Line data Source code
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_mesh2d_mem2mem.h"
12 : #include "ccu_instruction_reduce_mesh2d_mem2mem.h"
13 :
14 : namespace Hccl {
15 :
16 0 : CcuContextReduceMeshMem2Mem2D::CcuContextReduceMeshMem2Mem2D(
17 0 : const CcuCtxArg& arg, const std::vector<CcuTransport*>& transports, const CcuTransportGroup& group)
18 0 : : CcuContextAlgBase(arg, transports, group)
19 : {
20 0 : const CcuCtxArgReduceMeshMem2Mem2D* ctxArg = dynamic_cast<const CcuCtxArgReduceMeshMem2Mem2D*>(&arg);
21 0 : if (ctxArg == nullptr) {
22 0 : THROW<NullPtrException>(StringFormat("CcuContextReduceMeshMem2Mem2D::ctxArg ptr is null"));
23 : }
24 0 : rankId_ = ctxArg->rankId_;
25 0 : dimSize_ = ctxArg->dimSize_;
26 0 : axisId_ = ctxArg->axisId_; // 要进行操作的是 行或列
27 :
28 0 : if (dimSize_.size() != 2 || axisId_ > 1 || dimSize_[0] == 0) { // 2D 拓扑校验
29 0 : THROW<NullPtrException>(StringFormat(
30 : "[CcuContextReduceMeshMem2Mem2D] dimSize[%u] or axisId[%u] or dimSize[0] [%u] is invalid", dimSize_.size(),
31 0 : axisId_, dimSize_[0]));
32 : }
33 0 : dimId_.emplace_back(rankId_ % dimSize_[0]);
34 0 : dimId_.emplace_back(rankId_ / dimSize_[0]);
35 0 : localId_ = dimId_[axisId_]; // 本rank所在的行/列
36 0 : localSize_ = dimSize_[axisId_]; // 本rank所在的行/列的总数
37 :
38 0 : HCCL_INFO(
39 : "[CcuContextReduceMeshMem2Mem2D] RankId[%u], DimSize0[%llu], DimSize1[%llu], localId[%llu], lcoalSize[%llu]",
40 : rankId_, dimSize_[0], dimSize_[1], localId_, localSize_);
41 :
42 0 : dataType_ = ctxArg->op_.dataType;
43 0 : outputDataType_ = ctxArg->op_.outputDataType;
44 0 : if (outputDataType_ == DataType::INVALID) {
45 0 : outputDataType_ = dataType_;
46 0 : HCCL_INFO(
47 : "[CcuContextReduceMeshMem2Mem2D] outputDataType is [INVALID], set outputDataType to[%s]",
48 : outputDataType_.Describe().c_str());
49 : }
50 0 : reduceOp_ = ctxArg->op_.reduceOp;
51 0 : rootId_ = ctxArg->rootId_;
52 0 : rootDimId_.emplace_back(rootId_ % dimSize_[0]); // root的x
53 0 : rootDimId_.emplace_back(rootId_ / dimSize_[0]); // root的y
54 0 : HCCL_INFO(
55 : "[CcuContextReduceMeshMem2Mem2D] init end, ctxArg->dimSize size[%zu] localSize_[%u]", ctxArg->dimSize_.size(),
56 : localSize_);
57 :
58 0 : localAxisSignalName_ = "CcuContextReduceMeshMem2Mem2DAxisSync_" + std::to_string(axisId_);
59 0 : anotherAxisSignalName_ = "CcuContextReduceMeshMem2Mem2DAxisSync_" + std::to_string(1 - axisId_);
60 0 : }
61 :
62 0 : void CcuContextReduceMeshMem2Mem2D::InitResources()
63 : {
64 0 : localAxisSignal_ = CreateMaskSignal();
65 0 : anotherAxisSignal_ = CreateMaskSignal();
66 0 : ExportMaskSignal(localAxisSignal_, localAxisSignalName_);
67 0 : anotherAxisSignal_ = ImportMaskSignal(anotherAxisSignalName_);
68 :
69 0 : output_ = CreateVariable();
70 0 : if (transports.size() == 0) {
