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blockwise_gemm_pipeline_xdlops_v5.hpp

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1 // SPDX-License-Identifier: MIT

2 // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.

3 

4 #pragma once

5 

6 #include "ck/tensor_operation/gpu/block/blockwise_gemm_pipeline_xdlops_base.hpp"

7 

8 namespace ck {

9 

10 // Compute optimized pipeline

11 // GlobalPrefetchStages: 3

12 // LocalPreFillStages: 1

13 // LocalPreFetchStages: 1

14 // LocalSharedMemoryBuffer: 2

15 

16 template <BlockGemmPipelineScheduler BlkGemmPipelineVer,

17  index_t BlockSize,

18  typename ADataType,

19  typename BDataType,

20  typename ComputeDataType,

21  typename AccDataType,

22  typename ATileDesc,

23  typename BTileDesc,

24  typename AMmaTileDesc,

25  typename BMmaTileDesc,

26  index_t ABlockTransferSrcScalarPerVector,

27  index_t BBlockTransferSrcScalarPerVector,

28  index_t MPerBlock,

29  index_t NPerBlock,

30  index_t KPerBlock,

31  index_t MPerXDL,

32  index_t NPerXDL,

33  index_t MRepeat,

34  index_t NRepeat,

35  index_t KPacks>

36 struct BlockwiseGemmXdlops_pipeline_v5

37 {

38 };

39 

40 template <index_t BlockSize,

41  typename ADataType,

42  typename BDataType,

43  typename ComputeDataType,

44  typename AccDataType,

45  typename ATileDesc,

46  typename BTileDesc,

47  typename AMmaTileDesc,

48  typename BMmaTileDesc,

49  index_t ABlockTransferSrcScalarPerVector,

50  index_t BBlockTransferSrcScalarPerVector,

51  index_t MPerBlock,

52  index_t NPerBlock,

53  index_t KPerBlock,

54  index_t MPerXDL,

55  index_t NPerXDL,

56  index_t MRepeat,

57  index_t NRepeat,

58  index_t KPack

59  // ,bool TransposeC //disable transposec right now...

60  >

61 struct BlockwiseGemmXdlops_pipeline_v5<BlockGemmPipelineScheduler::Intrawave,

62  BlockSize,

63  ADataType,

64  BDataType,

65  ComputeDataType,

66  AccDataType,

67  ATileDesc,

68  BTileDesc,

69  AMmaTileDesc,

70  BMmaTileDesc,

71  ABlockTransferSrcScalarPerVector,

72  BBlockTransferSrcScalarPerVector,

73  MPerBlock,

74  NPerBlock,

75  KPerBlock,

76  MPerXDL,

77  NPerXDL,

78  MRepeat,

79  NRepeat,

80  KPack>

81  : BlockwiseGemmXdlops_pipeline_base<BlockSize,

82  ADataType,

83  BDataType,

84  ComputeDataType,

85  AccDataType,

86  ATileDesc,

87  BTileDesc,

88  AMmaTileDesc,

89  BMmaTileDesc,

90  ABlockTransferSrcScalarPerVector,

91  BBlockTransferSrcScalarPerVector,

92  MPerBlock,

93  NPerBlock,

94  KPerBlock,

95  MPerXDL,

96  NPerXDL,

97  MRepeat,

98  NRepeat,

99  KPack>

100 

101 {

102  using Base = BlockwiseGemmXdlops_pipeline_base<BlockSize,

103  ADataType,

104  BDataType,

105  ComputeDataType,

106  AccDataType,

107  ATileDesc,

108  BTileDesc,

109  AMmaTileDesc,

110  BMmaTileDesc,

111  ABlockTransferSrcScalarPerVector,

112  BBlockTransferSrcScalarPerVector,

113  MPerBlock,

114  NPerBlock,

115  KPerBlock,

116  MPerXDL,

117  NPerXDL,

118  MRepeat,

119  NRepeat,

120  KPack>;

121  using Base::A_K1;

122  using Base::B_K1;

123  using Base::I0;

124  using Base::I1;

125  using Base::KRepeat;

126  using Base::xdlops_gemm;

127  using typename Base::HotLoopInstList;

128 

129  using Base::CalculateCThreadOriginDataIndex;

130  using Base::CalculateCThreadOriginDataIndex8D;

131  using Base::GetCBlockDescriptor_G_M0_N0_M1_N1_M2_M3_M4_N2;

132  using Base::GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2;

133  using Base::GetCBlockDescriptor_M0_N0_M1_N1_M2_N2_N3_N4;

