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1 : /**
2 : * Copyright (c) 2025 Huawei Technologies Co., Ltd.
3 : * This program is free software, you can redistribute it and/or modify it under the terms and conditions of
4 : * CANN Open Software License Agreement Version 2.0 (the "License").
5 : * Please refer to the License for details. You may not use this file except in compliance with the License.
6 : * THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
7 : * INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
8 : * See LICENSE in the root of the software repository for the full text of the License.
9 : */
10 :
11 : #include "ccu_context_reduce_scatter_nhr1d_mem2mem.h"
12 :
13 : namespace Hccl {
14 :
15 : // 注意型号量变化
16 : constexpr uint16_t INPUT_XN_ID = 0;
17 : constexpr uint16_t TOKEN_XN_ID = 2;
18 : constexpr uint16_t CKE_IDX_0 = 0;
19 : constexpr uint16_t CKE_IDX_1 = 1;
20 : constexpr uint16_t CKE_IDX_2 = 2;
21 : constexpr uint16_t CKE_IDX_3 = 3;
22 : constexpr uint16_t CKE_IDX_4 = 4;
23 : constexpr uint16_t FST_AXIS_ID = 0;
24 : constexpr uint16_t SEC_AXIS_ID = 1;
25 : constexpr uint16_t RANK_NUM_PER_CKE = 16; // 本rank给远端置位时应当写的CKE，16个对端一个CKE
26 : constexpr uint16_t LINK_SIZE = 2;
27 :
28 0 : CcuContextReduceScatterNHR1DMem2Mem::CcuContextReduceScatterNHR1DMem2Mem(
29 0 : const CcuCtxArg& arg, const std::vector<CcuTransport*>& transports, const CcuTransportGroup& group)
30 0 : : CcuContextAlgBase(arg, transports, group)
31 : {
32 0 : const CcuCtxArgReduceScatterNHR1D* ctxArg = dynamic_cast<const CcuCtxArgReduceScatterNHR1D*>(&arg);
33 0 : rankId_ = ctxArg->rankId_;
34 0 : axisId_ = ctxArg->axisId_;
35 0 : dimSize_ = ctxArg->dimSize_[0];
36 0 : localAxisSignalName_ = "CcuContextReduceScatterNHR1DDieSync_" + std::to_string(axisId_);
37 0 : anotherAxisSignalName_ = "CcuContextReduceScatterNHR1DDieSync_" + std::to_string(1 - axisId_);
38 0 : stepInfoVector_ = ctxArg->stepInfoVector_;
39 0 : indexMap_ = ctxArg->indexMap_;
40 0 : localSize_ = indexMap_.size();
41 0 : myRankIdx_ = indexMap_.size();
42 0 : reduceOp_ = ctxArg->op_.reduceOp;
43 0 : dataType_ = ctxArg->op_.dataType;
44 0 : outputDataType_ = ctxArg->op_.outputDataType;
45 0 : linkNum_ = ctxArg->linkNum_;
46 0 : if (outputDataType_ == DataType::INVALID) {
47 0 : outputDataType_ = dataType_;
48 0 : HCCL_INFO(
49 : "[CcuContextReduceScatterNHR1DMem2Mem] outputDataType is [INVALID], set outputDataType to[%s]",
50 : outputDataType_.Describe().c_str());
51 : }
52 0 : signalNum_ = (dimSize_ + RANK_NUM_PER_CKE - 1) / RANK_NUM_PER_CKE; // 每个CKE有16个bit
53 0 : HCCL_INFO(
54 : "[CcuContextReduceScatterNHR1DMem2Mem] CtxArg: rankId_[%u], axisId_[%u], dimSize_[%u], localSize_[%u], "
55 : "dataType[%s], outputDataType[%s], reduceOp[%s], signalNum_[%u]",
56 : rankId_, axisId_, dimSize_, localSize_, dataType_.Describe().c_str(), outputDataType_.Describe().c_str(),
57 : reduceOp_.Describe().c_str(), signalNum_);
58 0 : }
59 :
60 0 : void CcuContextReduceScatterNHR1DMem2Mem::LoadArgs()
61 : {
62 0 : Load(input_[myRankIdx_]);
63 0 : Load(output_);
64 0 : Load(token_[myRankIdx_]);
65 0 : Load(die0Size_);
