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數(shù)據(jù)中心智能調(diào)度關(guān)鍵技術(shù)與應(yīng)用 讀者對象:本書適合從事數(shù)據(jù)中心、云計算、大數(shù)據(jù)及人工智能領(lǐng)域的技術(shù)研發(fā)人員、工程師,以及高校師生參考使用,為數(shù)據(jù)中心智能化管理提供全面的技術(shù)支持和實踐指南。 ![]()
本書系統(tǒng)性地探討了數(shù)據(jù)中心智能調(diào)度的核心技術(shù)與實際應(yīng)用,涵蓋數(shù)據(jù)中心和云計算概述、大數(shù)據(jù)處理的技術(shù)要點,以及人工智能平臺的資源調(diào)度方法等內(nèi)容。同時,書中深入解析了云服務(wù)負載預(yù)測方法、可再生能源的自適應(yīng)管理方法、基于虛擬機整合的自適應(yīng)節(jié)能調(diào)度方法,以及MapReduce和Spark調(diào)度方法的實際應(yīng)用。此外,本書重點介紹了TensorFlow的高效分布式并行算法,以及基于深度學(xué)習(xí)和模仿學(xué)習(xí)的任務(wù)完工時間優(yōu)化調(diào)度,為研究人員和工程師提供了創(chuàng)新性的解決方案和理論指導(dǎo)。本書適合從事數(shù)據(jù)中心、云計算、大數(shù)據(jù)及人工智能領(lǐng)域的技術(shù)研發(fā)人員、工程師,以及高校師生參考使用,為數(shù)據(jù)中心智能化管理提供全面的技術(shù)支持和實踐指南。
田文洪,電子科技大學(xué)教授、博導(dǎo),美國北卡羅萊納州立大學(xué)(NCSU)計算機科學(xué)專業(yè)博士,F(xiàn)任電子科技大學(xué)先進計算實驗室主任。研究方向包括云計算與AI的計算資源優(yōu)化調(diào)度、AI大模型訓(xùn)練和推理優(yōu)化、基于深度學(xué)習(xí)的自然語言處理和圖像識別及其應(yīng)用,在結(jié)合NP難題于資源調(diào)度領(lǐng)域做出創(chuàng)新貢獻。中國計算機學(xué)會(CCF)杰出會員、IEEE Senior Member(高級會員);入選中科院首批“西部之光”人才計劃、成都市特聘專家(蓉漂計劃)和電子科技大學(xué)“星火計劃”。已培養(yǎng)研究生120余名(其中博士生20余名);發(fā)表高水平學(xué)術(shù)論文150余篇,主編中英文專著7部;主持國家級、省市級和橫向項目20余項;近年來申請發(fā)明專利50余項,獲得中國發(fā)明專利授權(quán)20余項、美國專利授權(quán)2項。在產(chǎn)學(xué)研用領(lǐng)域深耕20余年,產(chǎn)生了良好的社會和經(jīng)濟效益,獲2023年華為公司難題揭榜“火花獎”(電子科技大學(xué)九位獲獎?wù)咧唬┑泉勴椂鄠。徐敏賢,中國科學(xué)院深圳先進技術(shù)研究院副研究員、博士生導(dǎo)師。博士畢業(yè)于澳大利亞墨爾本大學(xué)。主要研究方向為分布式和云計算系統(tǒng),已發(fā)表論文70余篇, 3篇入選ESI高被引論文,申請PCT/發(fā)明專利20余項。入選中國科學(xué)院青年國際合作人才庫核心骨干、廣東省海外博士后人才、深圳市海外高層次人才。博士畢業(yè)論文獲得2019 IEEE Technical Committee on Scalable Computing(TCSC)頒發(fā)的優(yōu)秀博士畢業(yè)論文獎,獲得2023 IEEE TCSC青年學(xué)者獎。主持和聯(lián)合主持國家級、省部級、市級、行業(yè)代表性企業(yè)項目20余項。現(xiàn)為IEEE高級會員,CCF高級會員。薛瑞尼,電子科技大學(xué)計算機學(xué)院副教授, 2009年在清華大學(xué)獲得計算機科學(xué)與技術(shù)博士學(xué)位,2010年香港科技大學(xué)訪問學(xué)者。主要研究方向為分布式存儲、大數(shù)據(jù)和人工智能。近年來在國內(nèi)外學(xué)術(shù)期刊會議發(fā)表論文40多篇,先后從事科研項目10多項,其中主持國家自然科學(xué)基金項目2項,國家自然基金重點項目子課題2項,國家自然基金聯(lián)合項目子課題1項。研究成果在螞蟻集團、滴滴出行等企業(yè)的生產(chǎn)系統(tǒng)或產(chǎn)品中部署,授權(quán)專利20余項。曾獲中國電子學(xué)會電子信息科技一等獎、高校科研優(yōu)秀成果科技進步一等獎。
第1章 數(shù)據(jù)中心概述 ······································································.1
1.1 數(shù)據(jù)中心簡介 ····················································································.2 1.1.1 什么是數(shù)據(jù)中心 ·········································································.2 1.1.2 數(shù)據(jù)中心的需求和挑戰(zhàn) ································································.4 1.2 云計算數(shù)據(jù)中心資源調(diào)度需求分析 ·························································.4 1.2.1 技術(shù)需求 ··················································································.4 1.2.2 技術(shù)目標(biāo) ··················································································.5 1.3 云計算數(shù)據(jù)中心資源調(diào)度研究進展 ·························································.5 1.4 云計算數(shù)據(jù)中心資源調(diào)度方案分析 ·························································.6 1.4.1 Google解決方案 ········································································.6 1.4.2 Amazon解決方案 ·······································································.7 1.4.3 IBM解決方案 ············································································.8 1.4.4 HP解決方案··············································································10 1.4.5 VMware解決方案 ·······································································10 1.4.6 阿里云解決方案 ·········································································12 1.4.7 華為云解決方案 ·········································································14 1.4.8 其他廠家解決方案 ······································································15 1.5 云計算數(shù)據(jù)中心資源調(diào)度標(biāo)準(zhǔn)進展 ·························································17 1.6 云資源管理調(diào)度關(guān)鍵技術(shù)及研究熱點 ······················································18 本章小結(jié) ·································································································20 思考題·····································································································21 參考文獻 ·································································································21 第2章 云計算概述 ········································································.25 2.1 云計算的發(fā)展背景 ··············································································26 2.2 云計算是集大成者 ··············································································28 2.2.1 并行計算 ················································································.28 2.2.2 網(wǎng)格計算 ················································································.29 2.2.3 效用計算 ················································································.29 2.2.4 普適計算 ················································································.30 2.2.5 軟件即服務(wù) ·············································································.30 