134  using Base::GetCThreadBuffer;

135  using Base::GetCThreadDescriptor_G_M0_N0_M1_N1_M2_M3_M4_N2;

136  using Base::GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2;

137  using Base::GetCThreadDescriptor_M0_N0_M1_N1_M2_N2_N3_N4;

138  using Base::MakeCGridDescriptor_G_M0_N0_M1_N1_M2_M3_M4_N2;

139  using Base::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2;

140 

141  using Base::a_block_desc_m0_m1_m2_k;

142  using Base::b_block_desc_n0_n1_n2_k;

143 

144  using Base::AMmaKStride;

145  using Base::BMmaKStride;

146 

147  static constexpr index_t PrefetchStages = 3;

148  static constexpr index_t PrefillStages = 1;

149  static constexpr index_t GlobalBufferNum = 2;

150  static constexpr index_t HotloopUnroll = 2;

151 

152  __host__ static constexpr bool BlockHasHotloop(index_t num_loop)

153  {

154  return num_loop > PrefetchStages;

155  }

156 

157  __host__ static constexpr TailNumber BlockLoopTailNum(index_t num_loop)

158  {

159  if(num_loop % HotloopUnroll == 1)

160  {

161  return TailNumber::Odd;

162  }

163  else

164  {

165  return TailNumber::Even;

166  }

167  }

168 

169  __device__ static constexpr auto HotLoopScheduler()

170  {

171  // TODO: Take data type into consideration as pipe ver 3

172  // A/B split schedule

173  // compiler is likely to use ds_read2 when instruction width smaller than 16bytes

174  constexpr auto num_ds_read_inst_a =

175  HotLoopInstList::A_LDS_Read_Width * sizeof(ADataType) == 16

176  ? HotLoopInstList::A_LDS_Read_Inst_Num

177  : HotLoopInstList::A_LDS_Read_Inst_Num / 2;

178  constexpr auto num_ds_read_inst_b =

179  HotLoopInstList::B_LDS_Read_Width * sizeof(BDataType) == 16

180  ? HotLoopInstList::B_LDS_Read_Inst_Num

181  : HotLoopInstList::B_LDS_Read_Inst_Num / 2;

182 

183  constexpr auto num_ds_write_inst_a = HotLoopInstList::A_LDS_Write_Inst_Num;

184  constexpr auto num_ds_write_inst_b = HotLoopInstList::B_LDS_Write_Inst_Num;

185 

186  constexpr auto num_buffer_load_inst_a = HotLoopInstList::A_Buffer_Load_Inst_Num;

187  constexpr auto num_buffer_load_inst_b = HotLoopInstList::B_Buffer_Load_Inst_Num;

188 

189  constexpr auto num_mfma_inst = HotLoopInstList::C_MFMA_Inst_Num;

190 

191  constexpr auto mfma_cycle = NPerXDL == 16 ? 16 : 32;

192  constexpr auto ds_read_a_issue_cycle =

193  HotLoopInstList::A_LDS_Read_Width * sizeof(ADataType) == 16 ? 8 : 4;

194  constexpr auto ds_read_b_issue_cycle =

195  HotLoopInstList::B_LDS_Read_Width * sizeof(BDataType) == 16 ? 8 : 4;

196  constexpr auto ds_read_a_mfma_rate =

197  (mfma_cycle - 4 + 2 * ds_read_a_issue_cycle - 1) / (2 * ds_read_a_issue_cycle);

198  constexpr auto ds_read_b_mfma_rate =

199  (mfma_cycle - 4 + 2 * ds_read_b_issue_cycle - 1) / (2 * ds_read_b_issue_cycle);

200 

201  constexpr auto num_dsread_stage1_a = num_ds_read_inst_a / KRepeat * (KRepeat - 1);

202  constexpr auto num_dsread_stage1_b = num_ds_read_inst_b / KRepeat * (KRepeat - 1);

203  constexpr auto num_dsread_stage3_a = num_ds_read_inst_a / KRepeat;

204  constexpr auto num_dsread_stage3_b = num_ds_read_inst_b / KRepeat;

205 

206  constexpr auto num_dsread_stage1_a_mfma =

207  (num_dsread_stage1_a + ds_read_a_mfma_rate - 1) / ds_read_a_mfma_rate;

208  constexpr auto num_dsread_stage1_b_mfma =

209  (num_dsread_stage1_b + ds_read_b_mfma_rate - 1) / ds_read_b_mfma_rate;