71 0 : THROW<NullPtrException>(StringFormat("CcuContextReduceMeshMem2Mem2D transports is empty"));
72 : }
73 0 : uint32_t transportIdx = 0;
74 0 : for (uint32_t peerId = 0; peerId < localSize_; peerId++) {
75 0 : if (peerId == localId_) {
76 0 : input_.push_back(CreateVariable());
77 0 : token_.push_back(CreateVariable());
78 : } else {
79 0 : HCCL_INFO(
80 : "[CcuContextReduceMeshMem2Mem2D] MyRank[%u], PeerId[%u], TransportId[%u]", localId_, peerId,
81 : transportIdx);
82 0 : CHK_PRT_RET(
83 : transports[transportIdx] == nullptr,
84 : HCCL_ERROR("[CcuContextReduceMeshMem2Mem2D] Algorithm transport ptr is null"), );
85 0 : input_.push_back(
86 0 : CreateVariable((*transports[transportIdx]), INPUT_XN_ID)); // 获取transport中id=1的Var来传递output
87 0 : token_.push_back(CreateVariable((*transports[transportIdx]), TOKEN_XN_ID));
88 0 : transportIdx++;
89 : }
90 : }
91 0 : locMask_ = CreateMaskSignal();
92 0 : xAxisGroupOpSize_ = CreateGroupOpSize();
93 0 : yAxisGroupOpSize_ = CreateGroupOpSize();
94 0 : xAxisSize_ = CreateVariable();
95 0 : yAxisSize_ = CreateVariable();
96 0 : yAxisOffset_ = CreateVariable();
97 0 : curGoSize_ = CreateGroupOpSize();
98 0 : for (uint16_t roundId = 0; roundId < (localSize_ - 1); roundId++) {
99 0 : xChunkSize_.push_back(CreateVariable());
100 0 : yChunkSize_.push_back(CreateVariable());
101 0 : chunkSize_.push_back(CreateVariable());
102 : }
103 0 : chunkOffset_ = CreateVariable();
104 0 : HCCL_INFO("[CcuContextReduceMeshMem2Mem2D] InitResources finished");
105 : }
106 :
107 0 : void CcuContextReduceMeshMem2Mem2D::LoadArgs()
108 : {
109 0 : Load(input_[localId_]);
110 0 : Load(output_);
111 0 : Load(token_[localId_]);
112 0 : Load(xAxisSize_);
113 0 : Load(yAxisSize_);
114 0 : Load(yAxisOffset_);
115 0 : for (uint16_t i = 0; i < (localSize_ - 1); i++) {
116 0 : Load(xChunkSize_[i]);
117 : }
118 0 : for (uint16_t i = 0; i < (localSize_ - 1); i++) {
119 0 : Load(yChunkSize_[i]);
120 : }
121 0 : Load(xAxisGroupOpSize_);
122 0 : Load(yAxisGroupOpSize_);
123 : // 只有step2会用到localcopy
124 0 : curGoSize_ = (axisId_ == X_AXIS_ID) ? yAxisGroupOpSize_ : xAxisGroupOpSize_;
125 0 : HCCL_INFO("[CcuContextReduceMeshMem2Mem2D] LoadArgs run finished");
126 0 : }
127 :
128 0 : void CcuContextReduceMeshMem2Mem2D::PreSync() // 前同步
129 : {
130 0 : uint16_t selfBit = 1 << localId_;
131 0 : uint16_t allBit = ((1 << localSize_) - 1) & (~(1 << localId_));
132 :
133 0 : for (auto t : transports) {
134 0 : WriteVariableWithSignal(*t, input_[localId_], INPUT_XN_ID, CKE_IDX_1, selfBit); // index = 1，传递output信息
135 0 : WriteVariableWithSignal(*t, token_[localId_], TOKEN_XN_ID, CKE_IDX_2, selfBit); // index = 2，传递token信息
136 : }
137 0 : GroupWait(*transportGroup, CKE_IDX_1, allBit); // index = 1，传递output信息
138 0 : GroupWait(*transportGroup, CKE_IDX_2, allBit); // index = 2，传递token信息
