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_scatter_mesh1d_detour.h"
12 : #include "ccu_instruction_reduce_scatter_mesh1d_detour.h"
13 :
14 : namespace Hccl {
15 :
16 : constexpr int INPUT_XN_ID = 0;
17 : constexpr int OUTPUT_XN_ID = 1;
18 : constexpr int TOKEN_XN_ID = 2;
19 : constexpr int CKE_IDX_0 = 0;
20 : constexpr int CKE_IDX_1 = 1;
21 : constexpr int CKE_IDX_2 = 2;
22 : constexpr int CKE_IDX_3 = 3;
23 :
24 0 : CcuContextReduceScatterMeshDetour1D::CcuContextReduceScatterMeshDetour1D(
25 0 : const CcuCtxArg& arg, const std::vector<CcuTransport*>& transports, const CcuTransportGroup& group)
26 0 : : CcuContextAlgBase(arg, transports, group)
27 : {
28 0 : const CcuCtxArgReduceScatterMeshDetour1D* ctxArg = dynamic_cast<const CcuCtxArgReduceScatterMeshDetour1D*>(&arg);
29 0 : if (ctxArg == nullptr) {
30 0 : THROW<NullPtrException>(StringFormat("CcuContextReduceScatterMeshDetour1D::ctxArg ptr is null"));
31 : }
32 0 : rankId_ = ctxArg->rankId_;
33 0 : rankSize_ = ctxArg->dimSize_[0];
34 0 : dataType_ = ctxArg->op_.dataType;
35 0 : outputDataType_ = ctxArg->op_.outputDataType;
36 0 : if (outputDataType_ == DataType::INVALID) {
37 0 : outputDataType_ = dataType_;
38 0 : HCCL_INFO(
39 : "[CcuContextReduceScatterMeshDetour1D] outputDataType is [INVALID], set outputDataType to[%s]",
40 : outputDataType_.Describe().c_str());
41 : }
42 0 : reduceOp_ = ctxArg->op_.reduceOp;
43 0 : singleTransportSize_ = ctxArg->singleTransportSize_;
44 0 : detourPathNum_ = ctxArg->detourPathNum_;
45 0 : pathNumPerPeer_ = ctxArg->pathNumPerPeer_;
46 0 : HCCL_INFO(
47 : "[CcuContextReduceScatterMeshDetour1D] Init, CtxArgs are rankId[%u], rankSize[%u], dataType[%s], "
48 : "outputDataType[%s], reduceOp[%s]",
49 : rankId_, rankSize_, dataType_.Describe().c_str(), outputDataType_.Describe().c_str(),
50 : reduceOp_.Describe().c_str());
51 0 : if (transports.size() == 0 || transports.size() < rankSize_ - 1) {
52 0 : THROW<NullPtrException>(
53 0 : StringFormat("CcuContextReduceScatterMeshDetour1D transports is empty or size is less"));
54 : }
55 0 : HCCL_INFO("[CcuContextReduceScatterMeshDetour1D] transport.size[%zu]", transports.size());
56 0 : for (uint32_t i = 0; i < pathNumPerPeer_; i++) {
57 : // 到每个对端有pathNum个transport，故detourTransport中共有pathNum组
58 0 : detourTransports_.emplace_back(std::vector<CcuTransport*>());
59 : }
60 0 : uint64_t directPathNum = pathNumPerPeer_ - detourPathNum_;
61 0 : for (uint64_t i = 0; i < directPathNum; i++) {
62 : // 有pathNum-detourPathNum组的直连链路，每组重复
63 0 : for (uint32_t j = 0; j < rankSize_ - 1; j++) {
64 0 : detourTransports_[i].emplace_back(transports[j]);
65 : }
66 0 : HCCL_INFO(
67 : "[CcuContextReduceScatterMeshDetour1D] Add directTransports[%llu], size[%zu]", i,
68 : detourTransports_[i].size());
69 : }
70 0 : for (uint32_t i = 0; i < detourPathNum_; i++) {