210  constexpr auto num_dsread_stage3_a_mfma =

211  (num_dsread_stage3_a + ds_read_a_mfma_rate - 1) / ds_read_a_mfma_rate;

212  constexpr auto num_dsread_stage3_b_mfma =

213  (num_dsread_stage3_b + ds_read_b_mfma_rate - 1) / ds_read_b_mfma_rate;

214 

215  constexpr auto num_mfma_stage2 = num_mfma_inst - num_ds_read_inst_a / ds_read_a_mfma_rate -

216  num_ds_read_inst_b / ds_read_b_mfma_rate;

217  constexpr auto num_mfma_per_issue =

218  num_mfma_stage2 / (num_buffer_load_inst_a + num_buffer_load_inst_b);

219  constexpr auto num_dswrite_per_issue_a = num_ds_write_inst_a / num_buffer_load_inst_a;

220  constexpr auto num_dswrite_per_issue_b = num_ds_write_inst_b / num_buffer_load_inst_b;

221 

222  // stage 1

223  static_for<0, num_dsread_stage1_a_mfma, 1>{}([&](auto i) {

224  ignore = i;

225  if constexpr((num_dsread_stage1_a - (i + 1) * ds_read_a_mfma_rate) >=

226  ds_read_a_mfma_rate)

227  {

228  __builtin_amdgcn_sched_group_barrier(0x100, ds_read_a_mfma_rate, 0); // DS read

229  }

230  else

231  {

232  __builtin_amdgcn_sched_group_barrier(

233  0x100,

234  num_dsread_stage1_a - (num_dsread_stage1_a_mfma - 1) * ds_read_a_mfma_rate,

235  0); // DS read

236  }

237  __builtin_amdgcn_sched_group_barrier(0x008, 1, 0); // MFMA

238  });

239  static_for<0, num_dsread_stage1_b_mfma, 1>{}([&](auto i) {

240  ignore = i;

241  if constexpr((num_dsread_stage1_b - (i + 1) * ds_read_b_mfma_rate) >=

242  ds_read_b_mfma_rate)

243  {

244  __builtin_amdgcn_sched_group_barrier(0x100, ds_read_b_mfma_rate, 0); // DS read

245  }

246  else

247  {

248  __builtin_amdgcn_sched_group_barrier(

249  0x100,

250  num_dsread_stage1_b - (num_dsread_stage1_b_mfma - 1) * ds_read_b_mfma_rate,

251  0); // DS read

252  }

253  __builtin_amdgcn_sched_group_barrier(0x008, 1, 0); // MFMA

254  });

255 

256  // stage 2

257  static_for<0, num_buffer_load_inst_a, 1>{}([&](auto i) {

258  ignore = i;

259  static_for<0, num_dswrite_per_issue_a, 1>{}([&](auto idswrite) {

260  ignore = idswrite;

261  __builtin_amdgcn_sched_group_barrier(0x200, 1, 0); // DS write

262  __builtin_amdgcn_sched_group_barrier(0x008, 1, 0); // MFMA

263  });

264  __builtin_amdgcn_sched_group_barrier(0x020, 1, 0); // VMEM read

265  __builtin_amdgcn_sched_group_barrier(

266  0x008, num_mfma_per_issue - num_dswrite_per_issue_a, 0); // MFMA

267  });

268  static_for<0, num_buffer_load_inst_b, 1>{}([&](auto i) {

269  ignore = i;

270  static_for<0, num_dswrite_per_issue_b, 1>{}([&](auto idswrite) {

271  ignore = idswrite;

272  __builtin_amdgcn_sched_group_barrier(0x200, 1, 0); // DS write

273  __builtin_amdgcn_sched_group_barrier(0x008, 1, 0); // MFMA

274  });

275  __builtin_amdgcn_sched_group_barrier(0x020, 1, 0); // VMEM read

276  __builtin_amdgcn_sched_group_barrier(

277  0x008, num_mfma_per_issue - num_dswrite_per_issue_b, 0); // MFMA

278  });

279 

280  // stage 3

281  static_for<0, num_dsread_stage3_a_mfma, 1>{}([&](auto i) {

282  ignore = i;

283  if constexpr((num_dsread_stage3_a - (i + 1) * ds_read_a_mfma_rate) >=

284  ds_read_a_mfma_rate)

285  {

286  __builtin_amdgcn_sched_group_barrier(0x100, ds_read_a_mfma_rate, 0); // DS read

