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gridwise_gemm_xdlops_bwd_weight.hpp
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1 // SPDX-License-Identifier: MIT
2 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
3 
4 #pragma once
5 
17 
18 namespace ck {
19 
20 // Implementation of "Merge" transformation primitive that uses division and mod. It is supposed to
21 // be used for low_lengths that are known at compile time and are power of 2, otherwise performance
22 // will be very bad
23 template <typename LowLengths>
25 {
26  static constexpr index_t NDimLow = LowLengths::Size();
27 
30 
32  decltype(container_reverse_exclusive_scan(LowLengths{}, math::multiplies{}, Number<1>{}));
33 
34  using UpLengths =
35  decltype(make_tuple(container_reduce(LowLengths{}, math::multiplies{}, Number<1>{})));
36 
37  LowLengths low_lengths_;
40 
41  __host__ __device__ constexpr Merge_v4_no_carry() = default;
42 
43  __host__ __device__ constexpr Merge_v4_no_carry(const LowLengths& low_lengths)
44  : low_lengths_{low_lengths},
46  container_reverse_exclusive_scan(low_lengths, math::multiplies{}, Number<1>{})},
47  up_lengths_{make_tuple(container_reduce(low_lengths, math::multiplies{}, Number<1>{}))}
48  {
49  static_assert(LowerIndex::Size() == NDimLow, "wrong!");
50  }
51 
52  __host__ __device__ static constexpr index_t GetNumOfLowerDimension() { return NDimLow; }
53 
54  __host__ __device__ static constexpr index_t GetNumOfUpperDimension() { return 1; }
55 
56  __host__ __device__ constexpr const auto& GetUpperLengths() const { return up_lengths_; }
57 
58  template <typename LowIdx, typename UpIdx>
59  __host__ __device__ constexpr void CalculateLowerIndex(LowIdx& idx_low,
60  const UpIdx& idx_up) const
61  {
62  static_assert(LowIdx::Size() == NDimLow && UpIdx::Size() == 1,
63  "wrong! inconsistent # of dimension");
64 
65  index_t tmp = idx_up[Number<0>{}];
66 
67  // division and mod
68  static_for<0, NDimLow - 1, 1>{}([&](auto i) {
69  idx_low(i) = tmp / this->low_lengths_scan_[i];
70  tmp %= this->low_lengths_scan_[i];
71  });
72 
73  idx_low(Number<NDimLow - 1>{}) = tmp;
74  }
75 
76  template <typename LowIdxDiff,
77  typename UpIdxDiff,
78  typename LowIdx,
79  typename UpIdx,
80  index_t Hack>
81  __host__ __device__ void UpdateLowerIndex(LowIdxDiff& idx_diff_low,
82  const UpIdxDiff& idx_up_diff,
83  LowIdx& idx_low,
84  const UpIdx& idx_up_new,
85  Number<Hack>) const
86  {
87  static_assert(LowIdxDiff::Size() == NDimLow && UpIdxDiff::Size() == 1 &&
88  LowIdx::Size() == NDimLow && UpIdx::Size() == 1,
89  "wrong! inconsistent # of dimension");
90 
91  constexpr auto I0 = Number<0>{};
92  constexpr auto INm1 = Number<NDimLow - 1>{};
93 
94  index_t tmp = idx_up_new[I0];
95 
96  idx_low(INm1) = tmp;
97  idx_diff_low(INm1) = idx_up_diff[I0];
98  }
99 
100  __host__ __device__ static constexpr bool IsLinearTransform() { return false; }
101 
102  __host__ __device__ static constexpr bool IsValidUpperIndexAlwaysMappedToValidLowerIndex()
103  {
104  return true;
105  }
106 
107  __host__ __device__ static constexpr bool IsKnownAtCompileTime()
108  {
112  }
113 
114  template <typename UpIdx>
115  __host__ __device__ static constexpr bool
116  IsValidUpperIndexMappedToValidLowerIndex(const UpIdx& /* idx_up */)
117  {
118  return true;
119  }
120 
121  __host__ __device__ void Print() const
122  {
123  printf("{");
124  printf("Merge_v3_direct_division_mod_wrw, ");
125  printf("low_lengths_ ");
126  print_multi_index(low_lengths_);
127  printf("low_lengths_scan_ ");
128  print_multi_index(low_lengths_scan_);
129  printf("up_lengths_ ");
130  print_multi_index(up_lengths_);
131  printf("}");
132  }
133 };
134 
135 template <typename LowLengths>
136 __host__ __device__ constexpr auto make_merge_transform_v4_no_carry(const LowLengths& low_lengths)
137 {
138  return Merge_v4_no_carry<LowLengths>{low_lengths};
139 }
140 
141 template <typename GridwiseGemm,
142  typename FloatA,
143  typename FloatB,
144  typename FloatC,
145  typename AGridDesc_B_K0_M_K1,
146  typename BGridDesc_B_K0_N_K1,
147  typename CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
148  typename AElementwiseOperation,
149  typename BElementwiseOperation,
150  typename CElementwiseOperation,
151  typename CBlockClusterAdaptor,
152  bool HasMainKBlockLoop>
153 __global__ void
154 #if CK_USE_LAUNCH_BOUNDS
155  __launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
156 #endif
157  kernel_gemm_xdlops_bwd_weight(const FloatA* __restrict__ p_a_grid,
158  const FloatB* __restrict__ p_b_grid,
159  FloatC* __restrict__ p_c_grid,
160  const AGridDesc_B_K0_M_K1 a_b_k0_m_k1_grid_desc,
161  const BGridDesc_B_K0_N_K1 b_b_k0_n_k1_grid_desc,
162  const CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock
163  c_grid_desc_mblock_mperblock_nblock_nperblock,
164  const AElementwiseOperation a_element_op,
165  const BElementwiseOperation b_element_op,
166  const CElementwiseOperation c_element_op,
167  const CBlockClusterAdaptor c_block_cluster_adaptor)
168 {
169 #if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
170  defined(__gfx94__))