71 0 : for (uint32_t j = 0; j < rankSize_ - 1; j++) {
72 0 : detourTransports_[i + directPathNum].emplace_back(transports[(i + 1) * (rankSize_ - 1) + j]);
73 0 : detourTransports_[i + directPathNum].emplace_back(
74 0 : transports[(i + 1) * (rankSize_ - 1) + j + detourPathNum_ * (rankSize_ - 1)]);
75 0 : HCCL_INFO(
76 : "detourTransports_ emplace_back sendLink[%u], recvLink[%u]", (i + 1) * (rankSize_ - 1) + j,
77 : (i + 1) * (rankSize_ - 1) + j + detourPathNum_ * (rankSize_ - 1));
78 : }
79 : }
80 0 : }
81 :
82 0 : void CcuContextReduceScatterMeshDetour1D::CreateMultiOpReduceDetour(
83 : DataType& dataType, DataType& outputDataType, ReduceOp& opType)
84 : {
85 0 : moConfig.loopCount = CcuRep::CCU_MS_DEFAULT_LOOP_COUNT;
86 0 : moConfig.msInterleave = pathNumPerPeer_ * rankSize_;
87 0 : if (moRes.executor.size() == 0) {
88 0 : moRes.executor = CreateBlockExecutor(moConfig.loopCount);
89 0 : moRes.maskSignal = CreateBlockMaskSignal(moConfig.loopCount);
90 0 : moRes.ccuBuffer = CreateBlockCcuBuffer(moConfig.loopCount * moConfig.msInterleave);
91 : }
92 0 : std::string loopType = "reduceDetour";
93 0 : if (registeredLoop.find(loopType) != registeredLoop.end()) {
94 0 : return;
95 : }
96 0 : CcuRep::LoopBlock lb(this, loopType + "_loop");
97 : {
98 : // loopblock的形参
99 0 : std::vector<CcuRep::Memory> src;
100 0 : std::vector<CcuRep::Memory> dst;
101 0 : std::vector<CcuRep::Variable> lengths;
102 0 : for (uint32_t i = 0; i < pathNumPerPeer_; i++) {
103 0 : lengths.emplace_back(CreateVariable());
104 0 : dst.emplace_back(CreateMemory());
105 0 : for (uint32_t j = 0; j < rankSize_; j++) {
106 0 : src.emplace_back(CreateMemory());
107 : }
108 : }
109 :
110 0 : lb(src, dst, lengths);
111 0 : std::vector<std::vector<CcuRep::CcuBuffer>> bufs;
112 0 : bufs.resize(pathNumPerPeer_);
113 0 : std::vector<CcuRep::MaskSignal> sems;
114 :
115 0 : for (uint32_t i = 0; i < pathNumPerPeer_; i++) {
116 0 : for (uint32_t j = 0; j < rankSize_; j++) {
117 0 : bufs[i].emplace_back(moRes.ccuBuffer[i * rankSize_ + j]);
118 : }
119 0 : sems.emplace_back(moRes.maskSignal[i]);
120 : }
121 :
122 : // 先读远端直连的到本地MS
123 0 : uint64_t directPathNum = pathNumPerPeer_ - detourPathNum_;
124 0 : for (uint32_t i = 0; i < directPathNum; i++) {
125 0 : for (uint32_t j = 0; j < detourTransports_[i].size(); j++) {
126 0 : if (detourTransports_[i][j] == nullptr) {
127 0 : THROW<CcuApiException>("transport is nullptr");
128 : }
129 0 : Read(*detourTransports_[i][j], bufs[i][j], src[i * rankSize_ + j], lengths[i], sems[i], 1 << j);
130 : }
131 : }
132 : // 再读远端绕路的到本地MS
133 0 : for (uint32_t i = directPathNum; i < pathNumPerPeer_; i++) {
134 0 : for (uint32_t j = 0; j < rankSize_ - 1; j++) {
135 0 : if (detourTransports_[i][j * 2 + 1] == nullptr) { // j * 2 + 1是recvOnly Link
136 0 : THROW<CcuApiException>("transport is nullptr");