287  }

288  else

289  {

290  __builtin_amdgcn_sched_group_barrier(

291  0x100,

292  num_dsread_stage3_a - (num_dsread_stage3_a_mfma - 1) * ds_read_a_mfma_rate,

293  0); // DS read

294  }

295  __builtin_amdgcn_sched_group_barrier(0x008, 1, 0); // MFMA

296  });

297  static_for<0, num_dsread_stage3_b_mfma, 1>{}([&](auto i) {

298  ignore = i;

299  if constexpr((num_dsread_stage3_b - (i + 1) * ds_read_b_mfma_rate) >=

300  ds_read_b_mfma_rate)

301  {

302  __builtin_amdgcn_sched_group_barrier(0x100, ds_read_b_mfma_rate, 0); // DS read

303  }

304  else

305  {

306  __builtin_amdgcn_sched_group_barrier(

307  0x100,

308  num_dsread_stage3_b - (num_dsread_stage3_b_mfma - 1) * ds_read_b_mfma_rate,

309  0); // DS read

310  }

311  __builtin_amdgcn_sched_group_barrier(0x008, 1, 0); // MFMA

312  });

313 

314  // IGLP COMPILER BUG:

315  // If comment out following scheduler barrier would cause sanity fail.

316  __builtin_amdgcn_sched_barrier(0);

317  }

318 

319  template <bool HasMainLoop,

320  TailNumber TailNum,

321  typename AGridDesc,

322  typename ABlockDesc,

323  typename ABlockTransfer,

324  typename AGridBuffer,

325  typename ABlockBuffer,

326  typename ABlockTransferStep,

327  typename BGridDesc,

328  typename BBlockDesc,

329  typename BBlockTransfer,

330  typename BGridBuffer,

331  typename BBlockBuffer,

332  typename BBlockTransferStep,

333  typename CThreadBuffer>

334  __device__ void Run(const AGridDesc& a_grid_desc,

335  const ABlockDesc& a_block_desc,

336  ABlockTransfer& a_blockwise_copy,

337  const AGridBuffer& a_grid_buf,

338  ABlockBuffer& a_block_buf,

339  const ABlockTransferStep& a_block_copy_step,

340  const BGridDesc& b_grid_desc,

341  const BBlockDesc& b_block_desc,

342  BBlockTransfer& b_blockwise_copy,

343  const BGridBuffer& b_grid_buf,

344  BBlockBuffer& b_block_buf,

345  const BBlockTransferStep& b_block_copy_step,

346  CThreadBuffer& c_thread_buf,

347  index_t num_loop) const

348  {

349  auto a_thread_buf = make_static_buffer<AddressSpaceEnum::Vgpr, ComputeDataType>(

350  a_thread_desc_.GetElementSpaceSize());

351  auto b_thread_buf = make_static_buffer<AddressSpaceEnum::Vgpr, ComputeDataType>(

352  b_thread_desc_.GetElementSpaceSize());

353 

354  // Global prefetch 1

355  a_blockwise_copy.RunRead(a_grid_desc, a_grid_buf, I0);

356  b_blockwise_copy.RunRead(b_grid_desc, b_grid_buf, I0);

357 

358  a_blockwise_copy.MoveSrcSliceWindow(a_grid_desc, a_block_copy_step);

359  b_blockwise_copy.MoveSrcSliceWindow(b_grid_desc, b_block_copy_step);

360 

361  // Local prefill 1

362  a_blockwise_copy.RunWrite(a_block_desc, a_block_buf, I0);

363  b_blockwise_copy.RunWrite(b_block_desc, b_block_buf, I0);

364 

365  // Global prefetch 2

366  a_blockwise_copy.RunRead(a_grid_desc, a_grid_buf, I0);

367  b_blockwise_copy.RunRead(b_grid_desc, b_grid_buf, I0);

368 

369  a_blockwise_copy.MoveSrcSliceWindow(a_grid_desc, a_block_copy_step);

370  b_blockwise_copy.MoveSrcSliceWindow(b_grid_desc, b_block_copy_step);

371 

372  // Global prefetch 3

373  a_blockwise_copy.RunRead(a_grid_desc, a_grid_buf, I1);

374  b_blockwise_copy.RunRead(b_grid_desc, b_grid_buf, I1);

375 

376  a_blockwise_copy.MoveSrcSliceWindow(a_grid_desc, a_block_copy_step);

377  b_blockwise_copy.MoveSrcSliceWindow(b_grid_desc, b_block_copy_step);

378 

379  // Initialize C

380  c_thread_buf.Clear();

381 

382  // Local prefetch 1

383  block_sync_lds();

