onednn-src 0.1.13

Source of oneAPI Deep Neural Network Library (oneDNN)
Documentation
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
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
/*******************************************************************************
* Copyright 2020 Intel Corporation
*
* 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
*
* 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.
*******************************************************************************/

#include "gpu/intel/include/types.h"

#define LOAD_FLOAT8(prefix, ptr) \
    DATA_TO_FLOAT8(prefix, \
            BLOCK_TO_DATA8(prefix, \
                    READ_BLOCK8(prefix, \
                            (__global BLOCK_T(ALIAS(prefix)) *)(ptr))))

#define STORE_FLOAT8(prefix, ptr, val) \
    WRITE_BLOCK8(prefix, (__global BLOCK_T(ALIAS(prefix)) *)(ptr), \
            DATA_TO_BLOCK8(prefix, FLOAT_TO_DATA8(prefix, val)))

#define LOAD_DOUBLE8(prefix, ptr) \
    DATA_TO_DOUBLE8(prefix, \
            BLOCK_TO_DATA8(prefix, \
                    READ_BLOCK8(prefix, \
                            (__global BLOCK_T(ALIAS(prefix)) *)(ptr))))

#define STORE_DOUBLE8(prefix, ptr, val) \
    WRITE_BLOCK8(prefix, (__global BLOCK_T(ALIAS(prefix)) *)(ptr), \
            DATA_TO_BLOCK8(prefix, DOUBLE_TO_DATA8(prefix, val)))

#if DST_DT_F64
#define UP_CASE_DATA DOUBLE
#define COMMON_DATA_T double
#define COMMON_DATA_MAX DBL_MAX
#define COMMON_DATA_ZERO 0.0
#else
#define UP_CASE_DATA FLOAT
#define COMMON_DATA_T float
#define COMMON_DATA_MAX FLT_MAX
#define COMMON_DATA_ZERO 0.0f
#endif

#define COMMON_DATA8_T CONCAT2(COMMON_DATA_T, 8)

#define COMMON_DATA_TO_X(x, y) CONCAT2(DATA_TO_, UP_CASE_DATA)(x, y)
#define COMMON_X_TO_DATA(x, y) CONCAT2(UP_CASE_DATA, _TO_DATA)(x, y)

#define COMMON_LOAD_DATA8(x, y) CONCAT3(LOAD_, UP_CASE_DATA, 8)(x, y)
#define COMMON_STORE_DATA8(x, y, z) CONCAT3(STORE_, UP_CASE_DATA, 8)(x, y, z)

#define VECT_SIZE 8
#define SV (GROUP_SIZE * VECT_SIZE)
#define HAS_TAIL (SOFTMAX_AXIS_SIZE % SV != 0)
#define NUM_BUF ((SOFTMAX_AXIS_SIZE + SV - 1) / SV)
#define SMALL_BUFFER (REPEAT_SUBGRP_BUF_SIZE < THREAD_BUF_SIZE)

#if IS_FWD

int find_axis_offset(int index, int local_id, int subgroup) {
    const int group_axis_block = GROUP_SIZE * THREAD_BUF_SIZE * CHANNELS;
    int offset = CHANNELS * THREAD_BUF_SIZE * local_id;
    if (index > 0) { offset += group_axis_block; }
    if (index > 0 && subgroup == (SUBGROUPS_REPEATED - 1) && SMALL_BUFFER) {
        offset = group_axis_block
                + (CHANNELS * REPEAT_SUBGRP_BUF_SIZE * local_id);
    }
    return offset;
}

int get_local_off(int subgroup, int subgroup_local_id) {
    if (subgroup == (SUBGROUPS_REPEATED - 1)) {
        if (SMALL_BUFFER) {
            return ((GROUP_SIZE + SUB_GROUP_SIZE * subgroup) * THREAD_BUF_SIZE
                    + subgroup_local_id * REPEAT_SUBGRP_BUF_SIZE);
        } else { // THREAD_BUF_SIZE == REPEAT_SUBGRP_BUF_SIZE i.e. 8 == 8
            return ((GROUP_SIZE + SUB_GROUP_SIZE * subgroup + subgroup_local_id)
                    * THREAD_BUF_SIZE);
        }
    } else {
        return 1; // subgroup thread within normal range
    }
}

int get_buffer_size(int index, int subgroup, int local_off) {
    if (index > 0 && subgroup == (SUBGROUPS_REPEATED - 1)) {
        if (SMALL_BUFFER) {
            int tail = SOFTMAX_AXIS_SIZE
                    - ((GROUP_SIZE + subgroup) * THREAD_BUF_SIZE);
            return ((local_off + REPEAT_SUBGRP_BUF_SIZE) <= SOFTMAX_AXIS_SIZE)
                    ? REPEAT_SUBGRP_BUF_SIZE
                    : tail % REPEAT_SUBGRP_BUF_SIZE;
        } else {
            return ((local_off + THREAD_BUF_SIZE) <= SOFTMAX_AXIS_SIZE)
                    ? THREAD_BUF_SIZE
                    : SOFTMAX_AXIS_SIZE % THREAD_BUF_SIZE;
        }
    } else {
        return THREAD_BUF_SIZE;
    }
}