139 0 : HCCL_INFO("[CcuContextReduceMeshMem2Mem2D] PreSync run finished");
140 0 : }
141 :
142 0 : void CcuContextReduceMeshMem2Mem2D::PostSync(uint32_t signalIndex)
143 : {
144 0 : uint16_t selfBit = 1 << localId_;
145 0 : uint16_t allBit = ((1 << localSize_) - 1) & (~(1 << localId_));
146 :
147 0 : for (auto t : transports) {
148 0 : RemotePost(*t, signalIndex, selfBit);
149 : }
150 0 : GroupWait(*transportGroup, signalIndex, allBit);
151 0 : HCCL_INFO("[CcuContextReduceMeshMem2Mem2D] PostSync run finished");
152 0 : }
153 :
154 0 : void CcuContextReduceMeshMem2Mem2D::AxisSync(uint32_t signalIndex) // 轴间同步
155 : {
156 0 : const uint32_t DIE_NUM = 2;
157 0 : LocalCtxPost(anotherAxisSignal_, 1 << (axisId_ + signalIndex * DIE_NUM));
158 0 : LocalWait(localAxisSignal_, 1 << (1 - axisId_ + signalIndex * DIE_NUM));
159 0 : HCCL_INFO("[CcuContextReduceMeshMem2Mem2D] AxisSync run finished");
160 0 : return;
161 : }
162 :
163 0 : void CcuContextReduceMeshMem2Mem2D::ReduceStep1()
164 : {
165 0 : HCCL_INFO("[CcuContextReduceMeshMem2Mem2D] RankId [%u], axisId [%u],Reduce Step1 starts", rankId_, axisId_);
166 0 : uint16_t allBit = ((1 << localSize_) - 1) & (~(1 << localId_));
167 0 : CcuRep::Memory dst = CreateMemory();
168 0 : CcuRep::Memory src = CreateMemory();
169 0 : dst.addr = input_[localId_]; // step1 reduce到input
170 0 : dst.token = token_[localId_];
171 0 : bool isYAxis = (axisId_ == Y_AXIS_ID);
172 0 : CcuRep::Memory tmpDst = CreateMemory();
173 0 : chunkSize_ = isYAxis ? yChunkSize_ : xChunkSize_;
174 0 : for (uint16_t i = 0; i < (localSize_ - 1); i++) { // 外层循环控制步数=chunk数量
175 : // 读不同rank的不同chunk
176 0 : for (uint16_t rmtId = 0; rmtId < localSize_; ++rmtId) {
177 0 : if (rmtId == localId_) {
178 0 : continue;
179 : }
180 0 : src.addr = input_[rmtId];
181 0 : src.token = token_[rmtId];
182 0 : tmpDst.addr = dst.addr;
183 0 : tmpDst.token = dst.token;
184 0 : if (isYAxis) { // 第一步yslicesize要在y轴方向reduce
185 0 : src.addr += yAxisOffset_;
186 0 : tmpDst.addr += yAxisOffset_;
187 : }
188 0 : chunkOffset_ = 0;
189 0 : uint16_t chkId = 0;
190 0 : if (rmtId < localId_) {
191 0 : chkId = (i + rmtId) % (localSize_ - 1);
192 : } else {
193 0 : chkId = (i + rmtId - 1) % (localSize_ - 1);
194 : }
195 : // 计算一下offset 0~(chikd-1)
196 0 : for (uint16_t j = 0; j < chkId; ++j) {
197 0 : chunkOffset_ += chunkSize_[j];
198 : }
199 : // 更新对应的addr
200 0 : src.addr += chunkOffset_;
201 0 : tmpDst.addr += chunkOffset_;
202 0 : CCU_IF(chunkSize_[chkId] == 0) { LocalPost(locMask_, 1 << rmtId); }
203 :
204 0 : CCU_IF(chunkSize_[chkId] != 0)
205 : {
206 0 : uint16_t transId = rmtId < localId_ ? rmtId : rmtId - 1;
207 0 : ReadReduce(
208 0 : *transports[transId], tmpDst, src, chunkSize_[chkId], dataType_, reduceOp_, locMask_, 1 << rmtId);
209 0 : }
210 : }