384  static_for<0, MRepeat, 1>{}([&](auto m0) {

385  a_thread_copy_.Run(a_block_desc_m0_m1_m2_k,

386  make_tuple(m0, I0, I0, I0),

387  a_block_buf,

388  a_thread_desc_,

389  make_tuple(m0, I0, I0, I0),

390  a_thread_buf);

391  });

392  static_for<0, NRepeat, 1>{}([&](auto n0) {

393  b_thread_copy_.Run(b_block_desc_n0_n1_n2_k,

394  make_tuple(n0, I0, I0, I0),

395  b_block_buf,

396  b_thread_desc_,

397  make_tuple(n0, I0, I0, I0),

398  b_thread_buf);

399  });

400 

401  // main body

402  if constexpr(HasMainLoop)

403  {

404  index_t i = 0;

405  do

406  {

407  auto LoopFunc = [&](auto vmem_buf) {

408  vector_type<ComputeDataType, KPack> a_thread_vec;

409  vector_type<ComputeDataType, KPack> b_thread_vec;

410 

411  static_for<0, KRepeat, 1>{}([&](auto k0) {

412  if constexpr(k0 == (KRepeat - 1))

413  {

414  block_sync_lds();

415 

416  a_blockwise_copy.RunWrite(a_block_desc, a_block_buf, vmem_buf);

417  b_blockwise_copy.RunWrite(b_block_desc, b_block_buf, vmem_buf);

418 

419  a_blockwise_copy.RunRead(a_grid_desc, a_grid_buf, vmem_buf);

420  b_blockwise_copy.RunRead(b_grid_desc, b_grid_buf, vmem_buf);

421 

422  a_blockwise_copy.MoveSrcSliceWindow(a_grid_desc, a_block_copy_step);

423  b_blockwise_copy.MoveSrcSliceWindow(b_grid_desc, b_block_copy_step);

424 

425  block_sync_lds();

426  }

427  static_for<0, MRepeat, 1>{}([&](auto m0) {

428  static_for<0, NRepeat, 1>{}([&](auto n0) {

429  static_for<0, KPack, 1>{}([&](auto ik) {

430  a_thread_vec.template AsType<ComputeDataType>()(ik) =

431  a_thread_buf[Number<a_thread_desc_.CalculateOffset(

432  make_tuple(m0, I0, I0, ik))>{}];

433  });

434  static_for<0, KPack, 1>{}([&](auto ik) {

435  b_thread_vec.template AsType<ComputeDataType>()(ik) =

436  b_thread_buf[Number<b_thread_desc_.CalculateOffset(

437  make_tuple(n0, I0, I0, ik))>{}];

438  });

439 

440  using mfma_input_type =

441  typename vector_type<ComputeDataType,

442  xdlops_gemm.K1PerXdlops>::type;

443 

444  constexpr index_t c_offset =

445  c_thread_desc_.CalculateOffset(make_tuple(m0, n0, 0));

446 

447  xdlops_gemm.Run(

448  a_thread_vec.template AsType<mfma_input_type>(),

449  b_thread_vec.template AsType<mfma_input_type>(),

450  c_thread_buf.GetVectorTypeReference(Number<c_offset>{}));

451  });

452 

453  a_thread_copy_.Run(

454  a_block_desc_m0_m1_m2_k,

455  make_tuple(m0, I0, I0, Number<(k0 + 1) % KRepeat * AMmaKStride>{}),

456  a_block_buf,

457  a_thread_desc_,

458  make_tuple(m0, I0, I0, I0),

459  a_thread_buf);

460  });

461 

462  static_for<0, NRepeat, 1>{}([&](auto n0) {

463  b_thread_copy_.Run(

464  b_block_desc_n0_n1_n2_k,

465  make_tuple(n0, I0, I0, Number<(k0 + 1) % KRepeat * BMmaKStride>{}),

466  b_block_buf,

467  b_thread_desc_,

468  make_tuple(n0, I0, I0, I0),

469  b_thread_buf);

470  });

471  });

472 

473  HotLoopScheduler();

474  };

475 

476  LoopFunc(I0);

477  LoopFunc(I1);

478 

479  i += HotloopUnroll;

480  } while(i < (num_loop - PrefetchStages));

481  }

482  // tail

483  auto ReadWriteCompFunc = [&](auto vmem_buf) {

484  vector_type<ComputeDataType, KPack> a_thread_vec;

485  vector_type<ComputeDataType, KPack> b_thread_vec;

