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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_all_reduce_nhr1d_mem2mem.h"
12 :
13 : namespace Hccl {
14 :
15 : 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
16 : constexpr uint16_t OUTPUT_XN_ID = 1;
17 : constexpr uint16_t TOKEN_XN_ID = 2;
18 : constexpr uint16_t CKE_IDX_0 = 0; // 后同步
19 : constexpr uint16_t CKE_IDX_1 = 1; // 前同步addr
20 : constexpr uint16_t CKE_IDX_2 = 2; // 前同步token
21 : constexpr uint16_t CKE_IDX_3 = 3; // NHR step同步信号0，用于RS前同步，AG后同步
22 : constexpr uint16_t CKE_IDX_4 = 4; // NHR step同步信号1，用于RS后同步
23 : constexpr uint16_t FST_AXIS_ID = 0;
24 : constexpr uint16_t SEC_AXIS_ID = 1;
25 :
26 0 : CcuContextAllReduceNHR1D::CcuContextAllReduceNHR1D(
27 0 : const CcuCtxArg& arg, const std::vector<CcuTransport*>& transports, const CcuTransportGroup& group)
28 0 : : CcuContextAlgBase(arg, transports, group)
29 : {
30 0 : const CcuCtxArgAllReduceNHR1D* ctxArg = dynamic_cast<const CcuCtxArgAllReduceNHR1D*>(&arg);
31 0 : rankId_ = ctxArg->rankId_;
32 0 : axisId_ = ctxArg->axisId_;
33 0 : axisSize_ = ctxArg->axisSize_;
34 0 : dimSize_ = ctxArg->dimSize_[0];
35 0 : stepInfoVector_ = ctxArg->stepInfoVector_;
36 0 : indexMap_ = ctxArg->indexMap_;
37 0 : localSize_ = indexMap_.size();
38 0 : myRankIdx_ = indexMap_.size();
39 0 : dataType_ = ctxArg->op_.dataType;
40 0 : reduceOp_ = ctxArg->op_.reduceOp;
41 0 : signalNum_ = (dimSize_ + RANK_NUM_PER_CKE - 1) / RANK_NUM_PER_CKE; // 每个CKE有16个bit
42 0 : HCCL_INFO(
43 : "[CcuContextAllReduceNHR1D] CtxArg: rankId_[%u], axisId_[%u], axisSize_[%u], dimSize_[%u], localSize_[%u], "
44 : "signalNum_[%u], dataType[%s], reduceOp[%s]",
45 : rankId_, axisId_, axisSize_, dimSize_, localSize_, signalNum_, dataType_.Describe().c_str(),
46 : reduceOp_.Describe().c_str());
47 0 : }
48 :
49 0 : void CcuContextAllReduceNHR1D::LoadArgs()
50 : {
51 0 : Load(input_);
52 0 : Load(output_[myRankIdx_]);
53 0 : Load(token_[myRankIdx_]);
54 0 : Load(isInputOutputEqual_);
55 0 : Load(die0Size_);
56 0 : Load(die1Size_);
57 0 : Load(die0SliceSize_);
58 0 : Load(die1SliceSize_);
59 0 : Load(die0LastSliceSize_);
60 0 : Load(die1LastSliceSize_);
61 0 : HCCL_DEBUG("[CcuContextAllReduceNHR1D] LoadArgs run finished");
62 0 : }
63 :
64 0 : void CcuContextAllReduceNHR1D::InitResources()
65 : {
66 0 : isInputOutputEqual_ = CreateVariable();
67 0 : die0SliceSize_ = CreateVariable();
68 0 : die1SliceSize_ = CreateVariable();
69 0 : die0LastSliceSize_ = CreateVariable();
70 0 : die1LastSliceSize_ = CreateVariable();
71 0 : die0Size_ = CreateVariable();
72 0 : die1Size_ = CreateVariable();
73 0 : localSignal_ = CreateMaskSignal();
74 :
75 0 : input_ = CreateVariable();
76 0 : for (uint32_t transportIdx = 0; transportIdx < localSize_; transportIdx++) {
77 0 : HCCL_DEBUG("[CcuContextAllReduceNHR1D] MyRank[%u], TransportId[%u]", rankId_, transportIdx);
78 0 : CHK_PRT_RET(
79 : transports[transportIdx] == nullptr,