171  __shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
172 
173  GridwiseGemm::template Run<HasMainKBlockLoop>(p_a_grid,
174  p_b_grid,
175  p_c_grid,
176  p_shared,
177  a_b_k0_m_k1_grid_desc,
178  b_b_k0_n_k1_grid_desc,
179  c_grid_desc_mblock_mperblock_nblock_nperblock,
180  a_element_op,
181  b_element_op,
182  c_element_op,
183  c_block_cluster_adaptor);
184 #else
185  ignore = p_a_grid;
186  ignore = p_b_grid;
187  ignore = p_c_grid;
188  ignore = a_b_k0_m_k1_grid_desc;
189  ignore = b_b_k0_n_k1_grid_desc;
190  ignore = c_grid_desc_mblock_mperblock_nblock_nperblock;
191  ignore = a_element_op;
192  ignore = b_element_op;
193  ignore = c_element_op;
194  ignore = c_block_cluster_adaptor;
195 #endif // end of if (defined(__gfx908__) || defined(__gfx90a__))
196 }
197 
198 template <index_t BlockSize,
199  typename FloatA,
200  typename FloatB,
201  typename FloatAcc,
202  typename FloatC,
203  InMemoryDataOperationEnum CGlobalMemoryDataOperation,
204  typename AGridDesc_B_K0_M_K1,
205  typename BGridDesc_B_K0_N_K1,
206  typename CMNGridDesc,
207  typename AElementwiseOperation,
208  typename BElementwiseOperation,
209  typename CElementwiseOperation,
210  index_t MPerBlock,
211  index_t NPerBlock,
212  index_t K0PerBlock,
213  index_t MPerXDL,
214  index_t NPerXDL,
215  index_t K1Value,
216  index_t MRepeat,
217  index_t NRepeat,
218  typename ABlockTransferThreadClusterLengths_K0_M_K1,
219  typename ABlockTransferThreadClusterArrangeOrder,
220  typename ABlockTransferSrcAccessOrder,
221  index_t ABlockTransferSrcVectorDim,
222  index_t ABlockTransferSrcScalarPerVector,
223  index_t ABlockTransferDstScalarPerVector_K1,
224  bool AThreadTransferSrcResetCoordinateAfterRun,
225  bool ABlockLdsExtraM,
226  index_t ABlockLdsM1PerBlock,
227  index_t ABlockLdsM0PerBlock,
228  index_t ABlockLdsM1Padding,
229  typename BBlockTransferThreadClusterLengths_K0_N_K1,
230  typename BBlockTransferThreadClusterArrangeOrder,
231  typename BBlockTransferSrcAccessOrder,
232  index_t BBlockTransferSrcVectorDim,
233  index_t BBlockTransferSrcScalarPerVector,
234  index_t BBlockTransferDstScalarPerVector_K1,
235  bool BThreadTransferSrcResetCoordinateAfterRun,
236  bool BBlockLdsExtraN,
237  index_t BBlockLdsN1PerBlock,
238  index_t BBlockLdsN0PerBlock,
239  index_t BBlockLdsN1Padding,
240  index_t CShuffleMRepeatPerShuffle,
241  index_t CShuffleNRepeatPerShuffle,
242  index_t CBlockTransferScalarPerVector_NWaveNPerXDL,
243  typename CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
244  bool ABlockLdsExtraM1Wrw = false,
245  bool BBlockLdsExtraN1Wrw = false,
246  index_t NumGemmKPrefetchStage = 1,
247  PipelineVersion PipelineVer = PipelineVersion::v1,
248  typename ComputeTypeA = FloatA,
249  typename ComputeTypeB = ComputeTypeA>
251 {
252  static constexpr auto I0 = Number<0>{};
253  static constexpr auto I1 = Number<1>{};
254  static constexpr auto I2 = Number<2>{};
255  static constexpr auto I3 = Number<3>{};
256  static constexpr auto I4 = Number<4>{};
257  static constexpr auto I5 = Number<5>{};
258  static constexpr auto I6 = Number<6>{};
259  static constexpr auto I7 = Number<7>{};
260 
261  // K1 should be Number<...>
262  static constexpr auto K1 = Number<K1Value>{};
263 
265 
267  decltype(GridwiseGemmPipeline_Selector<PipelineVer, NumGemmKPrefetchStage>())>;
268 
269  // denorm test fix, required to work around fp16 mfma issue
270  // we convert fp16->fp32->bf16 and execute bf16 mfma instruction
271  // when mfma if fixed, remove this section and update
272  // FloatAAdjusted -> ComputeTypeA, FloatBAdjusted -> ComputeTypeB,
273  // throughout this file
274 #if CK_GFX90A_DENORM_WORKAROUND
275  using FloatAAdjusted =
277  using FloatBAdjusted =
279 #else
280  using FloatAAdjusted = ComputeTypeA;
281  using FloatBAdjusted = ComputeTypeB;
282 #endif
283 
284  // M0/M1/M1Padding
285  static constexpr auto M1PerBlock = Number<ABlockLdsM1PerBlock>{};
286  static constexpr auto M0PerBlock = Number<ABlockLdsM0PerBlock>{};
287  static constexpr auto M1Padding = Number<ABlockLdsM1Padding>{};
288 
289  // N0/N1/N1Padding
290  static constexpr auto N1PerBlock = Number<BBlockLdsN1PerBlock>{};
291  static constexpr auto N0PerBlock = Number<BBlockLdsN0PerBlock>{};
292  static constexpr auto N1Padding = Number<BBlockLdsN1Padding>{};
293 
294  __host__ __device__ static constexpr auto GetABlockDescriptor_K0PerBlock_MPerBlock_K1()
295  {
296  constexpr auto max_lds_align = K1;
297 
298  // A matrix in LDS memory, dst of blockwise copy
299  constexpr auto a_block_desc_k0_m_k1 = [&]() {
300  if constexpr(ABlockLdsExtraM)
301  {
302  if constexpr(ABlockLdsExtraM1Wrw)
303  {
304  constexpr auto a_block_desc_k0_m0_m1_k1 = make_naive_tensor_descriptor(
305  make_tuple(
307  make_tuple(Number<M0PerBlock>{} * (Number<M1PerBlock>{} * K1 + M1Padding),
308  Number<M1PerBlock>{} * K1 + M1Padding,
309  K1,
310  I1));
311 
312  constexpr auto a_block_desc_k0_m_k1_tmp = transform_tensor_descriptor(
313  a_block_desc_k0_m0_m1_k1,
320 
321  return a_block_desc_k0_m_k1_tmp;
322  }
323  else
324  {
327  make_tuple(Number<MPerBlock + 1>{} * K1, K1, I1));
328  }
329  }
330  else
331  {