486 

487  static_for<0, KRepeat, 1>{}([&](auto k0) {

488  if constexpr(k0 == (KRepeat - 1))

489  {

490  block_sync_lds();

491 

492  a_blockwise_copy.RunWrite(a_block_desc, a_block_buf, vmem_buf);

493  b_blockwise_copy.RunWrite(b_block_desc, b_block_buf, vmem_buf);

494 

495  block_sync_lds();

496  }

497  static_for<0, MRepeat, 1>{}([&](auto m0) {

498  static_for<0, NRepeat, 1>{}([&](auto n0) {

499  static_for<0, KPack, 1>{}([&](auto ik) {

500  a_thread_vec.template AsType<ComputeDataType>()(ik) =

501  a_thread_buf[Number<a_thread_desc_.CalculateOffset(

502  make_tuple(m0, I0, I0, ik))>{}];

503  });

504  static_for<0, KPack, 1>{}([&](auto ik) {

505  b_thread_vec.template AsType<ComputeDataType>()(ik) =

506  b_thread_buf[Number<b_thread_desc_.CalculateOffset(

507  make_tuple(n0, I0, I0, ik))>{}];

508  });

509 

510  using mfma_input_type =

511  typename vector_type<ComputeDataType, xdlops_gemm.K1PerXdlops>::type;

512 

513  constexpr index_t c_offset =

514  c_thread_desc_.CalculateOffset(make_tuple(m0, n0, 0));

515 

516  xdlops_gemm.Run(a_thread_vec.template AsType<mfma_input_type>(),

517  b_thread_vec.template AsType<mfma_input_type>(),

518  c_thread_buf.GetVectorTypeReference(Number<c_offset>{}));

519  });

520  a_thread_copy_.Run(

521  a_block_desc_m0_m1_m2_k,

522  make_tuple(m0, I0, I0, Number<(k0 + 1) % KRepeat * AMmaKStride>{}),

523  a_block_buf,

524  a_thread_desc_,

525  make_tuple(m0, I0, I0, I0),

526  a_thread_buf);

527  });

528 

529  static_for<0, NRepeat, 1>{}([&](auto n0) {

530  b_thread_copy_.Run(

531  b_block_desc_n0_n1_n2_k,

532  make_tuple(n0, I0, I0, Number<(k0 + 1) % KRepeat * BMmaKStride>{}),

533  b_block_buf,

534  b_thread_desc_,

535  make_tuple(n0, I0, I0, I0),

536  b_thread_buf);

537  });

538  });

539 

540  HotLoopScheduler();

541  };

542  auto ReadCompFunc = [&]() {

543  vector_type<ComputeDataType, KPack> a_thread_vec;

544  vector_type<ComputeDataType, KPack> b_thread_vec;

545 

546  static_for<0, KRepeat - 1, 1>{}([&](auto k0) {

547  static_for<0, MRepeat, 1>{}([&](auto m0) {

548  static_for<0, NRepeat, 1>{}([&](auto n0) {

549  static_for<0, KPack, 1>{}([&](auto ik) {

550  a_thread_vec.template AsType<ComputeDataType>()(ik) =

551  a_thread_buf[Number<a_thread_desc_.CalculateOffset(

552  make_tuple(m0, I0, I0, ik))>{}];

553  });

554  static_for<0, KPack, 1>{}([&](auto ik) {

555  b_thread_vec.template AsType<ComputeDataType>()(ik) =

556  b_thread_buf[Number<b_thread_desc_.CalculateOffset(

557  make_tuple(n0, I0, I0, ik))>{}];

558  });

559 

560  using mfma_input_type =

561  typename vector_type<ComputeDataType, xdlops_gemm.K1PerXdlops>::type;

562 

563  constexpr index_t c_offset =

564  c_thread_desc_.CalculateOffset(make_tuple(m0, n0, 0));

565 

566  xdlops_gemm.Run(a_thread_vec.template AsType<mfma_input_type>(),

567  b_thread_vec.template AsType<mfma_input_type>(),

568  c_thread_buf.GetVectorTypeReference(Number<c_offset>{}));

569  });

570 

571  a_thread_copy_.Run(

572  a_block_desc_m0_m1_m2_k,

573  make_tuple(m0, I0, I0, Number<(k0 + 1) % KRepeat * AMmaKStride>{}),

574  a_block_buf,

575  a_thread_desc_,

576  make_tuple(m0, I0, I0, I0),

577  a_thread_buf);

578  });