80 : HCCL_ERROR("[CcuContextAllReduceNHR1D] Algorithm transport ptr is null"), );
81 0 : output_.push_back(
82 0 : CreateVariable((*transports[transportIdx]), OUTPUT_XN_ID)); // 获取transport中id=1的Var来传递output
83 0 : token_.push_back(CreateVariable((*transports[transportIdx]), TOKEN_XN_ID));
84 : }
85 0 : output_.push_back(CreateVariable());
86 0 : token_.push_back(CreateVariable());
87 :
88 0 : srcMem_ = CreateMemory();
89 0 : dstMem_ = CreateMemory();
90 0 : HCCL_DEBUG("[CcuContextAllReduceNHR1D] InitResources finished");
91 : }
92 :
93 0 : void CcuContextAllReduceNHR1D::PreSync()
94 : {
95 0 : HCCL_DEBUG("[CcuContextAllReduceNHR1D] PreSync start");
96 0 : uint16_t selfBit = 1 << (rankId_ % RANK_NUM_PER_CKE);
97 0 : uint16_t selfSignalId = rankId_ / RANK_NUM_PER_CKE;
98 0 : std::vector<uint16_t> waitBitVector(signalNum_, 0);
99 0 : for (auto t : transports) {
100 0 : WriteVariableWithSignal(*t, output_[localSize_], OUTPUT_XN_ID, selfSignalId + signalNum_ * CKE_IDX_1, selfBit);
101 0 : WriteVariableWithSignal(*t, token_[localSize_], TOKEN_XN_ID, selfSignalId + signalNum_ * CKE_IDX_2, selfBit);
102 : }
103 0 : for (auto& pair : indexMap_) {
104 0 : uint16_t pairBit = 1 << (pair.first % RANK_NUM_PER_CKE);
105 0 : uint16_t pairSignalId = pair.first / RANK_NUM_PER_CKE;
106 0 : waitBitVector[pairSignalId] = waitBitVector[pairSignalId] | pairBit;
107 : }
108 0 : for (uint16_t sId = 0; sId < waitBitVector.size(); sId++) {
109 0 : GroupWait(*transportGroup, sId + signalNum_ * CKE_IDX_1, waitBitVector[sId]);
110 0 : GroupWait(*transportGroup, sId + signalNum_ * CKE_IDX_2, waitBitVector[sId]);
111 : }
112 0 : HCCL_DEBUG("[CcuContextAllReduceNHR1D] PreSync end");
113 0 : }
114 :
115 0 : void CcuContextAllReduceNHR1D::PostSync()
116 : {
117 0 : uint16_t selfSignalId = rankId_ / RANK_NUM_PER_CKE;
118 0 : uint16_t selfBit = 1 << (rankId_ % RANK_NUM_PER_CKE);
119 0 : std::vector<uint16_t> waitBitVector(signalNum_, 0);
120 0 : for (auto& t : transports) {
121 0 : RemotePost(*t, selfSignalId + signalNum_ * CKE_IDX_0, selfBit);
122 : }
123 0 : for (auto& pair : indexMap_) {
124 0 : uint16_t pairSignalId = pair.first / RANK_NUM_PER_CKE;
125 0 : uint16_t pairBit = 1 << (pair.first % RANK_NUM_PER_CKE);
126 0 : waitBitVector[pairSignalId] = waitBitVector[pairSignalId] | pairBit;
127 : }
128 0 : for (uint32_t sId = 0; sId < signalNum_; sId++) {
129 0 : GroupWait(*transportGroup, sId + signalNum_ * CKE_IDX_0, waitBitVector[sId]);
130 : }
131 0 : HCCL_DEBUG("[CcuContextAllReduceNHR1D] PostSync run finished");
132 0 : }
133 :
134 0 : void CcuContextAllReduceNHR1D::AxisSync(uint32_t signalIndex)
135 : {
136 0 : const uint32_t DIE_NUM = 2;
137 0 : if (signalIndex > 1) {
138 0 : THROW<InvalidParamsException>(
139 0 : StringFormat("[CcuContextAllReduceNHR1D] Unexpected SignalInex[%u]", signalIndex));
140 : }
141 0 : LocalCtxPost(anotherAxisSignal_, 1 << (axisId_ + signalIndex * DIE_NUM));