333  make_tuple(Number<K0PerBlock>{}, Number<MPerBlock>{}, K1), max_lds_align);
334  }
335  }();
336 
337  return a_block_desc_k0_m_k1;
338  }
339 
340  __host__ __device__ static constexpr auto GetABlockDescriptor_Batch_K0PerBlock_MPerBlock_K1()
341  {
342  constexpr auto max_lds_align = K1;
343 
344  // A matrix in LDS memory, dst of blockwise copy
345  constexpr auto a_block_desc_b_k0_m_k1 = [&]() {
346  if constexpr(ABlockLdsExtraM)
347  {
348  if constexpr(ABlockLdsExtraM1Wrw)
349  {
350  constexpr auto a_block_desc_b_k0_m0_m1_k1 = make_naive_tensor_descriptor(
355  K1),
357  (Number<M1PerBlock>{} * K1 + M1Padding),
358  Number<M0PerBlock>{} * (Number<M1PerBlock>{} * K1 + M1Padding),
359  Number<M1PerBlock>{} * K1 + M1Padding,
360  K1,
361  I1));
362 
363  constexpr auto a_block_desc_b_k0_m_k1_tmp = transform_tensor_descriptor(
364  a_block_desc_b_k0_m0_m1_k1,
372 
373  return a_block_desc_b_k0_m_k1_tmp;
374  }
375  else
376  {
380  Number<MPerBlock + 1>{} * K1,
381  K1,
382  I1));
383  }
384  }
385  else
386  {
389  max_lds_align);
390  }
391  }();
392 
393  return a_block_desc_b_k0_m_k1;
394  }
395 
396  __host__ __device__ static constexpr auto GetBBlockDescriptor_K0PerBlock_NPerBlock_K1()
397  {
398  constexpr auto max_lds_align = K1;
399 
400  // B matrix in LDS memory, dst of blockwise copy
401  constexpr auto b_block_desc_k0_n_k1 = [&]() {
402  if constexpr(BBlockLdsExtraN)
403  {
404  if constexpr(BBlockLdsExtraN1Wrw)
405  {
406  constexpr auto b_block_desc_k0_n0_n1_k1 = make_naive_tensor_descriptor(
407  make_tuple(
409  make_tuple(Number<N0PerBlock>{} * (Number<N1PerBlock>{} * K1 + N1Padding),
410  Number<N1PerBlock>{} * K1 + N1Padding,
411  K1,
412  I1));
413 
414  constexpr auto b_block_desc_k0_n_k1_tmp = transform_tensor_descriptor(
415  b_block_desc_k0_n0_n1_k1,
422 
423  return b_block_desc_k0_n_k1_tmp;
424  }
425  else
426  {
429  make_tuple(Number<NPerBlock + 1>{} * K1, K1, I1));
430  }
431  }
432  else
433  {
435  make_tuple(Number<K0PerBlock>{}, Number<NPerBlock>{}, K1), max_lds_align);
436  }
437  }();
438 
439  return b_block_desc_k0_n_k1;
440  }
441 
442  __host__ __device__ static constexpr auto GetBBlockDescriptor_Batch_K0PerBlock_NPerBlock_K1()
443  {
444  constexpr auto max_lds_align = K1;
445 
446  // B matrix in LDS memory, dst of blockwise copy
447  constexpr auto b_block_desc_b_k0_n_k1 = [&]() {
448  if constexpr(BBlockLdsExtraN)
449  {
450  if constexpr(BBlockLdsExtraN1Wrw)
451  {
452  constexpr auto b_block_desc_b_k0_n0_n1_k1 = make_naive_tensor_descriptor(
457  K1),
459  (Number<N1PerBlock>{} * K1 + N1Padding),
460  Number<N0PerBlock>{} * (Number<N1PerBlock>{} * K1 + N1Padding),
461  Number<N1PerBlock>{} * K1 + N1Padding,
462  K1,
463  I1));
464 
465  constexpr auto b_block_desc_b_k0_n_k1_tmp = transform_tensor_descriptor(
466  b_block_desc_b_k0_n0_n1_k1,
474 
475  return b_block_desc_b_k0_n_k1_tmp;
476  }
477  else
478  {
482  Number<NPerBlock + 1>{} * K1,
483  K1,
484  I1));
485  }
486  }
487  else
488  {
491  max_lds_align);
492  }
493  }();
494 
495  return b_block_desc_b_k0_n_k1;
496  }
497 
498  __host__ __device__ static constexpr index_t GetSharedMemoryNumberOfByte()
499  {
500  constexpr auto max_lds_align = K1;
501 
502  // A matrix in LDS memory, dst of blockwise copy
503  constexpr auto a_b_k0_m_k1_block_desc = GetABlockDescriptor_Batch_K0PerBlock_MPerBlock_K1();
504 
505  // B matrix in LDS memory, dst of blockwise copy
506  constexpr auto b_b_k0_n_k1_block_desc = GetBBlockDescriptor_Batch_K0PerBlock_NPerBlock_K1();
507 
508  // LDS allocation for A and B: be careful of alignment
509  constexpr auto a_block_space_size = math::integer_least_multiple(
510  a_b_k0_m_k1_block_desc.GetElementSpaceSize(), max_lds_align);
511 
512  constexpr auto b_block_space_size = math::integer_least_multiple(
513  b_b_k0_n_k1_block_desc.GetElementSpaceSize(), max_lds_align);
514 
515  constexpr auto c_block_size =
516  GetCBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock().GetElementSpaceSize();
517 
518  return math::max((a_block_space_size * sizeof(FloatAAdjusted) +
519  b_block_space_size * sizeof(FloatBAdjusted)),
520  c_block_size * sizeof(FloatC));
521  }
522 
523  // block_id to matrix tile idx (m0, n0) mapping are controlled by {M01, N01}
524  template <typename Block2CTileMap>
525  __host__ __device__ static constexpr bool
526  CheckValidity(const AGridDesc_B_K0_M_K1& a_b_k0_m_k1_grid_desc,
527  const BGridDesc_B_K0_N_K1& b_b_k0_n_k1_grid_desc,
528  const CMNGridDesc& c_m_n_grid_desc,
529  const Block2CTileMap& block_2_ctile_map)
530  {
531  static_assert(is_known_at_compile_time<remove_cv_t<decltype(K1)>>::value,
532  "wrong! K1 need to be known at compile-time");
533 
534  static_assert((MPerBlock % (MPerXDL * MRepeat) == 0) &&
535  (NPerBlock % (NRepeat * NPerXDL)) == 0,
536  "Invalid tuning param!");
537 
538  const auto M = a_b_k0_m_k1_grid_desc.GetLength(I2);
539  const auto N = b_b_k0_n_k1_grid_desc.GetLength(I2);
540  const auto K0 = a_b_k0_m_k1_grid_desc.GetLength(I1);
541  const auto KBatch = a_b_k0_m_k1_grid_desc.GetLength(I0);
542 
543  // check gridwise gemm pipeline
544  const auto num_k_loop = K0 / K0PerBlock;