579 

580  static_for<0, NRepeat, 1>{}([&](auto n0) {

581  b_thread_copy_.Run(

582  b_block_desc_n0_n1_n2_k,

583  make_tuple(n0, I0, I0, Number<(k0 + 1) % KRepeat * BMmaKStride>{}),

584  b_block_buf,

585  b_thread_desc_,

586  make_tuple(n0, I0, I0, I0),

587  b_thread_buf);

588  });

589  });

590 

591  static_for<0, MRepeat, 1>{}([&](auto m0) {

592  static_for<0, NRepeat, 1>{}([&](auto n0) {

593  static_for<0, KPack, 1>{}([&](auto ik) {

594  a_thread_vec.template AsType<ComputeDataType>()(ik) = a_thread_buf

595  [Number<a_thread_desc_.CalculateOffset(make_tuple(m0, I0, I0, ik))>{}];

596  });

597  static_for<0, KPack, 1>{}([&](auto ik) {

598  b_thread_vec.template AsType<ComputeDataType>()(ik) = b_thread_buf

599  [Number<b_thread_desc_.CalculateOffset(make_tuple(n0, I0, I0, ik))>{}];

600  });

601 

602  using mfma_input_type =

603  typename vector_type<ComputeDataType, xdlops_gemm.K1PerXdlops>::type;

604 

605  constexpr index_t c_offset =

606  c_thread_desc_.CalculateOffset(make_tuple(m0, n0, 0));

607 

608  xdlops_gemm.Run(a_thread_vec.template AsType<mfma_input_type>(),

609  b_thread_vec.template AsType<mfma_input_type>(),

610  c_thread_buf.GetVectorTypeReference(Number<c_offset>{}));

611  });

612  });

613 

614  HotLoopScheduler();

615  };

616 

617  if constexpr(TailNum == TailNumber::Odd)

618  {

619  ReadWriteCompFunc(I0);

620  ReadWriteCompFunc(I1);

621  ReadCompFunc();

622  }

623  else if constexpr(TailNum == TailNumber::Even)

624  {

625  ReadWriteCompFunc(I0);

626  ReadCompFunc();

627  }

628  }

629 

630  protected:

631  // A[MRepeat, I1, I1, KPack]

632  static constexpr auto a_thread_desc_ =

633  make_naive_tensor_descriptor_packed(make_tuple(Number<MRepeat>{}, I1, I1, Number<KPack>{}));

634 

635  // B[NRepeat, N1, N2, KPack]

636  static constexpr auto b_thread_desc_ =

637  make_naive_tensor_descriptor_packed(make_tuple(Number<NRepeat>{}, I1, I1, Number<KPack>{}));

638 

639  using AThreadCopy = ThreadwiseTensorSliceTransfer_v4<ADataType,

640  ComputeDataType,

641  decltype(a_block_desc_m0_m1_m2_k),

642  decltype(a_thread_desc_),

643  Sequence<1, 1, 1, KPack>,

644  Sequence<0, 1, 2, 3>,

645  3,

646  A_K1,

647  A_K1>;

648 

649  using BThreadCopy = ThreadwiseTensorSliceTransfer_v4<BDataType,

650  ComputeDataType,

651  decltype(b_block_desc_n0_n1_n2_k),

652  decltype(b_thread_desc_),

653  Sequence<1, 1, 1, KPack>,

654  Sequence<0, 1, 2, 3>,

655  3,

656  B_K1,

657  B_K1>;

658 

659  AThreadCopy a_thread_copy_{Base::CalculateAThreadOriginDataIndex()};

660  BThreadCopy b_thread_copy_{Base::CalculateBThreadOriginDataIndex()};

661  using Base::c_thread_desc_;

662 };

