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 <ios>
12 : #include <iostream>
13 :
14 : #include "log.h"
15 :
16 : #include "ccu_temp_reduce_mesh_1D_mem2mem.h"
17 : #include "alg_data_trans_wrapper.h"
18 : #include "ccu_instruction_reduce_mesh1d_mem2mem.h"
19 : #include "ccu_rank_group.h"
20 : #include "ccu_ctx_creator_registry.h"
21 : #include "ccu_context_reduce_mesh1d_mem2mem.h"
22 :
23 : namespace Hccl {
24 :
25 : static CcuInstRegister<CcuContextReduceMeshMem2Mem1D> registrarReduce(CcuInstType::CCU_REDUCE_MESH_1D_MEM2MEM);
26 :
27 0 : CcuTempReduceMeshMem2Mem1D::CcuTempReduceMeshMem2Mem1D(
28 : const RankId virtualRank, const u32 tempRankSize, const std::vector<std::vector<RankId>>& tempVTopo,
29 0 : const std::map<RankId, u32>& tempVirtRankMap)
30 0 : : CcuAlgTemplateBase(virtualRank, tempRankSize, tempVTopo, tempVirtRankMap)
31 0 : {}
32 :
33 0 : CcuTempReduceMeshMem2Mem1D::~CcuTempReduceMeshMem2Mem1D() {}
34 :
35 0 : void CcuTempReduceMeshMem2Mem1D::InitReduceInfo(const ReduceOp& reduceOp, const DataType& dataType)
36 : {
37 0 : reduceOp_ = reduceOp;
38 0 : dataType_ = dataType;
39 0 : }
40 :
41 0 : HcclResult CcuTempReduceMeshMem2Mem1D::CalcRes(AlgTempResReq& tempResReq)
42 : {
43 0 : tempResReq.queNum = 1;
44 0 : tempResReq.streamNum = tempResReq.queNum + 1; // 多申请一个 stream 给 ccuInsGroup
45 0 : HCCL_INFO("[CalcRes] tempResReq.queNum[%u]", tempResReq.queNum);
46 0 : CHK_RET(CalcResLinksMesh(myRank_, tempRankSize_, tempVTopo_, linkNumBtwPeers_, tempResReq));
47 0 : return HcclResult::HCCL_SUCCESS;
48 : }
49 :
50 0 : HcclResult CcuTempReduceMeshMem2Mem1D::GenExtIns(
51 : const TempFuncs& tempFuncs, const TemplateDataParams& templateDataParams, const ResLinks& tempLinks,
52 : std::vector<InsQuePtr>& tempInsQues)
53 : {
54 0 : CHK_PRT_RET(
55 : tempInsQues.empty(), HCCL_ERROR("[CcuTempReduceMeshMem2Mem1D] empty queue"), HcclResult::HCCL_E_INTERNAL);
56 0 : CHK_PTR_NULL(tempInsQues[0]);
57 :
58 0 : buffInfo_ = templateDataParams.buffInfo;
59 0 : opMode_ = tempFuncs.opMode;
60 0 : CcuInstructionReduceMeshMem2Mem1D ccuIns;
61 0 : std::vector<uint64_t> dimSize;
62 0 : dimSize.push_back(tempRankSize_);
63 :
64 0 : uint32_t rankId = myRank_;
65 0 : uint32_t rootId = tempVirtRankMap_[rootId_];
66 :
67 0 : const CollAlgOperator& op = op_;
68 0 : const std::vector<std::vector<RankId>>& tempVTopo = tempVTopo_;
69 : uint64_t token;
70 0 : CHK_RET(GetToken(op_, token));
71 0 : uint64_t inputAddr = BufferTypeToAddr(buffInfo_.inBuffType) + buffInfo_.inBuffBaseOff;
72 0 : uint64_t outputAddr = BufferTypeToAddr(buffInfo_.outBuffType) + buffInfo_.outBuffBaseOff;
73 0 : uint64_t repeatNum = templateDataParams.repeatNum;
74 0 : uint64_t inputRepeatStride = templateDataParams.inputRepeatStride;
75 0 : uint64_t outputRepeatStride = templateDataParams.outputRepeatStride;