66 0 : Load(die1Size_);
67 0 : Load(inputSliceStride_);
68 0 : Load(outputSliceStride_);
69 0 : Load(inputRepeatStride_);
70 0 : Load(outputRepeatStride_);
71 0 : Load(repeatNumVar_);
72 0 : Load(isBottom_);
73 0 : repeatNumVarTemp_ = repeatNumVar_;
74 0 : HCCL_INFO("[CcuContextReduceScatterNHR1DMem2Mem] LoadArgs run finished");
75 0 : }
76 :
77 0 : void CcuContextReduceScatterNHR1DMem2Mem::InitResources()
78 : {
79 0 : die0Size_ = CreateVariable();
80 0 : die1Size_ = CreateVariable();
81 0 : sliceSize_ = CreateVariable();
82 0 : inputSliceStride_ = CreateVariable();
83 0 : outputSliceStride_ = CreateVariable();
84 0 : inputRepeatStride_ = CreateVariable();
85 0 : outputRepeatStride_ = CreateVariable();
86 0 : localAxisSignal_ = CreateMaskSignal();
87 0 : anotherAxisSignal_ = CreateMaskSignal();
88 0 : localSignal_ = CreateMaskSignal();
89 0 : repeatNumVar_ = CreateVariable();
90 0 : repeatNumVarTemp_ = CreateVariable();
91 0 : isBottom_ = CreateVariable();
92 :
93 0 : if (linkNum_ == LINK_SIZE) {
94 0 : ExportMaskSignal(localAxisSignal_, localAxisSignalName_);
95 0 : anotherAxisSignal_ = ImportMaskSignal(anotherAxisSignalName_);
96 : }
97 :
98 0 : output_ = CreateVariable();
99 0 : for (uint32_t transportIdx = 0; transportIdx < localSize_; transportIdx++) {
100 0 : HCCL_INFO("[CcuContextReduceScatterNHR1DMem2Mem] MyRank[%u], TransportId[%u]", rankId_, transportIdx);
101 0 : CHK_PRT_RET(
102 : transports[transportIdx] == nullptr,
103 : HCCL_ERROR("[CcuContextReduceScatterNHR1DMem2Mem] Algorithm transport ptr is null"), );
104 0 : input_.push_back(
105 0 : CreateVariable((*transports[transportIdx]), INPUT_XN_ID)); // 获取transport中id=0的Var来传递input
106 :
107 0 : token_.push_back(CreateVariable((*transports[transportIdx]), TOKEN_XN_ID));
108 : }
109 0 : input_.push_back(CreateVariable());
110 0 : token_.push_back(CreateVariable());
111 :
112 0 : repeatInputOffset_ = CreateVariable();
113 0 : repeatOutputOffset_ = CreateVariable();
114 0 : myrankInputSliceOffset_ = CreateVariable();
115 :
116 0 : srcMem_ = CreateMemory();
117 0 : dstMem_ = CreateMemory();
118 0 : flag_ = CreateVariable();
119 0 : HCCL_INFO("[CcuContextReduceScatterNHR1DMem2Mem] InitResources finished");
120 : }
121 :
122 0 : void CcuContextReduceScatterNHR1DMem2Mem::PreSync()
123 : {
124 0 : HCCL_INFO("[CcuContextReduceScatterNHR1DMem2Mem] PreSync start");
125 : // 本rank用哪一个CKE
126 0 : uint16_t selfSignalId = rankId_ / RANK_NUM_PER_CKE;
127 : // 本rank用CKE的哪一位
128 0 : uint16_t selfBit = 1 << (rankId_ % RANK_NUM_PER_CKE);
129 0 : for (auto t : transports) {
130 0 : WriteVariableWithSignal(*t, input_[localSize_], INPUT_XN_ID, selfSignalId + signalNum_ * CKE_IDX_1, selfBit);
131 0 : WriteVariableWithSignal(*t, token_[localSize_], TOKEN_XN_ID, selfSignalId + signalNum_ * CKE_IDX_2, selfBit);
132 : }
133 0 : std::vector<uint16_t> waitBitVector(signalNum_, 0);
134 0 : for (auto& pair : indexMap_) {
135 0 : uint16_t pairSignalId = pair.first / RANK_NUM_PER_CKE;
136 0 : uint16_t pairBit = 1 << (pair.first % RANK_NUM_PER_CKE);
137 0 : waitBitVector[pairSignalId] = waitBitVector[pairSignalId] | pairBit;