663 

664 } // namespace ck

blockwise_gemm_pipeline_xdlops_base.hpp

ck

Definition: ck.hpp:264

ck::make_naive_tensor_descriptor_packed

__host__ constexpr __device__ auto make_naive_tensor_descriptor_packed(const Tuple< Lengths... > &lengths)

Definition: tensor_descriptor_helper.hpp:101

ck::TailNumber

TailNumber

Definition: blkgemmpipe_scheduler.hpp:18

ck::TailNumber::Even

@ Even

ck::TailNumber::Odd

@ Odd

ck::ignore

constexpr detail::ignore_t ignore

Definition: ignore.hpp:20

ck::BlockGemmPipelineScheduler

BlockGemmPipelineScheduler

Definition: blkgemmpipe_scheduler.hpp:12

ck::BlockGemmPipelineScheduler::Intrawave

@ Intrawave

ck::make_tuple

__host__ constexpr __device__ auto make_tuple(Xs &&... xs)

Definition: tuple.hpp:211

ck::index_t

int32_t index_t

Definition: ck.hpp:289

ck::block_sync_lds

__device__ void block_sync_lds()

Definition: synchronization.hpp:10

ck::BlockwiseGemmXdlops_pipeline_base

Definition: blockwise_gemm_pipeline_xdlops_base.hpp:35

ck::BlockwiseGemmXdlops_pipeline_hotloop_inst

Definition: blockwise_gemm_pipeline_xdlops.hpp:34

ck::BlockwiseGemmXdlops_pipeline_v5< BlockGemmPipelineScheduler::Intrawave, BlockSize, ADataType, BDataType, ComputeDataType, AccDataType, ATileDesc, BTileDesc, AMmaTileDesc, BMmaTileDesc, ABlockTransferSrcScalarPerVector, BBlockTransferSrcScalarPerVector, MPerBlock, NPerBlock, KPerBlock, MPerXDL, NPerXDL, MRepeat, NRepeat, KPack >::HotLoopScheduler

static constexpr __device__ auto HotLoopScheduler()

Definition: blockwise_gemm_pipeline_xdlops_v5.hpp:169

ck::BlockwiseGemmXdlops_pipeline_v5< BlockGemmPipelineScheduler::Intrawave, BlockSize, ADataType, BDataType, ComputeDataType, AccDataType, ATileDesc, BTileDesc, AMmaTileDesc, BMmaTileDesc, ABlockTransferSrcScalarPerVector, BBlockTransferSrcScalarPerVector, MPerBlock, NPerBlock, KPerBlock, MPerXDL, NPerXDL, MRepeat, NRepeat, KPack >::Run

__device__ void Run(const AGridDesc &a_grid_desc, const ABlockDesc &a_block_desc, ABlockTransfer &a_blockwise_copy, const AGridBuffer &a_grid_buf, ABlockBuffer &a_block_buf, const ABlockTransferStep &a_block_copy_step, const BGridDesc &b_grid_desc, const BBlockDesc &b_block_desc, BBlockTransfer &b_blockwise_copy, const BGridBuffer &b_grid_buf, BBlockBuffer &b_block_buf, const BBlockTransferStep &b_block_copy_step, CThreadBuffer &c_thread_buf, index_t num_loop) const

Definition: blockwise_gemm_pipeline_xdlops_v5.hpp:334

ck::BlockwiseGemmXdlops_pipeline_v5< BlockGemmPipelineScheduler::Intrawave, BlockSize, ADataType, BDataType, ComputeDataType, AccDataType, ATileDesc, BTileDesc, AMmaTileDesc, BMmaTileDesc, ABlockTransferSrcScalarPerVector, BBlockTransferSrcScalarPerVector, MPerBlock, NPerBlock, KPerBlock, MPerXDL, NPerXDL, MRepeat, NRepeat, KPack >::BlockLoopTailNum

static constexpr __host__ TailNumber BlockLoopTailNum(index_t num_loop)

Definition: blockwise_gemm_pipeline_xdlops_v5.hpp:157

ck::BlockwiseGemmXdlops_pipeline_v5< BlockGemmPipelineScheduler::Intrawave, BlockSize, ADataType, BDataType, ComputeDataType, AccDataType, ATileDesc, BTileDesc, AMmaTileDesc, BMmaTileDesc, ABlockTransferSrcScalarPerVector, BBlockTransferSrcScalarPerVector, MPerBlock, NPerBlock, KPerBlock, MPerXDL, NPerXDL, MRepeat, NRepeat, KPack >::BlockHasHotloop

static constexpr __host__ bool BlockHasHotloop(index_t num_loop)

Definition: blockwise_gemm_pipeline_xdlops_v5.hpp:152

ck::BlockwiseGemmXdlops_pipeline_v5

Definition: blockwise_gemm_pipeline_xdlops_v5.hpp:37

ck::Sequence

Definition: sequence.hpp:43

ck::ThreadwiseTensorSliceTransfer_v4< ADataType, ComputeDataType, decltype(a_block_desc_m0_m1_m2_k), decltype(a_thread_desc_), Sequence< 1, 1, 1, KPack >, Sequence< 0, 1, 2, 3 >, 3, A_K1, A_K1 >

ck::integral_constant

Definition: integral_constant.hpp:10

ck::static_for

Definition: functional2.hpp:31

ck::vector_type

Definition: data_type.hpp:347