211 0 : LocalWait(locMask_, allBit);
212 : }
213 0 : HCCL_INFO("[CcuContextReduceMeshMem2Mem2D] Reduce Step1 ends");
214 0 : }
215 :
216 0 : void CcuContextReduceMeshMem2Mem2D::ReduceStep2()
217 : {
218 0 : HCCL_INFO("[CcuContextReduceMeshMem2Mem2D] RankId [%u] Reduce Step2 starts", rankId_);
219 0 : uint16_t allBit = ((1 << localSize_) - 1) & (~(1 << localId_));
220 0 : CcuRep::Memory dst = CreateMemory();
221 0 : CcuRep::Memory src = CreateMemory();
222 0 : dst.addr = output_; // 第二步reduce是从input reduce到root的output
223 0 : dst.token = token_[localId_];
224 :
225 0 : src.addr = input_[localId_];
226 0 : src.token = token_[localId_];
227 0 : bool isXAxis = (axisId_ == X_AXIS_ID);
228 0 : chunkSize_ = isXAxis ? yChunkSize_ : xChunkSize_;
229 0 : if (isXAxis) // 第二步yslicesize要在x轴方向reduce
230 : {
231 0 : src.addr += yAxisOffset_;
232 0 : dst.addr += yAxisOffset_;
233 : }
234 0 : GroupCopy(dst, src, curGoSize_);
235 0 : for (uint16_t i = 0; i < (localSize_ - 1); i++) {
236 0 : for (uint16_t rmtId = 0; rmtId < localSize_; ++rmtId) {
237 0 : if (rmtId == localId_) {
238 0 : continue;
239 : }
240 0 : dst.addr = output_;
241 0 : src.addr = input_[rmtId];
242 0 : src.token = token_[rmtId];
243 0 : if (isXAxis) {
244 0 : src.addr += yAxisOffset_;
245 0 : dst.addr += yAxisOffset_;
246 : }
247 0 : uint16_t chkId = 0;
248 0 : chunkOffset_ = 0;
249 0 : if (rmtId < localId_) {
250 0 : chkId = (i + rmtId) % (localSize_ - 1);
251 : } else {
252 0 : chkId = (i + rmtId - 1) % (localSize_ - 1);
253 : }
254 : // 计算一下offset 0~(chikd-1)
255 0 : for (uint16_t j = 0; j < chkId; ++j) {
256 0 : chunkOffset_ += chunkSize_[j];
257 : }
258 : // 更新对应的addr
259 0 : src.addr += chunkOffset_;
260 0 : dst.addr += chunkOffset_;
261 0 : CCU_IF(chunkSize_[chkId] == 0) { LocalPost(locMask_, 1 << rmtId); }
262 0 : CCU_IF(chunkSize_[chkId] != 0)
263 : {
264 0 : uint16_t transId = rmtId < localId_ ? rmtId : rmtId - 1;
265 0 : ReadReduce(
266 0 : *transports[transId], dst, src, chunkSize_[chkId], dataType_, reduceOp_, locMask_, 1 << rmtId);
267 0 : }
268 : }
269 0 : LocalWait(locMask_, allBit);
270 : }
271 0 : HCCL_INFO("[CcuContextReduceMeshMem2Mem2D] Reduce Step2 ends");
272 0 : }
273 :
274 0 : void CcuContextReduceMeshMem2Mem2D::Algorithm()
275 : {
276 0 : HCCL_INFO("[CcuContextReduceMeshMem2Mem2D] ReduceMeshMem2Mem2D run");
277 0 : InitResources();
278 0 : LoadArgs();
279 0 : PreSync(); // 前同步
280 0 : if (rankId_ == rootId_ || (dimId_[1] == rootDimId_[1] && axisId_ == Y_AXIS_ID)
281 0 : || (dimId_[0] == rootDimId_[0] && axisId_ == X_AXIS_ID)) {
282 : // 与root同行的元素要在Y方向规约 同列元素要在X方向规约
283 0 : ReduceStep1();
284 : }
285 0 : AxisSync(0);
286 0 : PostSync(CKE_IDX_3);
287 0 : AxisSync(1);
288 0 : if (rankId_ == rootId_) { // 第二步只有root进行readreduce
289 0 : ReduceStep2();
290 : }