76 0 : uint64_t normalSliceSize = templateDataParams.sliceSize;
77 0 : uint64_t lastSliceSize = templateDataParams.tailSize;
78 0 : uint64_t repeatNumVar = UINT64_MAX - repeatNum;
79 :
80 : // 数据切分为sliceNum块,当数据量不能均匀切分时,后面smallDataSliceNum个数据块比前面bigDataSliceNum个数据块每块少1个数据
81 0 : uint64_t sliceNum = tempRankSize_ - 1;
82 0 : uint64_t sliceSize = templateDataParams.sliceSize; // 获取本rank需要处理的数据量
83 0 : uint64_t sliceCount = sliceSize / DataTypeSizeGet(op_.dataType);
84 :
85 0 : uint64_t bigDataSliceNum = sliceCount % sliceNum;
86 0 : uint64_t bigDataSliceSize = (sliceCount / sliceNum + 1) * DataTypeSizeGet(op_.dataType);
87 0 : uint64_t smallDataSliceNum = sliceNum - sliceCount % sliceNum;
88 0 : uint64_t smallDataSliceSize = sliceCount / sliceNum * DataTypeSizeGet(op_.dataType);
89 :
90 0 : ccuIns.Init(
91 0 : tempVirtRankMap_[myRank_], rootId, op, tempVTopo, inputAddr, outputAddr, token, bigDataSliceNum,
92 : bigDataSliceSize, smallDataSliceNum, smallDataSliceSize, inputRepeatStride, outputRepeatStride, normalSliceSize,
93 : lastSliceSize, repeatNumVar);
94 :
95 0 : HCCL_INFO(
96 : "[CcuTempReduceMeshMem2Mem1D] Run Init: rankId[%u], rootId[%u], inputAddr[%llu], outputAddr[%llu],"
97 : "bigDataSliceNum[%llu], bigDataSliceSize[%llu], smallDataSliceNum[%llu], smallDataSliceSize[%llu],"
98 : "inputRepeatStride[%llu], outputRepeatStride[%llu], normalSliceSize[%llu], lastSliceSize[%llu], "
99 : "repeatNumVar[%llu]",
100 : rankId, rootId, inputAddr, outputAddr, bigDataSliceNum, bigDataSliceSize, smallDataSliceNum, smallDataSliceSize,
101 : inputRepeatStride, outputRepeatStride, normalSliceSize, lastSliceSize, repeatNumVar);
102 :
103 0 : std::vector<LinkData> links;
104 0 : for (auto& pair : tempLinks) {
105 0 : if (pair.second.empty()) {
106 0 : continue;
107 : }
108 0 : links.push_back(pair.second[0]);
109 : }
110 0 : HCCL_DEBUG("[CcuTempReduceMeshMem2Mem1D] links.size[%zu]", links.size());
111 0 : ccuIns.SetLinks(links);
112 :
113 0 : RankGroup rankGroup;
114 0 : for (auto& peer : tempVTopo_[0]) {
115 0 : rankGroup.AddRank(peer);
116 : }
117 0 : u32 cntCkeNum = 4;
118 0 : ccuIns.SetCntCkeNum(cntCkeNum);
119 0 : ccuIns.SetRankGroup(rankGroup);
120 0 : HCCL_DEBUG("CcuTempReduceMeshMem2Mem1D is [%s]", ccuIns.Describe().c_str());
121 0 : tempInsQues[0]->Append(std::move(std::make_unique<CcuInstructionReduceMeshMem2Mem1D>(ccuIns)));
122 :
123 0 : return HcclResult::HCCL_SUCCESS;
124 0 : }
125 :
126 0 : HcclResult CcuTempReduceMeshMem2Mem1D::GenExtIns(
127 : const RankGraph* rankGraph, const TemplateInfo& tmpInfo, const std::vector<InsQuePtr>& tempInsQues) const
128 : {
129 : (void)rankGraph;
130 : (void)tmpInfo;
131 : (void)tempInsQues;
132 : // 框架解析aicpuIns,算法的algCompnnetLite在device侧直接调用Run()
133 0 : return HcclResult::HCCL_SUCCESS;
134 : }
135 :
136 : } // namespace Hccl
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