138 : }
139 0 : for (uint16_t sId = 0; sId < waitBitVector.size(); sId++) {
140 0 : GroupWait(*transportGroup, sId + signalNum_ * CKE_IDX_1, waitBitVector[sId]);
141 0 : GroupWait(*transportGroup, sId + signalNum_ * CKE_IDX_2, waitBitVector[sId]);
142 : }
143 0 : HCCL_INFO("[CcuContextReduceScatterNHR1DMem2Mem] PreSync end");
144 0 : }
145 :
146 0 : void CcuContextReduceScatterNHR1DMem2Mem::PostSync()
147 : {
148 0 : uint16_t selfSignalId = rankId_ / RANK_NUM_PER_CKE;
149 0 : uint16_t selfBit = 1 << (rankId_ % RANK_NUM_PER_CKE);
150 0 : for (auto& t : transports) {
151 0 : RemotePost(*t, selfSignalId + signalNum_ * CKE_IDX_0, selfBit);
152 : }
153 0 : std::vector<uint16_t> waitBitVector(signalNum_, 0);
154 0 : for (auto& pair : indexMap_) {
155 0 : uint16_t pairSignalId = pair.first / RANK_NUM_PER_CKE;
156 0 : uint16_t pairBit = 1 << (pair.first % RANK_NUM_PER_CKE);
157 0 : waitBitVector[pairSignalId] = waitBitVector[pairSignalId] | pairBit;
158 : }
159 0 : for (uint32_t sId = 0; sId < waitBitVector.size(); sId++) {
160 0 : GroupWait(*transportGroup, sId + signalNum_ * CKE_IDX_0, waitBitVector[sId]);
161 : }
162 0 : HCCL_INFO("[CcuContextReduceScatterNHR1DMem2Mem] PostSync run finished");
163 0 : }
164 :
165 0 : void CcuContextReduceScatterNHR1DMem2Mem::AxisSync(uint32_t signalIndex)
166 : {
167 0 : const uint32_t DIE_NUM = 2;
168 0 : if (signalIndex > 1) {
169 0 : THROW<InvalidParamsException>(
170 0 : StringFormat("[CcuContextReduceScatterNHR1DMem2Mem] Unexpected SignalInex[%u]", signalIndex));
171 : }
172 0 : LocalCtxPost(anotherAxisSignal_, 1 << (axisId_ + signalIndex * DIE_NUM));
173 0 : LocalWait(localAxisSignal_, 1 << (1 - axisId_ + signalIndex * DIE_NUM));
174 0 : HCCL_INFO("[CcuContextReduceScatterNHR1DMem2Mem] AxisSync run finished");
175 0 : return;
176 : }
177 :
178 0 : void CcuContextReduceScatterNHR1DMem2Mem::DoRepeatReduceScatterNHR()
179 : {
180 0 : CcuRep::Variable tmpSliceOffset = CreateVariable();
181 0 : tmpSliceOffset = 0;
182 : // 用来记录每个rank要读取的rank的sliceIdx的偏移
183 : // 后面会用inputAddr来加上这个偏移获取sliceIdx的地址
184 0 : std::vector<CcuRep::Variable> inputSliceOffset;
185 0 : CCU_IF(isBottom_ == 1)
186 : {
187 0 : for (u64 i = 0; i < dimSize_; i++) {
188 0 : inputSliceOffset.push_back(CreateVariable());
189 0 : inputSliceOffset[i] = tmpSliceOffset;
190 0 : tmpSliceOffset += inputSliceStride_;
191 : }
192 0 : }
193 0 : CCU_IF(isBottom_ == 0)
194 : {
195 0 : for (u64 i = 0; i < dimSize_; i++) {
196 0 : inputSliceOffset.push_back(CreateVariable());
197 0 : inputSliceOffset[i] = tmpSliceOffset;
198 0 : tmpSliceOffset += inputRepeatStride_;
199 : }
200 0 : }
201 :
202 0 : for (auto& nhrStepInfo : stepInfoVector_) {
203 0 : DoRepeatReduceScatterNHRSingleStep(nhrStepInfo, inputSliceOffset);
204 : }
205 : // 因为所有的修改都是在input上进行的，所以最后需要把input上的数据搬到output上
206 0 : dstMem_.addr = output_;
207 0 : dstMem_.token = token_[myRankIdx_];
208 0 : srcMem_.addr = input_[myRankIdx_];
209 0 : srcMem_.addr += inputSliceOffset[rankId_];
210 0 : srcMem_.token = token_[myRankIdx_];
211 :
212 0 : CcuRep::Variable repeatNumAdd2 = CreateVariable();
213 0 : repeatNumAdd2 = 1;
