle, index_t _N, element_t _alpha, container_0_t _vx,
index_t _incx, index_t _stride_x, container_1_t _vy, index_t _incy,
index_t _stride_y, index_t _batch_size,
const typename sb_handle_t::event_t& _dependencies, index_t global_size);
} // namespace internal
/**
* \brief COPY in_matrix to out_matrix with scaling factor of alpha
*
* @tparam sb_handle_t SB_Handle type
* @tparam element_t Scaling factor type
* @tparam index_t Index type
* @tparam in_t Buffer Iterator or USM Pointer
* @tparam out_t Buffer Iterator or USM Pointer
* @param sb_handle SB_Handle
* @param trans compute matrix transpose or not.
* @param m rows of matrix
* @param n cols of matrix
* @param alpha Scaling factor
* @param in_memory BufferIterator or USM Pointer of input
* @param ld_in leading dimension of in_matrix
* @param matrix_out BufferIterator or USM Pointer of output
* @param ld_out leading dimention of out_matrix
*/
template <typename sb_handle_t, typename element_t, typename index_t,
typename in_t, typename out_t>
typename sb_handle_t::event_t _omatcopy(
sb_handle_t& sb_handle, char trans, index_t m, index_t n, element_t alpha,
in_t in_memory, index_t ld_in, out_t out_memory, index_t ld_out,
const typename sb_handle_t::event_t& _dependencies = {}) {
return internal::_matcopy<false>(
sb_handle, trans, m, n, alpha, in_memory, ld_in, static_cast<index_t>(1),
out_memory, ld_out, static_cast<index_t>(1), _dependencies);
}
/**
* \brief Copy out of place of in_matrix to out_matrix with increment between
* cols element different from 1.
*
* The increment within the same column can be different from 1 and specified
* by inc_in and inc_out arguments.
*
* @tparam sb_handle_t SB_Handle type
* @tparam element_t Scaling factor type
* @tparam index_t Index type
* @tparam in_t Buffer Iterator or USM Pointer
* @tparam out_t Buffer Iterator or USM Pointer
* @param sb_handle SB_Handle
* @param trans compute matrix transpose or not.
* @param m rows of matrix
* @param n cols of matrix
* @param alpha Scaling factor
* @param in_memory BufferIterator or USM Pointer of input
* @param ld_in leading dimension of in_matrix
* @param inc_in internal increment for the in_matrix
* @param matrix_out BufferIterator or USM Pointer of output
* @param ld_out leading dimention of out_matrix
* @param inc_out internal increment for the out_matrix
*/
template <typename sb_handle_t, typename element_t, typename index_t,
typename in_t, typename out_t>
typename sb_handle_t::event_t _omatcopy2(
sb_handle_t& sb_handle, char trans, index_t m, index_t n, element_t alpha,
in_t in_memory, index_t ld_in, index_t inc_in, out_t out_memory,
index_t ld_out, index_t inc_out,
const typename sb_handle_t::event_t& _dependencies = {}) {
return internal::_matcopy<false>(sb_handle, trans, m, n, alpha, in_memory,
ld_in, inc_in, out_memory, ld_out, inc_out,
_dependencies);
}
/**
* \brief Computes scaled addition of two matrices A & B with or without
* transpose and copying results back to an output matrix C.
*
* @tparam sb_handle_t SB_Handle type
* @tparam element_t Undelying element data type of the matrix container
* @tparam index_t Index type
* @tparam container_t Inputs/Output Container Type
* @param trans_a Apply or not matrix transpose to A.
* @param trans_b Apply or not matrix transpose to B.