__attribute__((reqd_work_group_size(GROUP_SIZE, 1, 1)))
__attribute__((intel_reqd_sub_group_size(SUB_GROUP_SIZE))) __kernel void
xe_softmax_fwd(__global SRC_DATA_T *src, __global DST_DATA_T *dst,
        __global float *src_scale, __global float *dst_scale) {
    float scale = 1.0f;
#if WITH_SRC_SCALES
    scale *= src_scale[0];
#endif
#if WITH_DST_SCALES
    scale /= dst_scale[0];
#endif
#if IS_NHWC || IS_BLOCKED
    // gws is the combination of mb and axis size
    const int group = get_global_id(0) / GROUP_SIZE;
    const int mb = group / CHANNELS_PADDED;
    const int channel_id = group % CHANNELS_PADDED;

    const int local_id = get_local_id(0);
    const int subgroup_local_id = get_sub_group_local_id();
    const int subgroup_id = get_sub_group_id();

    int buf_chunk = (local_id / SUB_GROUP_SIZE) * SOFTMAX_BUF;
    COMMON_DATA_T max_ = -COMMON_DATA_MAX;
    COMMON_DATA_T denom_ = COMMON_DATA_ZERO;

#if SUBGROUPS_REPEATED // only for NHWC kernel
    // total reads should be num_buf x THREAD_BUF_SIZE

    COMMON_DATA_T d[2][THREAD_BUF_SIZE];

    int num_buf = (subgroup_id < SUBGROUPS_REPEATED) ? 2 : 1;

    int local_off = get_local_off(subgroup_id, subgroup_local_id);

    for (int i = 0; i < num_buf; i++) {
        if (i > 0 && local_off >= SOFTMAX_AXIS_SIZE) break;

        __global SRC_DATA_T *src_copy = src;
        int axis_offset = find_axis_offset(i, subgroup_local_id, subgroup_id);
        off_t data_off = (off_t)mb * CHANNELS_PADDED * SOFTMAX_AXIS_SIZE
                + axis_offset + channel_id;
        int buf_reads = get_buffer_size(i, subgroup_id, local_off);

        src_copy += data_off;
        for (int k = 0, axis_channel_id = CHANNELS * buf_chunk; k < buf_reads;
                ++k, axis_channel_id += CHANNELS) {
            d[i][k] = COMMON_DATA_TO_X(SRC, src_copy[axis_channel_id]);
            max_ = max(d[i][k], max_);
        }
    }

#if GROUP_SIZE == SUB_GROUP_SIZE
    max_ = sub_group_reduce_max(max_);
#else
    max_ = work_group_reduce_max(max_);
#endif

    for (int i = 0; i < num_buf; i++) {
        if (i > 0 && local_off >= SOFTMAX_AXIS_SIZE) break;

        int buf_reads = get_buffer_size(i, subgroup_id, local_off);
        for (int k = 0; k < buf_reads; ++k) {
#if LOGSOFTMAX
            denom_ += exp(d[i][k] - max_);
#else
            d[i][k] = exp(d[i][k] - max_);
            denom_ += d[i][k];
#endif
        }
    }

#if GROUP_SIZE == SUB_GROUP_SIZE
    denom_ = sub_group_reduce_add(denom_);
#else
    denom_ = work_group_reduce_add(denom_);
#endif

#if LOGSOFTMAX
    denom_ = log(denom_);
#else
    denom_ = (SOFTMAX_INF_AS_ZERO && denom_ == 0.f) ? 1.0f : 1.0f / denom_;
#endif

    for (int i = 0; i < num_buf; i++) {
        if (i > 0 && local_off >= SOFTMAX_AXIS_SIZE) break;