137 : }
138 0 : Read(*detourTransports_[i][j * 2 + 1], bufs[i][j], src[i * rankSize_ + j], lengths[i], sems[i], 1 << j);
139 : }
140 : }
141 :
142 0 : for (uint32_t i = 0; i < pathNumPerPeer_; i++) {
143 0 : LocalCopy(
144 0 : bufs[i][rankSize_ - 1], src[i * rankSize_ + rankSize_ - 1], lengths[i], sems[i], 1 << (rankSize_ - 1));
145 : }
146 0 : for (uint32_t i = 0; i < pathNumPerPeer_; i++) {
147 0 : LocalWait(sems[i], (1 << rankSize_) - 1);
148 : }
149 0 : if (rankSize_ > 1) {
150 0 : for (uint32_t i = 0; i < pathNumPerPeer_; i++) {
151 0 : LocalReduce(bufs[i], rankSize_, dataType, outputDataType, opType, sems[i], lengths[i]);
152 0 : LocalWait(sems[i]);
153 : }
154 : }
155 0 : for (uint32_t i = 0; i < pathNumPerPeer_; i++) {
156 0 : LocalCopy(dst[i], bufs[i][0], lengths[i], sems[i]);
157 0 : LocalWait(sems[i]);
158 : }
159 0 : }
160 0 : registeredLoop.insert(loopType);
161 0 : return;
162 0 : }
163 :
164 0 : void CcuContextReduceScatterMeshDetour1D::GroupReduceDetour(
165 : std::vector<CcuRep::Memory>& src, std::vector<CcuRep::Memory>& dst, DataType& dataType, DataType& outputDataType,
166 : ReduceOp& opType)
167 : {
168 0 : CreateMultiOpReduceDetour(dataType, outputDataType, opType);
169 0 : uint32_t interLeave = 8;
170 :
171 0 : CCU_IF(iterNum_ != 0)
172 : {
173 0 : CcuRep::Variable loopParam = CreateVariable();
174 0 : CcuRep::Variable paraCfg = CreateVariable();
175 0 : CcuRep::Variable offsetCfg = CreateVariable();
176 :
177 0 : loopParam = CcuRep::GetLoopParam(
178 0 : 0, singleTransportSize_ * moConfig.loopCount, 0); // 下次迭代的偏移是单次总搬运量*loopNum
179 0 : loopParam += iterNum_; // 加上loop的迭代次数构成完整loop参数
180 0 : paraCfg = CcuRep::GetParallelParam(moConfig.loopCount - 1, 0, 1); // loop固定展开到128个
181 0 : offsetCfg = CcuRep::GetOffsetParam(singleTransportSize_, interLeave, pathNumPerPeer_); // 下一个loop偏移量
182 0 : auto lc = Loop("reduceDetour_loop")(src, dst, lengths_);
183 0 : LoopGroup({lc}, {loopParam}, paraCfg, offsetCfg);
184 0 : }
185 0 : return;
186 0 : }
187 :
188 0 : void CcuContextReduceScatterMeshDetour1D::Algorithm()
189 : {
190 0 : HCCL_INFO("[CcuContextReduceScatterMeshDetour1D] ReduceScatterMeshDetour1D run");
191 0 : uint16_t selfBit = 1 << rankId_;
192 0 : uint16_t allBit = ((1 << rankSize_) - 1) & (~(1 << rankId_));
193 0 : output_.push_back(CreateVariable());
194 : // 初始化资源
195 0 : uint16_t transportIdx = 0;
196 : // 按照rank号从小到大遍历transports，遇到本rank就填充本地资源，否则依次取远端资源，要求给框架返回的Link同样是按顺序排列的
197 0 : for (uint64_t peerId = 0; peerId < rankSize_; peerId++) {
198 0 : if (peerId == rankId_) {
199 0 : input_.push_back(CreateVariable());
200 0 : token_.push_back(CreateVariable());
201 : } else {
202 0 : HCCL_INFO(
203 : "[CcuContextReduceScatterMeshDetour1D] MyRank[%u], PeerId[%llu], TransportId[%u]", rankId_, peerId,
204 : transportIdx);
205 0 : CHK_PRT_RET(