214 0 : CCU_WHILE(repeatNumVar_ != UINT64_MAX)
215 : {
216 0 : repeatNumVar_ += repeatNumAdd2;
217 0 : CCU_IF(flag_ == 1)
218 : {
219 0 : CCU_IF(isBottom_ == 0)
220 : {
221 0 : srcMem_.addr += inputSliceStride_;
222 0 : dstMem_.addr += outputRepeatStride_;
223 0 : }
224 0 : CCU_IF(isBottom_ == 1)
225 : {
226 0 : srcMem_.addr += inputRepeatStride_;
227 0 : dstMem_.addr += outputRepeatStride_;
228 0 : }
229 0 : }
230 0 : CCU_IF(flag_ == 0)
231 : {
232 0 : if (axisId_ == 1) {
233 0 : srcMem_.addr += die0Size_;
234 0 : dstMem_.addr += die0Size_;
235 : }
236 0 : }
237 0 : CcuRep::Variable& localSliceSize = (axisId_ == 0) ? die0Size_ : die1Size_;
238 0 : LocalCopy(dstMem_, srcMem_, localSliceSize, localSignal_, 1);
239 0 : LocalWait(localSignal_, 1);
240 0 : flag_ = 1;
241 0 : }
242 0 : }
243 :
244 0 : void CcuContextReduceScatterNHR1DMem2Mem::DoRepeatReduceScatterNHRSingleStep(
245 : const NHRStepInfo& nhrStepInfo, const std::vector<CcuRep::Variable>& inputSliceOffset)
246 : {
247 0 : u32& toRankIdx = indexMap_[nhrStepInfo.toRank];
248 0 : u32& fromRankIdx = indexMap_[nhrStepInfo.fromRank];
249 0 : CcuTransport* sendTransport = transports[toRankIdx];
250 0 : CcuTransport* recvTransport = transports[fromRankIdx];
251 0 : const std::vector<u32>& sendSliceIdxList = nhrStepInfo.txSliceIdxs;
252 0 : dstMem_.token = token_[toRankIdx];
253 0 : srcMem_.token = token_[myRankIdx_];
254 :
255 : // 被写之前告诉写自己的rank自己准备好了-前同步
256 0 : uint16_t recvSignalIdPrev = nhrStepInfo.fromRank / RANK_NUM_PER_CKE;
257 0 : uint16_t recvBitPrev = 1 << (nhrStepInfo.fromRank % RANK_NUM_PER_CKE);
258 0 : RemotePost(*recvTransport, recvSignalIdPrev + signalNum_ * CKE_IDX_3, recvBitPrev, true);
259 :
260 0 : uint16_t selfSignalIdPrev = rankId_ / RANK_NUM_PER_CKE;
261 0 : uint16_t selfBitPrev = 1 << (rankId_ % RANK_NUM_PER_CKE);
262 0 : RemoteWait(*sendTransport, selfSignalIdPrev + signalNum_ * CKE_IDX_3, selfBitPrev);
263 :
264 0 : for (const u32& sendSliceIdx : sendSliceIdxList) {
265 0 : dstMem_.addr = input_[toRankIdx];
266 0 : dstMem_.addr += inputSliceOffset[sendSliceIdx];
267 0 : srcMem_.addr = input_[myRankIdx_];
268 0 : srcMem_.addr += inputSliceOffset[sendSliceIdx];
269 0 : DoRepeatSendRecvSlices(nhrStepInfo.toRank, srcMem_, dstMem_);
270 : }
271 :
272 : // 写之后告诉对面写完了-后同步
273 0 : uint16_t selfSignalId = rankId_ / RANK_NUM_PER_CKE;
274 0 : uint16_t selfBit = 1 << (rankId_ % RANK_NUM_PER_CKE);
275 0 : RemotePost(*sendTransport, selfSignalId + signalNum_ * CKE_IDX_4, selfBit, true);
276 :
277 0 : uint16_t recvSignalId = nhrStepInfo.fromRank / RANK_NUM_PER_CKE;
278 0 : uint16_t recvBit = 1 << (nhrStepInfo.fromRank % RANK_NUM_PER_CKE);
279 0 : RemoteWait(*recvTransport, recvSignalId + signalNum_ * CKE_IDX_4, recvBit);
280 0 : }
281 :
282 0 : void CcuContextReduceScatterNHR1DMem2Mem::DoRepeatSendRecvSlices(
283 : const u32& toRank, CcuRep::Memory& src, CcuRep::Memory& dst)
284 : {
285 0 : CcuRep::Variable repeatNumAdd = CreateVariable();
286 0 : repeatNumAdd = 1;
287 0 : flag_ = 0;
288 0 : CcuTransport* sendTransport = transports[indexMap_[toRank]];
289 0 : repeatNumVarTemp_ = repeatNumVar_;