        __global DST_DATA_T *dst_copy = dst;
        int axis_offset = find_axis_offset(i, subgroup_local_id, subgroup_id);
        off_t data_off = (off_t)mb * CHANNELS_PADDED * SOFTMAX_AXIS_SIZE
                + axis_offset + channel_id;
        int buf_reads = get_buffer_size(i, subgroup_id, local_off);
        dst_copy += data_off;
        for (int k = 0, axis_channel_id = CHANNELS * buf_chunk; k < buf_reads;
                ++k, axis_channel_id += CHANNELS) {
#if LOGSOFTMAX
            d[i][k] = d[i][k] - max_ - denom_;
#else
            d[i][k] = d[i][k] * denom_;
#endif
            dst_copy[axis_channel_id] = COMMON_X_TO_DATA(DST, d[i][k] * scale);
        }
    }

#else
    // NHWC kernel for lws size < max_lws or multiples of max_lws
    // Blocked layout kernel for 128-byte reads and writes
    const int channel_offset = CHANNELS * THREAD_BUF_SIZE * subgroup_local_id;

#if IS_BLOCKED
    const int channel_block = channel_id / CHANNELS;
    const int channel_in_block = channel_id % CHANNELS;

    off_t data_off = (off_t)mb * CHANNELS * SOFTMAX_AXIS_SIZE + channel_offset
            + channel_in_block;
    const int buf_reads = THREAD_BUF_SIZE;
#else
    off_t data_off = (off_t)mb * CHANNELS_PADDED * SOFTMAX_AXIS_SIZE
            + channel_offset + channel_id;

    const int local_off = local_id * THREAD_BUF_SIZE;
    int buf_reads;
    if (local_off >= SOFTMAX_AXIS_SIZE) {
        buf_reads = 0;
    } else {
        buf_reads = ((local_off + THREAD_BUF_SIZE) <= SOFTMAX_AXIS_SIZE)
                ? THREAD_BUF_SIZE
                : (SOFTMAX_AXIS_SIZE % THREAD_BUF_SIZE);
    }
#endif

    COMMON_DATA_T d[THREAD_BUF_SIZE];
    src += data_off;
    for (int k = 0, axis_channel_id = CHANNELS * buf_chunk; k < buf_reads;
            ++k, axis_channel_id += CHANNELS) {
        d[k] = COMMON_DATA_TO_X(SRC, src[axis_channel_id]);
        max_ = max(d[k], max_);
    }

#if GROUP_SIZE == SUB_GROUP_SIZE
    max_ = sub_group_reduce_max(max_);
#else
    max_ = work_group_reduce_max(max_);
#endif
    for (int k = 0; k < buf_reads; ++k) {
#if LOGSOFTMAX
        denom_ += exp(d[k] - max_);
#else
        d[k] = exp(d[k] - max_);
        denom_ += d[k];
#endif
    }

#if GROUP_SIZE == SUB_GROUP_SIZE
    denom_ = sub_group_reduce_add(denom_);
#else
    denom_ = work_group_reduce_add(denom_);
#endif
#if LOGSOFTMAX
    denom_ = log(denom_);
#else
    denom_ = (SOFTMAX_INF_AS_ZERO && denom_ == 0.f) ? 1.0f : 1.0f / denom_;
#endif

    dst += data_off;

    for (int k = 0, axis_channel_id = CHANNELS * buf_chunk; k < buf_reads;
            ++k, axis_channel_id += CHANNELS) {
#if LOGSOFTMAX
        d[k] = d[k] - max_ - denom_;
#else
        d[k] = d[k] * denom_;
#endif
        dst[axis_channel_id] = COMMON_X_TO_DATA(DST, d[k] * scale);
    }
#endif

#else // NCHW kernel starts here
    const off_t data_off
            = (off_t)(get_global_id(0) / GROUP_SIZE) * SOFTMAX_AXIS_SIZE;

    COMMON_DATA8_T d[NUM_BUF];
    COMMON_DATA_T max_ = -COMMON_DATA_MAX;
    COMMON_DATA_T denom_ = COMMON_DATA_ZERO;

    int last_buf = HAS_TAIL ? (NUM_BUF - 1) : NUM_BUF;

    src += data_off;
    int sid = get_sub_group_id();