206 : detourTransports_[0][transportIdx] == nullptr,
207 : HCCL_ERROR("[CcuContextReduceScatterMeshDetour1D] Algorithm transport ptr is null"), );
208 0 : input_.push_back(CreateVariable((*detourTransports_[0][transportIdx]), INPUT_XN_ID));
209 0 : token_.push_back(CreateVariable((*detourTransports_[0][transportIdx]), TOKEN_XN_ID));
210 0 : transportIdx++;
211 : }
212 : }
213 0 : offset_ = CreateVariable();
214 0 : iterNum_ = CreateVariable();
215 0 : tailOffset_ = CreateVariable();
216 0 : tailSize_ = CreateVariable();
217 0 : groupOpSize_ = CreateGroupOpSize();
218 0 : for (uint32_t i = 0; i < pathNumPerPeer_; i++) {
219 0 : lengths_.emplace_back(CreateVariable());
220 : }
221 :
222 0 : Load(input_[rankId_]);
223 0 : Load(output_[0]);
224 0 : Load(token_[rankId_]);
225 0 : Load(offset_);
226 0 : Load(iterNum_);
227 0 : Load(tailOffset_);
228 0 : Load(tailSize_);
229 0 : Load(groupOpSize_);
230 0 : for (uint32_t i = 0; i < pathNumPerPeer_; i++) {
231 0 : Load(lengths_[i]);
232 : }
233 :
234 0 : for (auto& t : detourTransports_[0]) {
235 0 : WriteVariableWithSignal(*t, input_[rankId_], INPUT_XN_ID, CKE_IDX_1, selfBit);
236 0 : WriteVariableWithSignal(*t, token_[rankId_], TOKEN_XN_ID, CKE_IDX_3, selfBit);
237 : }
238 :
239 0 : GroupWait(*transportGroup, CKE_IDX_1, allBit);
240 0 : GroupWait(*transportGroup, CKE_IDX_3, allBit);
241 : // 如果是4p*2场景，template里可以都传4k进来，transport和length通过<直连4k>, <直连4k>,
242 : // <绕路4k>这样构造达成数据量2:1的效果
243 :
244 0 : std::vector<CcuRep::Memory> reduceSrc;
245 0 : std::vector<CcuRep::Memory> reduceDst;
246 :
247 : // 为每个直连或绕路transport分别准备reduceSrc与reduceDst
248 0 : for (uint32_t i = 0; i < pathNumPerPeer_; i++) {
249 0 : reduceDst.emplace_back(CreateMemory());
250 0 : for (uint32_t j = 0; j < rankSize_; j++) {
251 0 : reduceSrc.emplace_back(CreateMemory());
252 : }
253 : }
254 :
255 : // reduceDst填充
256 0 : reduceDst[0].addr = output_[0];
257 : // reduceDst[0].addr += offset_;
258 0 : reduceDst[0].token = token_[rankId_];
259 0 : for (uint32_t i = 1; i < pathNumPerPeer_; i++) {
260 0 : reduceDst[i].addr = reduceDst[i - 1].addr + lengths_[i - 1];
261 0 : reduceDst[i].token = token_[rankId_];
262 : }
263 : // 直连transport的reduceSrc填充
264 0 : uint32_t srcId = 0;
265 0 : uint32_t curId = 0;
266 0 : for (uint32_t rankIdx = 0; rankIdx < rankSize_; rankIdx++) {
267 0 : if (rankIdx != rankId_) {
268 0 : curId = srcId;
269 0 : srcId++;
270 : } else {
271 0 : curId = rankSize_ - 1;
272 : }
273 0 : reduceSrc[curId].addr = input_[rankIdx];
274 0 : reduceSrc[curId].token = token_[rankIdx];
275 0 : reduceSrc[curId].addr += offset_;
276 : }
277 : // 绕路transport的reduceSrc相比直连src再做偏移
278 0 : for (uint32_t i = 1; i < pathNumPerPeer_; i++) {
279 0 : for (uint32_t j = 0; j < rankSize_; j++) {
280 0 : reduceSrc[i * rankSize_ + j].addr = reduceSrc[(i - 1) * rankSize_ + j].addr + lengths_[i - 1];