142 0 : LocalWait(localAxisSignal_, 1 << (1 - axisId_ + signalIndex * DIE_NUM));
143 0 : HCCL_DEBUG("[CcuContextAllReduceNHR1D] AxisSync run finished");
144 0 : return;
145 : }
146 :
147 0 : void CcuContextAllReduceNHR1D::DoReduceScatterNHR()
148 : {
149 0 : const uint32_t NHR_NUM = 2;
150 0 : for (u64 i = 0; i < stepInfoVector_.size() / NHR_NUM; i++) {
151 0 : const NHRStepInfo& nhrStepInfo = stepInfoVector_[i];
152 0 : DoReduceScatterNHRSingleStep(nhrStepInfo);
153 : }
154 0 : }
155 :
156 0 : void CcuContextAllReduceNHR1D::DoReduceScatterNHRSingleStep(const NHRStepInfo& nhrStepInfo)
157 : {
158 0 : u32 sendSliceIdx = 0;
159 0 : u32& fromRankIdx = indexMap_[nhrStepInfo.fromRank];
160 0 : u32& toRankIdx = indexMap_[nhrStepInfo.toRank];
161 0 : const std::vector<u32>& sendSliceIdxList = nhrStepInfo.txSliceIdxs;
162 0 : srcMem_.token = token_[myRankIdx_];
163 0 : dstMem_.token = token_[toRankIdx];
164 0 : CcuTransport* sendTransport = transports[toRankIdx];
165 0 : CcuTransport* recvTransport = transports[fromRankIdx];
166 :
167 0 : uint16_t selfSignalId = rankId_ / RANK_NUM_PER_CKE;
168 0 : uint16_t selfBit = 1 << (rankId_ % RANK_NUM_PER_CKE);
169 0 : uint16_t sendSignalId = nhrStepInfo.toRank / RANK_NUM_PER_CKE;
170 0 : uint16_t sendBit = 1 << (nhrStepInfo.toRank % RANK_NUM_PER_CKE);
171 0 : if (nhrStepInfo.step != 0) {
172 : // 通知fromRank，可以写入
173 0 : RemotePost(*recvTransport, selfSignalId + signalNum_ * CKE_IDX_3, selfBit, true);
174 :
175 : // 等待toRank通知其可以写入
176 0 : RemoteWait(*sendTransport, sendSignalId + signalNum_ * CKE_IDX_3, sendBit);
177 : }
178 :
179 0 : for (u32 i = 0; i < sendSliceIdxList.size(); i++) {
180 0 : sendSliceIdx = sendSliceIdxList[i];
181 0 : if (i != 0) {
182 0 : if (i % RANK_NUM_PER_CKE == 0) {
183 0 : LocalWait(localSignal_, (1 << RANK_NUM_PER_CKE) - 1);
184 : }
185 : }
186 0 : if (nhrStepInfo.step == 0) {
187 : // 只有第0步的源数据从input中取
188 0 : HCCL_INFO("[CcuContextAllReduceNHR1D] nhrStepInfo 0.");
189 0 : srcMem_.addr = input_;
190 0 : srcMem_.addr += sliceOffset_[sendSliceIdx];
191 : } else {
192 0 : srcMem_.addr = output_[myRankIdx_];
193 0 : srcMem_.addr += sliceOffset_[sendSliceIdx];
194 : }
195 0 : dstMem_.addr = output_[toRankIdx];
196 0 : dstMem_.addr += sliceOffset_[sendSliceIdx];
197 0 : DoWriteReduceSlice(nhrStepInfo.toRank, srcMem_, dstMem_, sendSliceIdx, i % RANK_NUM_PER_CKE);
198 : }
199 0 : LocalWait(localSignal_, (1 << (sendSliceIdxList.size() % RANK_NUM_PER_CKE)) - 1);
200 :
201 : // 通知toRank数据写入完毕
202 0 : RemotePost(*sendTransport, selfSignalId + signalNum_ * CKE_IDX_4, selfBit, true);
203 : // 等待fromRank通知数据写入完毕
204 0 : uint16_t recvBit = 1 << (nhrStepInfo.fromRank % RANK_NUM_PER_CKE);
205 0 : uint16_t recvSignalId = nhrStepInfo.fromRank / RANK_NUM_PER_CKE;
206 0 : RemoteWait(*recvTransport, recvSignalId + signalNum_ * CKE_IDX_4, recvBit);
207 0 : HCCL_DEBUG(
208 : "[DoReduceScatterNHRSingleStep] rank %u step %u, toRank=%u, fromRank=%u, nSlice=%lu", rankId_, nhrStepInfo.step,