545 
546  if(!GridwiseGemmPipe::IsSupported(num_k_loop))
547  {
548  return false;
549  }
550 
551  if(!(M == c_m_n_grid_desc.GetLength(I0) && N == c_m_n_grid_desc.GetLength(I1) &&
552  K0 == b_b_k0_n_k1_grid_desc.GetLength(I1) &&
553  K1 == a_b_k0_m_k1_grid_desc.GetLength(I3) &&
554  K1 == b_b_k0_n_k1_grid_desc.GetLength(I3) &&
555  KBatch == b_b_k0_n_k1_grid_desc.GetLength(I0)))
556  return false;
557 
558  if(!(M % MPerBlock == 0 && N % NPerBlock == 0 && K0 % K0PerBlock == 0))
559  return false;
560 
561  if(!block_2_ctile_map.CheckValidity(c_m_n_grid_desc))
562  {
563  return false;
564  }
565 
566  // TODO: also check validity of all components (blockwise-copy, threadwise-copy, etc)
567  return true;
568  }
569 
570  __host__ __device__ static constexpr bool CalculateHasMainK0BlockLoop(index_t K0)
571  {
572  // const bool has_main_k0_block_loop = K0 > K0PerBlock;
573  const index_t num_loop = K0 / K0PerBlock;
574 
575  return GridwiseGemmPipe::CalculateHasMainLoop(num_loop);
576 
577  // return has_main_k0_block_loop;
578  }
579 
580  __host__ __device__ static constexpr auto
581  MakeCGridDesc_MBlock_MPerBlock_NBlock_NPerBlock(const CMNGridDesc& c_m_n_grid_desc)
582  {
583  const auto M = c_m_n_grid_desc.GetLength(I0);
584  const auto N = c_m_n_grid_desc.GetLength(I1);
585 
586  const auto MBlock = M / MPerBlock;
587  const auto NBlock = N / NPerBlock;
588 
590  c_m_n_grid_desc,
595  }
596 
597  // return block_id to C matrix tile idx (m0, n0) mapping
598  __host__ __device__ static constexpr auto MakeCBlockClusterAdaptor(
599  const CMNGridDesc& c_m_n_grid_desc, index_t M01, index_t N01, index_t KBatch)
600  {
602  c_m_n_grid_desc, M01, N01, KBatch);
603  }
604 
605  __host__ __device__ static constexpr auto
607  {
608  constexpr index_t MWave = MPerBlock / (MRepeat * MPerXDL);
609  constexpr index_t NWave = NPerBlock / (NRepeat * NPerXDL);
610 
612  make_tuple(I1,
614  I1,
616  }
617 
619  decltype(MakeCGridDesc_MBlock_MPerBlock_NBlock_NPerBlock(CMNGridDesc{}));
620  using CBlockClusterAdaptor = decltype(MakeCBlockClusterAdaptor(CMNGridDesc{}, 1, 1, 1));
621 
622  template <bool HasMainKBlockLoop>
623  __device__ static void Run(const FloatA* __restrict__ p_a_grid,
624  const FloatB* __restrict__ p_b_grid,
625  FloatC* __restrict__ p_c_grid,
626  void* __restrict__ p_shared,
627  const AGridDesc_B_K0_M_K1& a_b_k0_m_k1_grid_desc,
628  const BGridDesc_B_K0_N_K1& b_b_k0_n_k1_grid_desc,
630  c_grid_desc_mblock_mperblock_nblock_nperblock,
631  const AElementwiseOperation& a_element_op,
632  const BElementwiseOperation& b_element_op,
633  const CElementwiseOperation& c_element_op,
634  const CBlockClusterAdaptor& c_block_cluster_adaptor)
635  {
636  const auto a_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
637  p_a_grid, a_b_k0_m_k1_grid_desc.GetElementSpaceSize());
638  const auto b_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
639  p_b_grid, b_b_k0_n_k1_grid_desc.GetElementSpaceSize());
640  auto c_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
641  p_c_grid, c_grid_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
642 
643  const auto K0 = a_b_k0_m_k1_grid_desc.GetLength(I1);
644 
645  // divide block work by [M, N]
646  const auto block_work_idx =
647  c_block_cluster_adaptor.CalculateBottomIndex(make_multi_index(get_block_1d_id()));
648 
649  const index_t k_batch_id = block_work_idx[I0];
650 
651  if(!c_block_cluster_adaptor.ValidCTileIndex(
652  make_tuple(block_work_idx[I1], block_work_idx[I2]),
653  make_tuple(c_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I0),
654  c_grid_desc_mblock_mperblock_nblock_nperblock.GetLength(I2))))
655  {
656  return;
657  }
658 
659  // HACK: this force m/n_block_data_idx_on_grid into SGPR
660  const index_t m_block_data_idx_on_grid =
661  __builtin_amdgcn_readfirstlane(block_work_idx[I1] * MPerBlock);
662 
663  const index_t n_block_data_idx_on_grid =
664  __builtin_amdgcn_readfirstlane(block_work_idx[I2] * NPerBlock);
665 
666  // lds max alignment
667  constexpr auto max_lds_align = K1;
668 
669  // A matrix in LDS memory, dst of blockwise copy
670  constexpr auto a_k0_m_k1_block_desc = GetABlockDescriptor_K0PerBlock_MPerBlock_K1();
671 
672  constexpr auto a_b_k0_m_k1_block_desc = GetABlockDescriptor_Batch_K0PerBlock_MPerBlock_K1();
673  // B matrix in LDS memory, dst of blockwise copy
674  constexpr auto b_k0_n_k1_block_desc = GetBBlockDescriptor_K0PerBlock_NPerBlock_K1();
675 
676  constexpr auto b_b_k0_n_k1_block_desc = GetBBlockDescriptor_Batch_K0PerBlock_NPerBlock_K1();
677  // A matrix blockwise copy
678  auto a_blockwise_copy =
680  AElementwiseOperation,
682  InMemoryDataOperationEnum::Set,
684  ABlockTransferThreadClusterLengths_K0_M_K1,
685  ABlockTransferThreadClusterArrangeOrder,
686  FloatA,
688  decltype(a_b_k0_m_k1_grid_desc),
689  decltype(a_b_k0_m_k1_block_desc),
690  ABlockTransferSrcAccessOrder,
692  ABlockTransferSrcVectorDim,
693  3,
694  ABlockTransferSrcScalarPerVector,
695  ABlockTransferDstScalarPerVector_K1,
696  1,
697  1,
698  AThreadTransferSrcResetCoordinateAfterRun,
699  true>(
700  a_b_k0_m_k1_grid_desc,