290 0 : CCU_WHILE(repeatNumVarTemp_ != UINT64_MAX)
291 : {
292 0 : CCU_IF(repeatNumVarTemp_ != UINT64_MAX) { repeatNumVarTemp_ += repeatNumAdd; }
293 :
294 0 : CCU_IF(flag_ == 1)
295 : {
296 0 : CCU_IF(isBottom_ == 0)
297 : {
298 0 : src.addr += inputSliceStride_;
299 0 : dst.addr += inputSliceStride_;
300 0 : }
301 0 : CCU_IF(isBottom_ == 1)
302 : {
303 0 : src.addr += inputRepeatStride_;
304 0 : dst.addr += inputRepeatStride_;
305 0 : }
306 0 : }
307 0 : CCU_IF(flag_ == 0)
308 : {
309 0 : if (axisId_ == 1) {
310 0 : src.addr += die0Size_;
311 0 : dst.addr += die0Size_;
312 : }
313 0 : }
314 0 : sliceSize_ = (axisId_ == 0) ? die0Size_ : die1Size_;
315 0 : WriteReduce(*sendTransport, dst, src, sliceSize_, dataType_, reduceOp_, localSignal_, 1);
316 0 : LocalWait(localSignal_, (1 << 1) - 1);
317 0 : flag_ = 1;
318 0 : }
319 0 : flag_ = 0;
320 0 : }
321 :
322 0 : void CcuContextReduceScatterNHR1DMem2Mem::Algorithm()
323 : {
324 0 : HCCL_INFO("[CcuContextReduceScatterNHR1DMem2Mem] CcuContextReduceScatterNHR1DMem2Mem run.");
325 0 : InitResources();
326 0 : LoadArgs();
327 0 : if (linkNum_ == LINK_SIZE) {
328 0 : AxisSync(FST_AXIS_ID);
329 : }
330 0 : PreSync();
331 0 : DoRepeatReduceScatterNHR();
332 0 : PostSync();
333 0 : if (linkNum_ == LINK_SIZE) {
334 0 : AxisSync(SEC_AXIS_ID);
335 : }
336 :
337 0 : HCCL_INFO("[CcuContextReduceScatterNHR1DMem2Mem] CcuContextReduceScatterNHR1DMem2Mem end.");
338 0 : return;
339 : }
340 :
341 0 : std::vector<uint64_t> CcuContextReduceScatterNHR1DMem2Mem::GeneArgs(const CcuTaskArg& arg)
342 : {
343 0 : const CcuTaskArgReduceScatterNHR1D* taskArg = dynamic_cast<const CcuTaskArgReduceScatterNHR1D*>(&arg);
344 0 : if (taskArg == nullptr) {
345 0 : THROW<NullPtrException>(StringFormat("CcuContextReduceScatterNHR1DMem2Mem::taskArg ptr is null"));
346 : }
347 : // input & output & buffer地址
348 0 : uint64_t inputAddr = taskArg->inputAddr_;
349 0 : uint64_t outputAddr = taskArg->outputAddr_;
350 0 : uint64_t token = taskArg->token_;
351 0 : uint64_t die0Size = taskArg->die0Size_;
352 0 : uint64_t die1Size = taskArg->die1Size_;
353 0 : uint64_t inputSliceStride = taskArg->inputSliceStride_;
354 0 : uint64_t outputSliceStride = taskArg->outputSliceStride_;
355 0 : uint64_t inputRepeatStride = taskArg->inputRepeatStride_;
356 0 : uint64_t outputRepeatStride = taskArg->outputRepeatStride_;
357 0 : uint64_t repeatNumVar = taskArg->repeatNum_;
358 0 : uint64_t isBottom = taskArg->isBottom_;
359 :
360 0 : HCCL_INFO(
361 : "[CcuContextReduceScatterNHR1DMem2Mem] TaskArgs: inputAddr[%llu], outputAddr[%llu],"
362 : "die0Size[%llu], die1Size[%llu],"
363 : "inputSliceStride[%llu], outputSliceStride[%llu], inputRepeatStride[%llu], outputRepeatStride[%llu]",
364 : inputAddr, outputAddr, die0Size, die1Size, inputSliceStride, outputSliceStride, inputRepeatStride,
365 : outputRepeatStride);
366 :
367 : return {
368 : inputAddr, outputAddr, token, die0Size, die1Size, inputSliceStride, outputSliceStride,
369 0 : inputRepeatStride, outputRepeatStride, repeatNumVar, isBottom};
370 : }
371 : } // namespace Hccl
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