* @param m Number of rows in output matrix C
* @param n Number of columns in output matrix C
* @param alpha Scaling factor of matrix A
* @param A Container Input matrix A
* @param lda Matrix A leading dimension
* @param beta scaling factor of matrix B
* @param B Container Input matrix B
* @param ldb Matrix B leading dimension
* @param C Container Output matrix C
* @param ldc Matrix C leading dimension
*/
template <typename sb_handle_t, typename element_t, typename index_t,
typename container_0_t, typename container_1_t,
typename container_2_t>
typename sb_handle_t::event_t _omatadd(
sb_handle_t& sb_handle, char trans_a, char trans_b, index_t m, index_t n,
element_t alpha, container_0_t A, index_t lda, element_t beta,
container_1_t B, index_t ldb, container_2_t C, index_t ldc,
const typename sb_handle_t::event_t& _dependencies = {}) {
return internal::_omatadd(sb_handle, trans_a, trans_b, m, n, alpha, A, lda,
beta, B, ldb, C, ldc, _dependencies);
}
/**
* \brief COPY batch of matrices inplace with scaling factor of alpha
*
* @tparam sb_handle_t SB_Handle type
* @tparam element_t Scaling factor type
* @tparam index_t Index type
* @tparam in_out_t input/output type
* @param sb_handle SB_Handle
* @param trans compute matrix transpose or not
* @param m rows of matrix
* @param n cols of matrix
* @param alpha Scaling factor
* @param memory container of input & output matrices
* @param ld_in leading dimension at input
* @param ld_out leading dimention at output
* @param stride stride distance between matrices inside batch
* @param batch_size number of matrices to compute
*/
template <typename sb_handle_t, typename element_t, typename index_t,
typename in_out_t>
typename sb_handle_t::event_t _imatcopy_batch(sb_handle_t& sb_handle,
char trans, index_t m, index_t n,
element_t alpha, in_out_t memory,
index_t ld_in, index_t ld_out,
index_t stride,
index_t batch_size) {
return internal::_matcopy_batch<true>(sb_handle, trans, m, n, alpha, memory,
ld_in, stride, memory, ld_out, stride,
batch_size);
}
/**
* \brief COPY batch of matrices outplace from in_memory to out_memory with
* scaling factor of alpha
*
* @tparam sb_handle_t SB_Handle type
* @tparam element_t Scaling factor type
* @tparam index_t Index type
* @tparam in_t container input type
* @tparam out_t container output type
* @param sb_handle SB_Handle
* @param trans compute matrix transpose or not
* @param m rows of matrix
* @param n cols of matrix
* @param alpha Scaling factor
* @param in_memory input matrix container
* @param ld_in leading dimension of input
* @param stride_in stride distance between matrices inside batch
* @param out_memory output matrix container
* @param ld_out leading dimention of output
* @param stride_out stride distance between matrices inside batch
* @param batch_size number of matrices to compute
*/
template <typename sb_handle_t, typename element_t, typename index_t,
typename in_t, typename out_t>
typename sb_handle_t::event_t _omatcopy_batch(
sb_handle_t& sb_handle, char trans, index_t m, index_t n, element_t alpha,
in_t in_memory, index_t ld_in, index_t stride_in, out_t out_memory,
index_t ld_out, index_t stride_out, index_t batch_size,
const typename sb_handle_t::event_t& _dependencies = {}) {
return internal::_matcopy_batch<false>(
sb_handle, trans, m, n, alpha, in_memory, ld_in, stride_in, out_memory,
ld_out, stride_out, batch_size, _dependencies);
}
/**
* \brief Batch Computation of scaled addition of two matrices A & B with or
* without transpose and copying results back to an output matrix C.
*
* @tparam sb_handle_t SB_Handle type
* @tparam element_t Undelying element data type of the matrix container
* @tparam index_t Index type
* @tparam container_t Inputs/Output Container Type
* @param trans_a Apply or not matrix transpose to A.
* @param trans_b Apply or not matrix transpose to B.