#if IS_READ_ALIGNED
    for (int k = 0; k < last_buf; ++k) {
#if GROUP_SIZE == SUB_GROUP_SIZE
        int idx = k * SUB_GROUP_SIZE;
#else
        int idx = HAS_TAIL ? k * SUB_GROUP_SIZE : sid * SUB_GROUP_SIZE;
#endif
        d[k] = COMMON_LOAD_DATA8(SRC, &src[idx * VECT_SIZE]);
        for (int i = 0; i < VECT_SIZE; ++i) {
            max_ = max(d[k][i], max_);
        }
    }
#if HAS_TAIL
    {
        int k = last_buf;
        for (int i = 0; i < VECT_SIZE; ++i) {
            int off = k * VECT_SIZE * SUB_GROUP_SIZE + i * SUB_GROUP_SIZE
                    + get_sub_group_local_id();
            d[k][i] = (off < SOFTMAX_AXIS_SIZE ? COMMON_DATA_TO_X(SRC, src[off])
                                               : -COMMON_DATA_MAX);
            max_ = max(d[k][i], max_);
        }
    }
#endif
#else // subgroup block read requires 4-byte alignment
    for (int k = 0; k < NUM_BUF; ++k) {
        for (int i = 0; i < VECT_SIZE; ++i) {
            int off = k * VECT_SIZE * SUB_GROUP_SIZE + i * SUB_GROUP_SIZE
                    + get_sub_group_local_id();
            d[k][i] = (off < SOFTMAX_AXIS_SIZE ? DATA_TO_FLOAT(SRC, src[off])
                                               : -FLT_MAX);
            max_ = max(d[k][i], max_);
        }
    }
#endif

#if GROUP_SIZE == SUB_GROUP_SIZE
    max_ = sub_group_reduce_max(max_);
#else
    max_ = work_group_reduce_max(max_);
#endif

    for (int k = 0; k < last_buf; ++k) {
#if LOGSOFTMAX
        for (int i = 0; i < VECT_SIZE; ++i)
            denom_ += exp(d[k][i] - max_);
#else
        d[k] = exp(d[k] - max_);
        for (int i = 0; i < VECT_SIZE; ++i)
            denom_ += d[k][i];
#endif
    }

#if HAS_TAIL
    {
        int k = last_buf;
#if LOGSOFTMAX
        for (int i = 0; i < VECT_SIZE; ++i) {
            int off = k * VECT_SIZE * SUB_GROUP_SIZE + i * SUB_GROUP_SIZE
                    + get_sub_group_local_id();
            if (off < SOFTMAX_AXIS_SIZE) denom_ += exp(d[k][i] - max_);
        }
#else
        d[k] = exp(d[k] - max_);
        for (int i = 0; i < VECT_SIZE; ++i) {
            int off = k * VECT_SIZE * SUB_GROUP_SIZE + i * SUB_GROUP_SIZE
                    + get_sub_group_local_id();
            if (off < SOFTMAX_AXIS_SIZE) denom_ += d[k][i];
        }
#endif
    }
#endif

#if GROUP_SIZE == SUB_GROUP_SIZE
    denom_ = sub_group_reduce_add(denom_);
#else
    denom_ = work_group_reduce_add(denom_);
#endif

#if LOGSOFTMAX
    denom_ = log(denom_);
#else
    denom_ = (SOFTMAX_INF_AS_ZERO && denom_ == 0.f) ? 1.0f : 1.0f / denom_;
#endif

    dst += data_off;
#if IS_WRITE_ALIGNED
    for (int k = 0; k < last_buf; ++k) {
#if GROUP_SIZE == SUB_GROUP_SIZE
        int idx = k * SUB_GROUP_SIZE;
#else
        int idx = HAS_TAIL ? k * SUB_GROUP_SIZE : sid * SUB_GROUP_SIZE;
#endif
#if LOGSOFTMAX
        d[k] = d[k] - max_ - denom_;
#else
        d[k] = d[k] * denom_;
#endif

        COMMON_STORE_DATA8(DST, &dst[idx * VECT_SIZE], scale * d[k]);
    }
#if HAS_TAIL // subgroup block write requires 16-byte alignment
    {
        int k = last_buf;
#if LOGSOFTMAX
        d[k] = d[k] - max_ - denom_;
#else
        d[k] = d[k] * denom_;
#endif
        for (int i = 0; i < VECT_SIZE; i++) {
            int off = k * VECT_SIZE * SUB_GROUP_SIZE + i * SUB_GROUP_SIZE
                    + get_sub_group_local_id();
            if (off < SOFTMAX_AXIS_SIZE)
                dst[off] = COMMON_X_TO_DATA(DST, scale * d[k][i]);
        }
    }
#endif
#else // for test-cases not aligned by 16 bytes needed for block write
    for (int k = 0; k < NUM_BUF; k++) {
#if LOGSOFTMAX
        d[k] = d[k] - max_ - denom_;
#else
        d[k] = d[k] * denom_;
#endif
        for (int i = 0; i < VECT_SIZE; i++) {
            int off = k * VECT_SIZE * SUB_GROUP_SIZE + i * SUB_GROUP_SIZE
                    + get_sub_group_local_id();
            if (off < SOFTMAX_AXIS_SIZE)
                dst[off] = COMMON_X_TO_DATA(DST, scale * d[k][i]);
        }
    }
#endif
#endif
}