291 0 : AxisSync(0);
292 0 : PostSync(CKE_IDX_0);
293 0 : AxisSync(1);
294 0 : }
295 :
296 0 : std::vector<uint64_t> CcuContextReduceMeshMem2Mem2D::CalMeshChunkSlice(uint64_t dataSize, uint64_t sliceNum)
297 : {
298 0 : uint64_t dataCount = dataSize / DataTypeSizeGet(dataType_);
299 0 : uint64_t bigDataSliceNum = dataCount % sliceNum;
300 0 : uint64_t bigDataSliceSize = (dataCount / sliceNum + 1) * DataTypeSizeGet(dataType_);
301 0 : uint64_t smallDataSliceNum = sliceNum - dataCount % sliceNum;
302 0 : uint64_t smallDataSliceSize = dataCount / sliceNum * DataTypeSizeGet(dataType_);
303 0 : return {bigDataSliceNum, bigDataSliceSize, smallDataSliceNum, smallDataSliceSize};
304 : }
305 :
306 0 : std::vector<uint64_t> CcuContextReduceMeshMem2Mem2D::GeneArgs(const CcuTaskArg& arg)
307 : {
308 0 : const CcuTaskArgReduceMeshMem2Mem2D* taskArg = dynamic_cast<const CcuTaskArgReduceMeshMem2Mem2D*>(&arg);
309 0 : if (taskArg == nullptr) {
310 0 : THROW<NullPtrException>(StringFormat("CcuTaskArgReduceMeshMem2Mem2D::taskArg ptr is null"));
311 : }
312 0 : uint64_t inputAddr = taskArg->inputAddr_;
313 0 : uint64_t outputAddr = taskArg->outputAddr_;
314 0 : uint64_t tokenInfo = taskArg->token_;
315 0 : uint64_t xAxisSize = taskArg->xAxisSize_;
316 0 : uint64_t yAxisSize = taskArg->yAxisSize_;
317 0 : uint64_t yAxisOffset = xAxisSize;
318 0 : auto xAxisGoSize = CalGoSize(xAxisSize);
319 0 : auto yAxisGoSize = CalGoSize(yAxisSize);
320 0 : std::vector<uint64_t> processReturn = {inputAddr, outputAddr, tokenInfo, xAxisSize, yAxisSize, yAxisOffset};
321 0 : HCCL_INFO(
322 : "[CcuContextReduceMeshMem2Mem2D] ReduceMeshMem2Mem2D inputAddr [%llu] outputAddr [%llu] "
323 : "xAxisSize [%llu] yAxisSize [%llu],yAxisOffset[%llu],",
324 : inputAddr, outputAddr, xAxisSize, yAxisSize, yAxisOffset);
325 : // mesh chunk for xslicesize
326 0 : std::vector<uint64_t> xChunkVec = CalMeshChunkSlice(xAxisSize, localSize_ - 1);
327 0 : for (uint64_t i = 0; i < xChunkVec[0]; i++) {
328 0 : processReturn.push_back(xChunkVec[1]);
329 : }
330 0 : for (uint64_t i = 0; i < xChunkVec[2]; i++) {
331 0 : processReturn.push_back(xChunkVec[3]);
332 : }
333 : // mesh chunk for yslicesize
334 0 : std::vector<uint64_t> yChunkVec = CalMeshChunkSlice(yAxisSize, localSize_ - 1);
335 0 : for (uint64_t i = 0; i < yChunkVec[0]; i++) {
336 0 : processReturn.push_back(yChunkVec[1]);
337 : }
338 0 : for (uint64_t i = 0; i < yChunkVec[2]; i++) {
339 0 : processReturn.push_back(yChunkVec[3]);
340 : }
341 : // for gosize
342 0 : processReturn.insert(processReturn.end(), xAxisGoSize.begin(), xAxisGoSize.end());
343 0 : processReturn.insert(processReturn.end(), yAxisGoSize.begin(), yAxisGoSize.end());
344 0 : return processReturn;
345 0 : }
346 : } // namespace Hccl
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