* @param m Number of rows in output matrix C
* @param n Number of columns in output matrix C
* @param alpha Scaling factor of matrix A
* @param A Container Input matrix A
* @param lda Matrix A leading dimension
* @param stride_a stride distance between two matrices inside A container
* @param beta scaling factor of matrix B
* @param B Container Input matrix B
* @param ldb Matrix B leading dimension
* @param stride_b stride distance between two matrices inside B container
* @param C Container Output matrix C
* @param ldc Matrix C leading dimension
* @param stride_c stride distance between two matrices inside C container
* @param batch_size number of matrices to compute in this batch
*/
template <typename sb_handle_t, typename element_t, typename index_t,
typename container_0_t, typename container_1_t,
typename container_2_t>
typename sb_handle_t::event_t _omatadd_batch(
sb_handle_t& sb_handle, char trans_a, char trans_b, index_t m, index_t n,
element_t alpha, container_0_t a, index_t lda, index_t stride_a,
element_t beta, container_1_t b, index_t ldb, index_t stride_b,
container_2_t c, index_t ldc, index_t stride_c, index_t batch_size,
const typename sb_handle_t::event_t& _dependencies = {}) {
return internal::_omatadd_batch(sb_handle, trans_a, trans_b, m, n, alpha, a,
lda, stride_a, beta, b, ldb, stride_b, c, ldc,
stride_c, batch_size, _dependencies);
}
/**
* \brief Compute a batch of AXPY operation all together
*
* Implements AXPY \f$y = ax + y\f$
*
* @param sb_handle SB_Handle
* @param _alpha scalar
* @param _vx BufferIterator or USM pointer
* @param _incx Increment for the vector X
* @param _stride_x Stride distance of two consecutive vectors in X
* @param _vy BufferIterator or USM pointer
* @param _incy Increment for the vector Y
* @param _stride_y Stride distance of two consecutive vectors in Y
* @param _batch_size number of axpy operations to compute
* @param _dependencies Vector of events
*/
template <typename sb_handle_t, typename container_0_t, typename container_1_t,
typename element_t, typename index_t>
typename sb_handle_t::event_t _axpy_batch(
sb_handle_t& sb_handle, index_t _N, element_t _alpha, container_0_t _vx,
index_t _incx, index_t _stride_x, container_1_t _vy, index_t _incy,
index_t _stride_y, index_t _batch_size,
const typename sb_handle_t::event_t& _dependencies = {}) {
return internal::_axpy_batch(sb_handle, _N, _alpha, _vx, _incx, _stride_x,
_vy, _incy, _stride_y, _batch_size,
_dependencies);
}
namespace extension {
/**
* \brief Transpose a Matrix in-place
*
* Provided matrix A serves as input with leading dimension ld_in as well as
* output with leading dimension ld_out to which it's transposed.
*
* @tparam element_t Undelying element data type of the matrix container
* @tparam sb_handle_t SB_Handle type
* @tparam index_t Index type
* @tparam in_t Input Container Type
* @tparam out_t Output Container Type
* @param sb_handle sb_handle
* @param m Rows of matrix (input)
* @param n Columns of matrix (input)
* @param A Input-Output matrix container
* @param ld_in leading dimension of A at input
* @param ld_out leading dimention of A at output
*/
template <typename element_t, typename sb_handle_t, typename index_t,
typename in_t, typename out_t>
typename sb_handle_t::event_t _transpose(
sb_handle_t& sb_handle, index_t m, index_t n, in_t A, index_t ld_in,
index_t ld_out, const typename sb_handle_t::event_t& _dependencies = {}) {
return blas::internal::_transpose<true, element_t>(sb_handle, m, n, A, ld_in,
A, ld_out, _dependencies);
}
/**
* \brief Transpose a Matrix out-of-place
*
* Input matrix A with leading dimension ld_a gets transposed and written back
* to matrix B with leading dimension ld_b.
*
* @tparam element_t Undelying element data type of the matrix container
* @tparam sb_handle_t SB_Handle type
* @tparam index_t Index type
* @tparam in_t Input Container Type
* @tparam out_t Output Container Type
* @param sb_handle sb_handle
* @param m Rows of matrix A
* @param n Columns of matrix A
* @param A Input matrix container
* @param ld_a leading dimension of A
* @param B Output matrix container
* @param ld_b leading dimention of B
*/
template <typename element_t, typename sb_handle_t, typename index_t,
typename in_t, typename out_t>
typename sb_handle_t::event_t _transpose(
sb_handle_t& sb_handle, index_t m, index_t n, in_t A, index_t ld_a, out_t B,
index_t ld_b, const typename sb_handle_t::event_t& _dependencies = {}) {
return blas::internal::_transpose<false, element_t>(sb_handle, m, n, A, ld_a,
B, ld_b, _dependencies);
}
template <typename operator_t, typename element_t, typename sb_handle_t,
typename input_t, typename output_t, typename index_t>
typename sb_handle_t::event_t _reduction(
sb_handle_t& sb_handle, input_t buffer_in, index_t ld, output_t buffer_out,
index_t rows, index_t cols, reduction_dim_t reduction_dim,
const typename sb_handle_t::event_t& _dependencies = {}) {
return blas::internal::_reduction<operator_t, element_t>(
sb_handle, buffer_in, ld, buffer_out, rows, cols, reduction_dim,
_dependencies);
}
} // namespace extension
} // namespace blas
#endif // PORTBLAS_EXTENSION_INTERFACE_H