209 : nhrStepInfo.toRank, nhrStepInfo.fromRank, sendSliceIdxList.size());
210 0 : }
211 :
212 0 : void CcuContextAllReduceNHR1D::DoWriteReduceSlice(
213 : const u32& toRank, CcuRep::Memory& src, CcuRep::Memory& dst, const u32& sendSliceIdx, u32 signalIndex)
214 : {
215 : bool islastSlice;
216 : // 添加 die1 偏移
217 0 : if (axisId_ == 1) {
218 0 : dst.addr += die0Size_;
219 0 : src.addr += die0Size_;
220 : }
221 0 : CcuTransport* sendTransport = transports[indexMap_[toRank]];
222 0 : islastSlice = (sendSliceIdx + 1 == dimSize_);
223 :
224 : // allreduce切片的最后一块slice，大小可能不一致
225 0 : const CcuRep::Variable& sliceSize = axisId_ == 0 ? (islastSlice ? die0LastSliceSize_ : die0SliceSize_) :
226 : (islastSlice ? die1LastSliceSize_ : die1SliceSize_);
227 0 : CCU_IF(sliceSize != 0)
228 : {
229 0 : WriteReduce(*sendTransport, dst, src, sliceSize, dataType_, reduceOp_, localSignal_, 1 << signalIndex);
230 0 : }
231 0 : CCU_IF(sliceSize == 0) { LocalPost(localSignal_, 1 << signalIndex); }
232 0 : }
233 :
234 0 : void CcuContextAllReduceNHR1D::DoAllGatherNHR()
235 : {
236 0 : const uint32_t NHR_NUM = 2;
237 0 : for (u64 i = stepInfoVector_.size() / NHR_NUM; i < stepInfoVector_.size(); i++) {
238 0 : const NHRStepInfo& nhrStepInfo = stepInfoVector_[i];
239 0 : DoAllGatherNHRSingleStep(nhrStepInfo);
240 : }
241 0 : }
242 :
243 0 : void CcuContextAllReduceNHR1D::DoAllGatherNHRSingleStep(const NHRStepInfo& nhrStepInfo)
244 : {
245 0 : u32 sendSliceIdx = 0;
246 0 : u32& toRankIdx = indexMap_[nhrStepInfo.toRank];
247 0 : u32& fromRankIdx = indexMap_[nhrStepInfo.fromRank];
248 0 : CcuTransport* sendTransport = transports[toRankIdx];
249 0 : CcuTransport* recvTransport = transports[fromRankIdx];
250 0 : const std::vector<u32>& sendSliceIdxList = nhrStepInfo.txSliceIdxs;
251 0 : srcMem_.token = token_[myRankIdx_];
252 0 : dstMem_.token = token_[toRankIdx];
253 :
254 0 : uint16_t selfSignalId = rankId_ / RANK_NUM_PER_CKE;
255 0 : uint16_t selfBit = 1 << (rankId_ % RANK_NUM_PER_CKE);
256 :
257 0 : for (u32 i = 0; i < sendSliceIdxList.size(); i++) {
258 0 : sendSliceIdx = sendSliceIdxList[i];
259 :
260 0 : if (i != 0) {
261 0 : if (i % RANK_NUM_PER_CKE == 0) {
262 0 : LocalWait(localSignal_, (1 << RANK_NUM_PER_CKE) - 1);
263 : }
264 : }
265 :
266 0 : srcMem_.addr = output_[myRankIdx_];
267 0 : dstMem_.addr = output_[toRankIdx];
268 0 : dstMem_.addr += sliceOffset_[sendSliceIdx];
269 0 : srcMem_.addr += sliceOffset_[sendSliceIdx];
270 0 : DoSendRecvSlice(nhrStepInfo.toRank, srcMem_, dstMem_, sendSliceIdx, i % RANK_NUM_PER_CKE);
271 : }
272 0 : LocalWait(localSignal_, (1 << (sendSliceIdxList.size() % RANK_NUM_PER_CKE)) - 1);
273 :
274 0 : if (nhrStepInfo.step + 1 != stepInfoVector_.size()) { // 最后一步不需要同步
275 : // 通知toRank，写入完毕
276 0 : RemotePost(*sendTransport, selfSignalId + signalNum_ * CKE_IDX_3, selfBit, true);
277 : // 等待fromRank通知写入完毕