701  make_multi_index(k_batch_id, 0, m_block_data_idx_on_grid, 0),
702  a_element_op,
703  a_b_k0_m_k1_block_desc,
704  make_multi_index(0, 0, 0, 0),
706 
707  // B matrix blockwise copy
708  auto b_blockwise_copy =
710  BElementwiseOperation,
712  InMemoryDataOperationEnum::Set,
714  BBlockTransferThreadClusterLengths_K0_N_K1,
715  BBlockTransferThreadClusterArrangeOrder,
716  FloatB,
718  decltype(b_b_k0_n_k1_grid_desc),
719  decltype(b_b_k0_n_k1_block_desc),
720  BBlockTransferSrcAccessOrder,
722  BBlockTransferSrcVectorDim,
723  3,
724  BBlockTransferSrcScalarPerVector,
725  BBlockTransferDstScalarPerVector_K1,
726  1,
727  1,
728  BThreadTransferSrcResetCoordinateAfterRun,
729  true>(
730  b_b_k0_n_k1_grid_desc,
731  make_multi_index(k_batch_id, 0, n_block_data_idx_on_grid, 0),
732  b_element_op,
733  b_b_k0_n_k1_block_desc,
734  make_multi_index(0, 0, 0, 0),
736 
737  // GEMM definition
738  // c_mtx += transpose(a_mtx) * b_mtx
739  // a_mtx[K0PerBlock, MPerBlock] is in LDS
740  // b_mtx[K0PerBlock, NPerBlock] is in LDS
741  // c_mtx[MPerBlock, NPerBlock] is distributed among threads, and saved in
742  // register
743  // sanity check
744 
745  constexpr index_t KPack =
746  math::max(K1,
748  .k_per_blk);
749 
750  auto blockwise_gemm =
754  FloatAcc,
755  decltype(a_k0_m_k1_block_desc),
756  decltype(b_k0_n_k1_block_desc),
757  MPerXDL,
758  NPerXDL,
759  MRepeat,
760  NRepeat,
761  KPack>{};
762 
763  auto c_thread_buf = blockwise_gemm.GetCThreadBuffer();
764 
765  // LDS allocation for A and B: be careful of alignment
766  constexpr auto a_block_space_size =
767  math::integer_least_multiple(a_k0_m_k1_block_desc.GetElementSpaceSize(), max_lds_align);
768 
769  constexpr auto a_block_slice_copy_step = make_multi_index(0, K0PerBlock, 0, 0);
770  constexpr auto b_block_slice_copy_step = make_multi_index(0, K0PerBlock, 0, 0);
771 
772  auto a_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
773  static_cast<FloatAAdjusted*>(p_shared), a_k0_m_k1_block_desc.GetElementSpaceSize());
774 
775  auto b_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
776  static_cast<FloatBAdjusted*>(p_shared) + a_block_space_size,
777  b_k0_n_k1_block_desc.GetElementSpaceSize());
778 
779  // gridwise GEMM pipeline
780  const index_t K0BlockMainLoop = __builtin_amdgcn_readfirstlane(K0 / K0PerBlock);
781 
782  GridwiseGemmPipe::template Run<HasMainKBlockLoop>(a_b_k0_m_k1_grid_desc,
783  a_b_k0_m_k1_block_desc,
784  a_blockwise_copy,
785  a_grid_buf,
786  a_block_buf,
787  a_block_slice_copy_step,
788  b_b_k0_n_k1_grid_desc,
789  b_b_k0_n_k1_block_desc,
790  b_blockwise_copy,
791  b_grid_buf,
792  b_block_buf,
793  b_block_slice_copy_step,
794  blockwise_gemm,
795  c_thread_buf,
796  K0BlockMainLoop);
797 
798  // output: register to global memory
799  {
800  constexpr index_t MWave = MPerBlock / (MRepeat * MPerXDL);
801  constexpr index_t NWave = NPerBlock / (NRepeat * NPerXDL);
802 
803  constexpr auto c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc =
804  blockwise_gemm.GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
805 
806  constexpr auto c_m0_n0_m1_n1_m2_m3_m4_n2_thread_desc =
807  blockwise_gemm.GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
808 
809  constexpr auto M0 = c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc.GetLength(I0);
810  constexpr auto N0 = c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc.GetLength(I1);
811  constexpr auto M1 = c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc.GetLength(I2);
812  constexpr auto N1 = c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc.GetLength(I3);
813  constexpr auto M2 = c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc.GetLength(I4);
814  constexpr auto M3 = c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc.GetLength(I5);
815  constexpr auto M4 = c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc.GetLength(I6);
816  constexpr auto N2 = c_m0_n0_m1_n1_m2_m3_m4_n2_block_desc.GetLength(I7);
817 
818  constexpr auto c_block_desc_mblock_mperblock_nblock_nperblock =
819  GetCBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock();
820 
821  auto c_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
822  static_cast<FloatC*>(p_shared),
823  c_block_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
824 
825  static_assert(M1 == MWave, "");
826  static_assert(N1 == NWave, "");
827  static_assert(M2 * M3 * M4 == MPerXDL, "");
828  static_assert(N2 == NPerXDL, "");
829 
830  constexpr auto c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2 = transform_tensor_descriptor(
831  c_block_desc_mblock_mperblock_nblock_nperblock,
832  make_tuple(
833  make_freeze_transform(I0), // freeze mblock
834  make_unmerge_transform(make_tuple(CShuffleMRepeatPerShuffle,
835  M1,
836  M2,
837  M3,
838  M4)), // M1 = MWave, M2 * M3 * M4 = MPerXDL
839  make_freeze_transform(I0), // freeze nblock
840  make_unmerge_transform(make_tuple(CShuffleNRepeatPerShuffle,
841  N1,
842  N2))), // M1 = MWave, M2 * M3 * M4 = MPerXDL
844  make_tuple(
846 
847  // calculate origin of thread output tensor on global memory
848  // blockwise GEMM c matrix starting index