#endif
#if IS_BWD
__attribute__((reqd_work_group_size(GROUP_SIZE, 1, 1)))
__attribute__((intel_reqd_sub_group_size(SUB_GROUP_SIZE))) __kernel void
xe_softmax_bwd(__global DST_DATA_T *dst, __global SRC_DATA_T *diff_src,
        __global DST_DATA_T *diff_dst) {
#if IS_NHWC || IS_16C
    const int groups = get_global_id(0) / GROUP_SIZE;
    const int batch = groups / IC_PADDED;
    const int ic = groups % IC_PADDED;
    const int sub_grp_id = get_sub_group_local_id();
    const int local_id = get_local_id(0);
    const int slice = local_id / SUB_GROUP_SIZE;
    const int ic_buff = IC * VECT_SIZE;

#if IS_16C
    const int ic_blk = ic / IC;
    const int ic_in_blk = ic % IC;
    off_t data_off = (off_t)BATCH * IC * SOFTMAX_AXIS_SIZE * ic_blk
            + (off_t)batch * IC * SOFTMAX_AXIS_SIZE + ic_buff * sub_grp_id
            + ic_in_blk;
#else
    off_t data_off
            = (off_t)batch * IC * SOFTMAX_AXIS_SIZE + ic_buff * sub_grp_id + ic;
#endif

    COMMON_DATA_T sbr = COMMON_DATA_ZERO;
    COMMON_DATA_T diff_d[VECT_SIZE];
    COMMON_DATA_T dst_[VECT_SIZE];

    diff_dst += data_off;
    dst += data_off;

    for (int i = 0, idx = IC * slice * SOFTMAX_BUF; i < VECT_SIZE;
            ++i, idx += IC) {
        diff_d[i] = COMMON_DATA_TO_X(DST, diff_dst[idx]);
        dst_[i] = COMMON_DATA_TO_X(DST, dst[idx]);
#if LOGSOFTMAX
        sbr += diff_d[i];
#else
        sbr += dst_[i] * diff_d[i];
#endif
    }
#if GROUP_SIZE == SUB_GROUP_SIZE
    sbr = sub_group_reduce_add(sbr);
#else
    sbr = work_group_reduce_add(sbr);
#endif
    diff_src += data_off;

    for (int i = 0, idx = IC * slice * SOFTMAX_BUF; i < VECT_SIZE;
            ++i, idx += IC) {
#if LOGSOFTMAX
        diff_d[i] = diff_d[i] - exp(dst_[i]) * sbr;
#else
        diff_d[i] = (diff_d[i] - sbr) * dst_[i];
#endif
        diff_src[idx] = COMMON_X_TO_DATA(SRC, diff_d[i]);
    }

#else
    const off_t data_off
            = (off_t)(get_global_id(0) / GROUP_SIZE) * SOFTMAX_AXIS_SIZE;

    COMMON_DATA_T sbr = COMMON_DATA_ZERO;
    COMMON_DATA8_T diff_d[NUM_BUF];
    COMMON_DATA8_T dst_[NUM_BUF];

    diff_dst += data_off;
    dst += data_off;
    for (int k = 0; k < NUM_BUF; ++k) {
        diff_d[k] = COMMON_LOAD_DATA8(
                DST, &diff_dst[k * VECT_SIZE * SUB_GROUP_SIZE]);
        dst_[k] = COMMON_LOAD_DATA8(DST, &dst[k * VECT_SIZE * SUB_GROUP_SIZE]);

        for (int i = 0; i < VECT_SIZE; ++i) {
#if LOGSOFTMAX
            sbr += diff_d[k][i];
#else
            sbr += dst_[k][i] * diff_d[k][i];
#endif
        }
    }

    sbr = sub_group_reduce_add(sbr);

    diff_src += data_off;

    for (int k = 0; k < NUM_BUF; ++k) {
#if LOGSOFTMAX
        diff_d[k] = diff_d[k] - exp(dst_[k]) * sbr;
#else
        diff_d[k] = (diff_d[k] - sbr) * dst_[k];
#endif
        COMMON_STORE_DATA8(
                SRC, &diff_src[k * VECT_SIZE * SUB_GROUP_SIZE], diff_d[k]);
    }
#endif
}
#endif