2.2.6 虛擬化技術(shù) ·············································································.31 2.3 云計算的驅(qū)動因素 ············································································.31 2.3.1 云計算的發(fā)展現(xiàn)狀和趨勢 ···························································.33 2.3.2 云計算應(yīng)用初步分類 ·································································.35 2.4 云計算產(chǎn)業(yè)鏈中的不同角色 ································································.36 2.5 云計算的主要特征和技術(shù)挑戰(zhàn) ·····························································.37 2.5.1 云計算的主要特征 ····································································.37 2.5.2 挑戰(zhàn)性問題 ·············································································.38 本章小結(jié) ································································································.46 思考題 ···································································································.46 參考文獻 ································································································.46 第3章 大數(shù)據(jù)處理 ········································································.51 3.1 大數(shù)據(jù)的發(fā)展背景及定義 ···································································.52 3.2 大數(shù)據(jù)問題 ······················································································.55 3.2.1 速度方面的問題 ·······································································.55 3.2.2 種類及架構(gòu)問題 ·······································································.56 3.2.3 體量及靈活性問題 ····································································.56 3.2.4 成本問題 ················································································.57 3.2.5 價值挖掘問題 ··········································································.57 3.2.6 存儲及安全問題 ·······································································.58 3.2.7 互聯(lián)互通與數(shù)據(jù)共享問題 ···························································.59 3.3 大數(shù)據(jù)與云計算的辯證關(guān)系 ································································.60 3.4 大數(shù)據(jù)技術(shù) ······················································································.61 3.4.1 基礎(chǔ)架構(gòu)支持 ··········································································.62 3.4.2 數(shù)據(jù)采集 ················································································.64 3.4.3 數(shù)據(jù)存儲 ················································································.65 3.4.4 數(shù)據(jù)計算 ················································································.68 3.4.5 數(shù)據(jù)展現(xiàn)與交互 ·······································································.73 本章小結(jié) ································································································.75 思考題 ···································································································.76 參考文獻 ································································································.76 第4章 人工智能平臺的資源調(diào)度概述 ················································.78 4.1 引言 ·································································································79 4.2 深度學(xué)習(xí)的分布式并行訓(xùn)練系統(tǒng)架構(gòu) ······················································79 4.3 深度學(xué)習(xí)的分布式并行策略 ··································································81 4.3.1 深度學(xué)習(xí)的基礎(chǔ)概念 ···································································82 4.3.2 分布式并行訓(xùn)練算法 ···································································82 4.3.3 研究現(xiàn)狀分析 ············································································85 4.4 分布式并行訓(xùn)練的時效分析 ··································································91 本章小結(jié) ·································································································96 思考題·····································································································96 參考文獻 ·································································································97 第5章 基于深度學(xué)習(xí)的云服務(wù)負載預(yù)測方法 ·······································.99 5.1 引言 ······························································································.100 5.2 相關(guān)工作 ························································································.101 5.2.1 基于回歸方法的云服務(wù)負載預(yù)測方法···········································.101 5.2.2 基于學(xué)習(xí)的云服務(wù)負載預(yù)測方法 ·················································.102 5.2.3 討論分析 ···············································································.103 5.3 系統(tǒng)模型 ························································································.104 5.4 esDNN:基于高效監(jiān)督學(xué)習(xí)的深度神經(jīng)網(wǎng)絡(luò) ··········································.106 5.4.1 多元時間序列預(yù)測的滑動窗口 ····················································.106 5.4.2 esDNN算法 ···········································································.109 5.5 性能測試 ························································································.112 5.5.1 數(shù)據(jù)集和環(huán)境配置 ···································································.112 5.5.2 與基于無監(jiān)督學(xué)習(xí)方法的比較 ····················································.113 5.5.3 與基于神經(jīng)網(wǎng)絡(luò)方法的比較 ·······················································.114 5.5.4 與其他方面的比較 ···································································.118 本章小結(jié) ······························································································.119 思考題··································································································.120 參考文獻 ······························································································.120 第6章 云應(yīng)用程序和可再生能源的自適應(yīng)管理方法 ····························.123 6.1 引言 ······························································································.124 6.2 相關(guān)工作 ························································································.125 6.2.1 DVFS和虛擬機整合·································································.125 6.2.2 Brownout ···············································································.126 6.2.3 數(shù)據(jù)中心冷卻系統(tǒng)的整體管理 ····················································.126 6.2.4 可再生能源 ············································································.126 6.3 系統(tǒng)模型 ························································································.127 6.4 問題建模 ························································································.129 6.4.1 功率消耗 ···············································································.129 6.4.2 工作負載模型 ·········································································.130 6.4.3 優(yōu)化目標(biāo) ···············································································.131 6.5 根據(jù)可再生資源進行調(diào)度決策 ····························································.132 6.5.1 Green-Aware 調(diào)度算法 ·····························································.132 6.5.2 交互式工作負載的Brownout算法 ···············································.133 6.5.3 批處理工作負載的延遲算法 ·······················································.134 6.5.4 主機調(diào)度 ···············································································.135 6.5.5 可再生能源預(yù)測 ······································································.136 6.6 原型系統(tǒng)的實現(xiàn) ··············································································.137 6.7 性能評估 ························································································.139 6.7.1 環(huán)境設(shè)置 ···············································································.140 6.7.2 工作負載 ···············································································.140 6.7.3 應(yīng)用 ·····················································································.141 6.7.4 結(jié)果 ·····················································································.141 本章小結(jié) ·······························································································.145 思考題 ··································································································.145 參考文獻 ·······························································································.146 第7章 云計算環(huán)境下基于虛擬機整合的自適應(yīng)節(jié)能調(diào)度 ······················.149 7.1 緒論 ······························································································.150 7.2 虛擬機整合技術(shù) ··············································································.150 7.3 相關(guān)研究工作 ··················································································.152 7.4 問題定義 ························································································.153 7.5 數(shù)據(jù)中心能耗模型 ···········································································.154 7.5.1 服務(wù)器功耗模型 ······································································.154 7.5.2 服務(wù)器能耗模型 ······································································.155 7.5.3 云數(shù)據(jù)中心總能耗模型 ·····························································.156 7.5.4 數(shù)據(jù)中心節(jié)能調(diào)度下限 ·····························································.156 7.6 SAVE算法描述 ···············································································.158 7.6.1 概述 ·····················································································.158 7.6.2 分配算法 ···············································································.159 7.6.3 遷移算法 ···············································································.161 7.7 實驗驗證與分析 ··············································································.165 7.7.1 實驗準(zhǔn)備 ···············································································.165 7.7.2 數(shù)據(jù)準(zhǔn)備 ···············································································.167 7.7.3 基線方法 ···············································································.167 7.7.4 結(jié)果分析 ···············································································.169 本章小結(jié) ······························································································.175 思考題··································································································.175 參考文獻 ······························································································.175 第8章 MapReduce模型中數(shù)據(jù)傾斜問題的算法 ·································.177 8.1 緒論 ······························································································.178 8.1.1 背景及意義 ············································································.178 8.1.2 研究現(xiàn)狀 ···············································································.179 8.1.3 研究內(nèi)容 ···············································································.180 8.2 數(shù)據(jù)傾斜相關(guān)理論研究 ·····································································.181 8.2.1 數(shù)據(jù)傾斜 ···············································································.181 8.2.2 算法介紹 ···············································································.183 8.2.3 算法綜合對比 ·········································································.190 8.3 多任務(wù)數(shù)據(jù)傾斜調(diào)度算法設(shè)計 ····························································.193 8.3.1 問題描述與建模 ······································································.193 8.3.2 Revised Johnson1954算法(RJA) ··············································.195 8.3.3 離線多任務(wù)調(diào)度算法 ································································.199 8.3.4 在線多任務(wù)調(diào)度算法 ································································.201 8.4 單任務(wù)數(shù)據(jù)傾斜算法設(shè)計 ··································································.203 8.4.1 YarnTune概述 ·········································································.203 8.4.2 檢測數(shù)據(jù)傾斜 ·········································································.206 8.4.3 YarnTune核心功能 ··································································.208 8.5 系統(tǒng)測試和分析 ··············································································.212 8.5.1 軟硬件測試環(huán)境 ······································································.212 8.5.2 多任務(wù)數(shù)據(jù)傾斜測試 ································································.212 8.5.3 單任務(wù)數(shù)據(jù)傾斜測試 ································································.217 本章小結(jié) ······························································································.220 思考題··································································································.221 參考文獻 ······························································································.221 第9章 Spark中的數(shù)據(jù)均衡分配算法研究 ·········································.223 9.1 Spark設(shè)計思想 ················································································.224 9.1.1 Spark概述 ·············································································.224 9.1.2 Spark計算模型 ·······································································.225 9.1.3 Spark整體架構(gòu) ·······································································.226 9.2 Spark數(shù)據(jù)存儲體系 ··········································································.227 9.2.1 存儲整體架構(gòu) ·········································································.227 9.2.2 數(shù)據(jù)寫入過程 ·········································································.228 9.2.3 數(shù)據(jù)讀取過程 ·········································································.229 9.3 Spark Shuffle分析 ············································································.230 9.3.1 Shuffle概述 ············································································.230 9.3.2 Shuffle寫操作 ·········································································.231 9.3.3 Shuffle讀操作 ·········································································.232 9.4 Spark分區(qū)方法 ················································································.233 9.4.1 HashPartition分區(qū) ····································································.233 9.4.2 RangePartition分區(qū) ··································································.234 9.5 問題描述與建模 ··············································································.235 9.5.1 相關(guān)定義 ···············································································.235 