849  const auto c_thread_mtx_on_block =
850  blockwise_gemm.CalculateCThreadOriginDataIndex(I0, I0, I0, I0);
851 
852  const index_t m_thread_data_on_block = c_thread_mtx_on_block[I0];
853  const index_t n_thread_data_on_block = c_thread_mtx_on_block[I1];
854 
855  const auto m_thread_data_on_block_to_m0_m1_m2_m3_m4_adaptor =
857  make_tuple(make_merge_transform(make_tuple(M0, M1, M2, M3, M4))),
860 
861  const auto m_thread_data_on_block_idx =
862  m_thread_data_on_block_to_m0_m1_m2_m3_m4_adaptor.CalculateBottomIndex(
863  make_multi_index(m_thread_data_on_block));
864 
865  const auto n_thread_data_on_block_to_n0_n1_n2_adaptor =
870 
871  const auto n_thread_data_on_block_idx =
872  n_thread_data_on_block_to_n0_n1_n2_adaptor.CalculateBottomIndex(
873  make_multi_index(n_thread_data_on_block));
874 
875  // VGPR to LDS
876  auto c_thread_copy_vgpr_to_lds =
878  FloatC,
879  decltype(c_m0_n0_m1_n1_m2_m3_m4_n2_thread_desc),
880  decltype(c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2),
882  Sequence<CShuffleMRepeatPerShuffle,
883  CShuffleNRepeatPerShuffle,
884  I1,
885  I1,
886  M2,
887  I1,
888  M4,
889  I1>,
891  7,
892  1,
893  InMemoryDataOperationEnum::Set,
894  1,
895  true>{
896  c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2,
898  0,
899  m_thread_data_on_block_idx[I1],
900  n_thread_data_on_block_idx[I1],
901  m_thread_data_on_block_idx[I2],
902  m_thread_data_on_block_idx[I3],
903  m_thread_data_on_block_idx[I4],
904  n_thread_data_on_block_idx[I2]),
906 
907  // LDS to global
908  auto c_block_copy_lds_to_global = ThreadGroupTensorSliceTransfer_v6r1<
909  ThisThreadBlock, // index_t BlockSize,
910  CElementwiseOperation, // ElementwiseOperation,
911  CGlobalMemoryDataOperation, // DstInMemOp,
912  Sequence<1,
913  CShuffleMRepeatPerShuffle * MWave * MPerXDL,
914  1,
915  CShuffleNRepeatPerShuffle * NWave * NPerXDL>, // BlockSliceLengths,
916  CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
917  Sequence<0, 1, 2, 3>, // typename ThreadClusterArrangeOrder,
918  FloatC, // typename SrcData,
919  FloatC, // typename DstData,
920  decltype(c_block_desc_mblock_mperblock_nblock_nperblock),
921  decltype(c_grid_desc_mblock_mperblock_nblock_nperblock),
922  Sequence<0, 1, 2, 3>, // typename DimAccessOrder,
923  3, // index_t VectorDim,
924  CBlockTransferScalarPerVector_NWaveNPerXDL, // index_t ScalarPerVector,
925  true, // bool ThreadTransferSrcResetCoordinateAfterRun,
926  false> // bool ThreadTransferDstResetCoordinateAfterRun
927  {c_block_desc_mblock_mperblock_nblock_nperblock,
928  make_multi_index(0, 0, 0, 0),
929  c_grid_desc_mblock_mperblock_nblock_nperblock,
930  make_multi_index(block_work_idx[I1], 0, block_work_idx[I2], 0),
931  c_element_op};
932 
933  constexpr auto mxdlperwave_forward_step =
934  make_multi_index(0, CShuffleMRepeatPerShuffle * MWave * MPerXDL, 0, 0);
935  constexpr auto nxdlperwave_forward_step =
936  make_multi_index(0, 0, 0, CShuffleNRepeatPerShuffle * NWave * NPerXDL);
937  constexpr auto nxdlperwave_backward_step =
938  make_multi_index(0, 0, 0, -CShuffleNRepeatPerShuffle * NWave * NPerXDL);
939 
940  static_for<0, MRepeat, CShuffleMRepeatPerShuffle>{}([&](auto mxdlperwave_iter) {
941  constexpr auto mxdlperwave = mxdlperwave_iter;
942 
943  static_for<0, NRepeat, CShuffleNRepeatPerShuffle>{}([&](auto nxdlperwave_iter) {
944  constexpr bool nxdlperwave_forward_sweep =
945  (mxdlperwave % (2 * CShuffleMRepeatPerShuffle) == 0);
946 
947  constexpr index_t nxdlperwave_value =
948  nxdlperwave_forward_sweep
949  ? nxdlperwave_iter
950  : (NRepeat - nxdlperwave_iter - CShuffleNRepeatPerShuffle);
951 
952  constexpr auto nxdlperwave = Number<nxdlperwave_value>{};
953 
954  // make sure it's safe to do ds_write
955  block_sync_lds();
956 
957  // VGPR to LDS
958  c_thread_copy_vgpr_to_lds.Run(
959  c_m0_n0_m1_n1_m2_m3_m4_n2_thread_desc,
960  make_tuple(mxdlperwave, nxdlperwave, I0, I0, I0, I0, I0, I0),
961  c_thread_buf,
962  c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2,
963  c_block_buf);
964 
965  // make sure it's safe to do ds_read
966  block_sync_lds();
967 
968  // LDS to global
969  c_block_copy_lds_to_global.Run(c_block_desc_mblock_mperblock_nblock_nperblock,
970  c_block_buf,
971  c_grid_desc_mblock_mperblock_nblock_nperblock,
972  c_grid_buf);
973 
974  // move on nxdlperwave dimension
975  if constexpr(nxdlperwave_forward_sweep &&
976  (nxdlperwave < NRepeat - CShuffleNRepeatPerShuffle))
977  {
978  c_block_copy_lds_to_global.MoveDstSliceWindow(
979  c_grid_desc_mblock_mperblock_nblock_nperblock,
980  nxdlperwave_forward_step);
981  }
982  else if constexpr((!nxdlperwave_forward_sweep) && (nxdlperwave > 0))
983  {
984  c_block_copy_lds_to_global.MoveDstSliceWindow(
985  c_grid_desc_mblock_mperblock_nblock_nperblock,
986  nxdlperwave_backward_step);
987  }
988  });
989 
990  // move on mxdlperwave dimension
991  if constexpr(mxdlperwave < MRepeat - CShuffleMRepeatPerShuffle)
992  {
993  c_block_copy_lds_to_global.MoveDstSliceWindow(
994  c_grid_desc_mblock_mperblock_nblock_nperblock, mxdlperwave_forward_step);
995  }
996  });
997  }
998  }
999 }; // namespace ck
1000 