278 0 : uint16_t recvBit = 1 << (nhrStepInfo.fromRank % RANK_NUM_PER_CKE);
279 0 : uint16_t recvSignalId = nhrStepInfo.fromRank / RANK_NUM_PER_CKE;
280 0 : RemoteWait(*recvTransport, recvSignalId + signalNum_ * CKE_IDX_3, recvBit);
281 : }
282 :
283 0 : HCCL_DEBUG(
284 : "[DoAllGatherNHRSingleStep] rank %u step %u, toRank=%u, fromRank=%u, nSlice=%lu", rankId_, nhrStepInfo.step,
285 : nhrStepInfo.toRank, nhrStepInfo.fromRank, sendSliceIdxList.size());
286 0 : }
287 :
288 0 : void CcuContextAllReduceNHR1D::DoSendRecvSlice(
289 : const u32& toRank, CcuRep::Memory& src, CcuRep::Memory& dst, const u32& sendSliceIdx, u32 signalIndex)
290 : {
291 : bool islastSlice;
292 0 : CcuTransport* sendTransport = transports[indexMap_[toRank]];
293 0 : islastSlice = (sendSliceIdx + 1 == dimSize_);
294 : // 添加 die1 偏移
295 0 : if (axisId_ == 1) {
296 0 : dst.addr += die0Size_;
297 0 : src.addr += die0Size_;
298 : }
299 0 : const CcuRep::Variable& sliceSize = axisId_ == 0 ? (islastSlice ? die0LastSliceSize_ : die0SliceSize_) :
300 : (islastSlice ? die1LastSliceSize_ : die1SliceSize_);
301 0 : CCU_IF(sliceSize != 0) { Write(*sendTransport, dst, src, sliceSize, localSignal_, 1 << signalIndex); }
302 0 : CCU_IF(sliceSize == 0) { LocalPost(localSignal_, 1 << signalIndex); }
303 0 : }
304 :
305 0 : void CcuContextAllReduceNHR1D::LocalCopySlices()
306 : {
307 0 : u32 nonTxSliceIdx = 0;
308 0 : CcuRep::Variable tmpSliceOffset = CreateVariable();
309 0 : tmpSliceOffset = 0;
310 :
311 0 : for (u64 i = 0; i < dimSize_; i++) {
312 0 : sliceOffset_.push_back(CreateVariable());
313 0 : sliceOffset_[i] = tmpSliceOffset;
314 0 : tmpSliceOffset += axisId_ == 0 ? die0SliceSize_ : die1SliceSize_;
315 : }
316 :
317 : // 当input == output时，不需要拷贝
318 0 : CCU_IF(isInputOutputEqual_ == 0)
319 : {
320 : // 将step0中不需要写的slice，拷贝到本rank的output中
321 0 : const NHRStepInfo& nhrStepInfo = stepInfoVector_[0];
322 0 : const std::vector<u32>& nonTxSliceIdxList = GetNonTxSliceIdxs(nhrStepInfo.txSliceIdxs);
323 0 : for (u32 i = 0; i < nonTxSliceIdxList.size(); i++) {
324 0 : nonTxSliceIdx = nonTxSliceIdxList[i];
325 :
326 0 : if (i != 0) {
327 0 : if (i % RANK_NUM_PER_CKE == 0) {
328 0 : LocalWait(localSignal_, (1 << RANK_NUM_PER_CKE) - 1);
329 : }
330 : }
331 :
332 0 : srcMem_.addr = input_;
333 0 : dstMem_.addr = output_[myRankIdx_];
334 0 : srcMem_.addr += sliceOffset_[nonTxSliceIdx];
335 0 : dstMem_.addr += sliceOffset_[nonTxSliceIdx];
336 0 : srcMem_.token = token_[myRankIdx_];
337 0 : dstMem_.token = token_[myRankIdx_];
338 0 : DoLocalCopySlice(srcMem_, dstMem_, nonTxSliceIdx, i);
339 : }
340 0 : LocalWait(localSignal_, (1 << (nonTxSliceIdxList.size() % RANK_NUM_PER_CKE)) - 1);
341 0 : }
342 0 : }
343 :
344 0 : std::vector<u32> CcuContextAllReduceNHR1D::GetNonTxSliceIdxs(const std::vector<u32>& txSliceIdxs) const
345 : {
346 0 : std::vector<bool> isTx(dimSize_, false);
347 0 : for (u32 idx : txSliceIdxs) {
348 0 : if (idx < dimSize_) {
349 0 : isTx[idx] = true;