281 0 : reduceSrc[i * rankSize_ + j].token = reduceSrc[(i - 1) * rankSize_ + j].token;
282 : }
283 : }
284 :
285 0 : GroupReduceDetour(reduceSrc, reduceDst, dataType_, outputDataType_, reduceOp_);
286 :
287 : // 余下的尾块用直连Reduce
288 0 : std::vector<CcuRep::Memory> tailSrc;
289 0 : CcuRep::Memory tailDst = CreateMemory();
290 0 : for (uint32_t i = 0; i < rankSize_; i++) {
291 0 : tailSrc.emplace_back(CreateMemory());
292 : }
293 0 : tailDst.addr = output_[0];
294 : // tailDst.addr += offset_;
295 0 : tailDst.addr += tailOffset_;
296 0 : tailDst.token = token_[rankId_];
297 0 : srcId = 0;
298 0 : curId = 0;
299 0 : for (uint32_t rankIdx = 0; rankIdx < rankSize_; rankIdx++) {
300 0 : if (rankIdx != rankId_) {
301 0 : curId = srcId;
302 0 : srcId++;
303 : } else {
304 0 : curId = rankSize_ - 1;
305 : }
306 0 : tailSrc[curId].addr = input_[rankIdx];
307 0 : tailSrc[curId].addr += offset_;
308 0 : tailSrc[curId].addr += tailOffset_;
309 0 : tailSrc[curId].token = token_[rankIdx];
310 : }
311 :
312 0 : GroupReduce(detourTransports_[0], tailDst, tailSrc, groupOpSize_, dataType_, outputDataType_, reduceOp_);
313 :
314 0 : for (auto t : detourTransports_[0]) {
315 0 : RemotePost(*t, CKE_IDX_0, selfBit);
316 : }
317 0 : GroupWait(*transportGroup, CKE_IDX_0, allBit);
318 :
319 0 : HCCL_INFO("[CcuContextReduceScatterMeshDetour1D] ReduceScatterMeshDetour1D end");
320 0 : return;
321 0 : }
322 :
323 0 : std::vector<uint64_t> CcuContextReduceScatterMeshDetour1D::GeneArgs(const CcuTaskArg& arg)
324 : {
325 0 : const CcuTaskArgReduceScatterMeshDetour1D* taskArg = dynamic_cast<const CcuTaskArgReduceScatterMeshDetour1D*>(&arg);
326 0 : if (taskArg == nullptr) {
327 0 : THROW<NullPtrException>(StringFormat("CcuContextReduceScatterMeshDetour1D::taskArg ptr is null"));
328 : }
329 0 : uint64_t inputAddr = taskArg->inputAddr_;
330 0 : uint64_t outputAddr = taskArg->outputAddr_;
331 0 : uint64_t tokenInfo = taskArg->token_;
332 0 : uint64_t offset = taskArg->offset_;
333 0 : uint64_t iterNum = taskArg->iterNum_;
334 0 : uint64_t tailOffset = taskArg->tailOffset_;
335 0 : uint64_t tailSize = taskArg->tailSize_;
336 0 : auto goSize = CalGoSize(tailSize); // ***
337 :
338 0 : HCCL_INFO(
339 : "[CcuContextReduceScatterMeshDetour1D] GeneArgs, taskArg are inputAddr[%llu], outputAddr[%llu], "
340 : "offset[%llu], iterNum[%llu], tailOffset[%llu], tailSize[%llu]",
341 : inputAddr, outputAddr, offset, iterNum, tailOffset, tailSize);
342 : std::vector<uint64_t> sqeArgs = {inputAddr, outputAddr, tokenInfo, offset, iterNum, tailOffset,
343 0 : tailSize, goSize[0], goSize[1], goSize[2], goSize[3]};
344 0 : for (auto len : taskArg->lengths_) {
345 0 : HCCL_INFO("get lengths");
346 0 : sqeArgs.emplace_back(len);
347 : }
348 0 : return sqeArgs;
349 0 : }
350 :
351 : } // namespace Hccl
|