1001 } // namespace ck
#define CK_MIN_BLOCK_PER_CU
Definition: ck.hpp:34
#define CK_MAX_THREAD_PER_BLOCK
Definition: ck.hpp:33
__host__ constexpr __device__ auto integer_least_multiple(X x, Y y)
Definition: math.hpp:78
__host__ constexpr __device__ T max(T x)
Definition: math.hpp:84
__host__ __device__ multiplies() -> multiplies< void, void >
FIXME: create macro to replace 'host device' and nothing more.
Definition: ck.hpp:264
__host__ constexpr __device__ auto make_multi_index(Xs &&... xs)
Definition: array_multi_index.hpp:15
__host__ constexpr __device__ auto make_naive_tensor_descriptor(const Tuple< Lengths... > &lengths, const Tuple< Strides... > &strides)
Definition: tensor_descriptor_helper.hpp:49
__global__ void kernel_gemm_xdlops_bwd_weight(const FloatA *__restrict__ p_a_grid, const FloatB *__restrict__ p_b_grid, FloatC *__restrict__ p_c_grid, const AGridDesc_B_K0_M_K1 a_b_k0_m_k1_grid_desc, const BGridDesc_B_K0_N_K1 b_b_k0_n_k1_grid_desc, const CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock c_grid_desc_mblock_mperblock_nblock_nperblock, const AElementwiseOperation a_element_op, const BElementwiseOperation b_element_op, const CElementwiseOperation c_element_op, const CBlockClusterAdaptor c_block_cluster_adaptor)
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:157
InMemoryDataOperationEnum
Definition: ck.hpp:267
__host__ constexpr __device__ auto make_naive_tensor_descriptor_packed(const Tuple< Lengths... > &lengths)
Definition: tensor_descriptor_helper.hpp:101
__host__ constexpr __device__ auto make_merge_transform(const LowLengths &low_lengths)
Definition: multi_index_transform_helper.hpp:55
__host__ constexpr __device__ auto make_merge_transform_v3_division_mod(const LowLengths &low_lengths)
Definition: multi_index_transform_helper.hpp:84
__host__ constexpr __device__ auto make_naive_tensor_descriptor_aligned(const Tuple< Lengths... > &lengths, Align align)
Definition: tensor_descriptor_helper.hpp:132
__host__ constexpr __device__ auto make_single_stage_tensor_adaptor(const Transforms &transforms, LowerDimensionOldTopIdss, UpperDimensionNewTopIdss)
Definition: tensor_adaptor.hpp:429
ushort bhalf_t
Definition: data_type.hpp:24
__host__ constexpr __device__ auto make_freeze_transform(const LowerIndex &low_idx)
Definition: multi_index_transform_helper.hpp:98
constexpr detail::ignore_t ignore
Definition: ignore.hpp:20
__device__ index_t get_block_1d_id()
Definition: get_id.hpp:22
typename conditional< predicate, X, Y >::type conditional_t
Definition: functional.hpp:115
__host__ constexpr __device__ auto container_reverse_exclusive_scan(const Array< TData, NSize > &x, Reduce f, TData init)
Definition: container_helper.hpp:213
__host__ constexpr __device__ auto make_pass_through_transform(const LowLength &low_length)
Definition: multi_index_transform_helper.hpp:12
__host__ constexpr __device__ auto make_tuple(Xs &&... xs)
Definition: tuple.hpp:211
remove_cv_t< remove_reference_t< T > > remove_cvref_t
Definition: type.hpp:300
__host__ constexpr __device__ auto make_unmerge_transform(const UpLengths &up_lengths, integral_constant< bool, Use24BitIntegerCalculation >=integral_constant< bool, false >{})
Definition: multi_index_transform_helper.hpp:90
int32_t index_t
Definition: ck.hpp:289
__host__ constexpr __device__ auto container_reduce(const Container &x, Reduce reduce, Init init, Number< IBegin >=Number< 0 >{}, Number< IEnd >=Number< Container::Size()>{}, Number< IStep >=Number< 1 >{})
Definition: container_helper.hpp:111
__host__ constexpr __device__ auto transform_tensor_descriptor(const OldTensorDescriptor &old_tensor_desc, const NewTransforms &new_transforms, NewLowerDimensionOldVisibleIdss, NewUpperDimensionNewVisibleIdss)
Definition: tensor_descriptor.hpp:319
__device__ void block_sync_lds()
Definition: synchronization.hpp:10
PipelineVersion
Definition: gridwise_gemm_pipeline_selector.hpp:17
__host__ __device__ void print_multi_index(const Tuple< Xs... > &x)
Definition: statically_indexed_array_multi_index.hpp:147
typename remove_cv< T >::type remove_cv_t
Definition: type.hpp:298
__host__ constexpr __device__ auto make_merge_transform_v4_no_carry(const LowLengths &low_lengths)
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:136
Definition: array.hpp:14
Definition: block_to_ctile_map.hpp:718
Definition: blockwise_gemm_smfmac_xdlops.hpp:44
__host__ constexpr __device__ auto & GetCThreadBuffer()
Definition: blockwise_gemm_smfmac_xdlops.hpp:79
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:251
remove_cvref_t< decltype(GridwiseGemmPipeline_Selector< PipelineVer, NumGemmKPrefetchStage >())> GridwiseGemmPipe
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:267
__host__ static constexpr __device__ auto GetBBlockDescriptor_K0PerBlock_NPerBlock_K1()
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:396
ComputeTypeB FloatBAdjusted
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:281
ThisThreadBlock< BlockSize > ThisThreadBlock
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:264
__host__ static constexpr __device__ index_t GetSharedMemoryNumberOfByte()
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:498