350 : }
351 : }
352 :
353 0 : std::vector<u32> nonTxSliceIdxs;
354 0 : for (u32 idx = 0; idx < dimSize_; ++idx) {
355 0 : if (!isTx[idx]) {
356 0 : nonTxSliceIdxs.push_back(idx);
357 : }
358 : }
359 :
360 0 : return nonTxSliceIdxs;
361 0 : }
362 :
363 0 : void CcuContextAllReduceNHR1D::DoLocalCopySlice(
364 : CcuRep::Memory& src, CcuRep::Memory& dst, const u32& copySliceIdx, u32 signalIndex)
365 : {
366 : bool islastSlice;
367 : // 添加 die1 偏移
368 0 : if (axisId_ == 1) {
369 0 : src.addr += die0Size_;
370 0 : dst.addr += die0Size_;
371 : }
372 :
373 0 : islastSlice = (copySliceIdx + 1 == dimSize_);
374 0 : const CcuRep::Variable& sliceSize = axisId_ == 0 ? (islastSlice ? die0LastSliceSize_ : die0SliceSize_) :
375 : (islastSlice ? die1LastSliceSize_ : die1SliceSize_);
376 0 : CCU_IF(sliceSize == 0) { LocalPost(localSignal_, 1 << signalIndex); }
377 :
378 0 : CCU_IF(sliceSize != 0) { LocalCopy(dst, src, sliceSize, localSignal_, 1 << signalIndex); }
379 0 : }
380 :
381 0 : void CcuContextAllReduceNHR1D::Algorithm()
382 : {
383 0 : HCCL_DEBUG("[CcuContextAllReduceNHR1D] AllReduceNHR1D run");
384 :
385 0 : InitResources();
386 0 : LoadArgs();
387 0 : LocalCopySlices();
388 0 : PreSync();
389 0 : DoReduceScatterNHR();
390 0 : DoAllGatherNHR();
391 0 : PostSync();
392 :
393 0 : HCCL_DEBUG("[CcuContextAllReduceNHR1D] AllReduceNHR1D end");
394 0 : return;
395 : }
396 :
397 0 : std::vector<uint64_t> CcuContextAllReduceNHR1D::GeneArgs(const CcuTaskArg& arg)
398 : {
399 0 : const CcuTaskArgAllReduceNHR1D* taskArg = dynamic_cast<const CcuTaskArgAllReduceNHR1D*>(&arg);
400 0 : if (taskArg == nullptr) {
401 0 : THROW<NullPtrException>(StringFormat("CcuContextAllReduceNHR1D::taskArg ptr is null"));
402 : }
403 : // input&output&buffer地址
404 0 : uint64_t inputAddr = taskArg->inputAddr_;
405 0 : uint64_t outputAddr = taskArg->outputAddr_;
406 0 : uint64_t token = taskArg->token_;
407 0 : uint64_t isInputOutputEqual = taskArg->isInputOutputEqual_;
408 0 : uint64_t die0Size = taskArg->die0Size_;
409 0 : uint64_t die1Size = taskArg->die1Size_;
410 0 : uint64_t die0SliceSize = taskArg->die0SliceSize_;
411 0 : uint64_t die1SliceSize = taskArg->die1SliceSize_;
412 0 : uint64_t die0LastSliceSize = taskArg->die0LastSliceSize_;
413 0 : uint64_t die1LastSliceSize = taskArg->die1LastSliceSize_;
414 :
415 0 : HCCL_INFO(
416 : "[CcuContextAllReduceNHR1D] TaskArgs: inputAddr[%llu], outputAddr[%llu], "
417 : "die0Size[%llu], die1Size[%llu], die0SliceSize[%llu], die1SliceSize[%llu],"
418 : "die0LastSliceSize[%llu], die1LastSliceSize[%llu]",
419 : inputAddr, outputAddr, die0Size, die1Size, die0SliceSize, die1SliceSize, die0LastSliceSize, die1LastSliceSize);
420 :
421 : return {inputAddr, outputAddr, token, isInputOutputEqual, die0Size,
422 0 : die1Size, die0SliceSize, die1SliceSize, die0LastSliceSize, die1LastSliceSize};
423 : }
424 : } // namespace Hccl
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