decltype(MakeCGridDesc_MBlock_MPerBlock_NBlock_NPerBlock(CMNGridDesc{})) CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:619
__host__ static constexpr __device__ auto GetABlockDescriptor_K0PerBlock_MPerBlock_K1()
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:294
ComputeTypeA FloatAAdjusted
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:280
__host__ static constexpr __device__ auto GetABlockDescriptor_Batch_K0PerBlock_MPerBlock_K1()
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:340
__host__ static constexpr __device__ auto GetCBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock()
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:606
__host__ static constexpr __device__ bool CalculateHasMainK0BlockLoop(index_t K0)
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:570
__host__ static constexpr __device__ auto MakeCBlockClusterAdaptor(const CMNGridDesc &c_m_n_grid_desc, index_t M01, index_t N01, index_t KBatch)
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:598
static __device__ void Run(const FloatA *__restrict__ p_a_grid, const FloatB *__restrict__ p_b_grid, FloatC *__restrict__ p_c_grid, void *__restrict__ p_shared, const AGridDesc_B_K0_M_K1 &a_b_k0_m_k1_grid_desc, const BGridDesc_B_K0_N_K1 &b_b_k0_n_k1_grid_desc, const CGridDesc_MBlock_MPerBlock_NBlock_NPerBlock &c_grid_desc_mblock_mperblock_nblock_nperblock, const AElementwiseOperation &a_element_op, const BElementwiseOperation &b_element_op, const CElementwiseOperation &c_element_op, const CBlockClusterAdaptor &c_block_cluster_adaptor)
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:623
__host__ static constexpr __device__ bool CheckValidity(const AGridDesc_B_K0_M_K1 &a_b_k0_m_k1_grid_desc, const BGridDesc_B_K0_N_K1 &b_b_k0_n_k1_grid_desc, const CMNGridDesc &c_m_n_grid_desc, const Block2CTileMap &block_2_ctile_map)
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:526
__host__ static constexpr __device__ auto MakeCGridDesc_MBlock_MPerBlock_NBlock_NPerBlock(const CMNGridDesc &c_m_n_grid_desc)
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:581
decltype(MakeCBlockClusterAdaptor(CMNGridDesc{}, 1, 1, 1)) CBlockClusterAdaptor
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:620
__host__ static constexpr __device__ auto GetBBlockDescriptor_Batch_K0PerBlock_NPerBlock_K1()
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:442
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:25
__host__ constexpr __device__ Merge_v4_no_carry(const LowLengths &low_lengths)
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:43
LowLengthsScan low_lengths_scan_
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:38
__host__ constexpr __device__ Merge_v4_no_carry()=default
decltype(make_tuple(container_reduce(LowLengths{}, math::multiplies{}, Number< 1 >{}))) UpLengths
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:35
__host__ static constexpr __device__ bool IsValidUpperIndexMappedToValidLowerIndex(const UpIdx &)
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:116
__host__ __device__ void UpdateLowerIndex(LowIdxDiff &idx_diff_low, const UpIdxDiff &idx_up_diff, LowIdx &idx_low, const UpIdx &idx_up_new, Number< Hack >) const
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:81
static constexpr index_t NDimLow
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:26
__host__ static constexpr __device__ index_t GetNumOfLowerDimension()
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:52
__host__ constexpr __device__ const auto & GetUpperLengths() const
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:56
__host__ constexpr __device__ void CalculateLowerIndex(LowIdx &idx_low, const UpIdx &idx_up) const
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:59
__host__ static constexpr __device__ bool IsKnownAtCompileTime()
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:107
__host__ static constexpr __device__ bool IsLinearTransform()
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:100
UpLengths up_lengths_
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:39
decltype(container_reverse_exclusive_scan(LowLengths{}, math::multiplies{}, Number< 1 >{})) LowLengthsScan
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:32
__host__ static constexpr __device__ index_t GetNumOfUpperDimension()
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:54
__host__ static constexpr __device__ bool IsValidUpperIndexAlwaysMappedToValidLowerIndex()
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:102
LowLengths low_lengths_
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:37
__host__ __device__ void Print() const
Definition: gridwise_gemm_xdlops_bwd_weight.hpp:121
Definition: xdlops_gemm.hpp:886
Definition: sequence.hpp:43
Blockwise data transfer.
Definition: thread_group_tensor_slice_transfer_v4r1.hpp:46
Definition: thread_group_tensor_slice_transfer_v6r1.hpp:34
Definition: threadwise_tensor_slice_transfer.hpp:39
Definition: integral_constant.hpp:10
Definition: is_known_at_compile_time.hpp:14
Definition: math.hpp:34
Definition: functional2.hpp:31
Definition: unary_element_wise_operation.hpp:241