9.5.2 問題建模 ···············································································.236 9.6 數(shù)據(jù)均衡分配算法整體設(shè)計 ·······························································.237 9.6.1 抽樣算法 ···············································································.238 9.6.2 數(shù)據(jù)均衡分區(qū)算法 ···································································.240 9.6.3 權(quán)重調(diào)整算法 ·········································································.242 9.6.4 任務(wù)分配算法 ·········································································.245 9.7 算法復(fù)雜度分析 ··············································································.246 9.8 MRFair概述 ···················································································.246 9.8.1 MRFair的目標(biāo)與特征 ·······························································.246 9.8.2 MRFair系統(tǒng)架構(gòu) ·····································································.247 9.8.3 MRFair數(shù)據(jù)均衡分配示例 ·························································.248 9.9 MRFair傾斜檢測時機及算法 ······························································.249 9.9.1 MRFair傾斜檢測時機 ·······························································.249 9.9.2 MRFair傾斜檢測算法 ·······························································.250 9.10 MRFair數(shù)據(jù)重新分配時機及算法 ······················································.250 9.10.1 MRFair數(shù)據(jù)重新分配時機 ·······················································.250 9.10.2 MRFair數(shù)據(jù)重新分配算法 ·······················································.251 9.11 MRFair核心模塊 ············································································.253 9.12 系統(tǒng)測試環(huán)境 ················································································.255 9.12.1 軟硬件測試環(huán)境 ·····································································.255 9.12.2 測試數(shù)據(jù) ··············································································.256 9.12.3 對比算法或系統(tǒng) ·····································································.257 9.12.4 評價指標(biāo) ··············································································.257 9.13 Reduce Partition數(shù)據(jù)均衡分配算法測試 ··············································.257 9.13.1 WordCount基準(zhǔn)測試 ·······························································.257 9.13.2 Sort基準(zhǔn)測試 ········································································.260 9.14 MRFair數(shù)據(jù)均衡分配算法測試 ·························································.263 9.14.1 WordCount基準(zhǔn)測試 ·······························································.263 9.14.2 Sort基準(zhǔn)測試 ········································································.265 本章小結(jié) ······························································································.266 思考題··································································································.267 參考文獻 ······························································································.267 第10章 深度學(xué)習(xí)框架TensorFlow的高效分布式并行算法研究 ·············.269 10.1 分布式并行算法的背景及意義 ···························································.270 10.1.1 問題背景 ··············································································.270 10.1.2 研究意義 ··············································································.271 10.2 研究現(xiàn)狀及內(nèi)容 ·············································································.272 10.2.1 研究現(xiàn)狀 ··············································································.272 10.2.2 研究內(nèi)容 ··············································································.272 10.3 深度學(xué)習(xí)理論研究 ··········································································.273 10.3.1 大數(shù)據(jù)與云計算 ····································································.273 10.3.2 機器學(xué)習(xí) ··············································································.274 10.3.3 深度學(xué)習(xí) ··············································································.275 10.4 TensorFlow深度學(xué)習(xí)框架研究 ··························································.277 10.4.1 TensorFlow系統(tǒng)架構(gòu) ······························································.277 10.4.2 TensorFlow數(shù)據(jù)流圖 ······························································.280 10.4.3 TensorFlow會話管理 ······························································.281 10.4.4 TensorFlow分布式執(zhí)行 ···························································.282 10.4.5 TensorFlow數(shù)據(jù)輸入 ······························································.283 10.5 TensorFlow分布式架構(gòu)分析 ·····························································.285 10.5.1 TensorFlow遠程調(diào)用 ······························································.285 10.5.2 現(xiàn)有TensorFlow分布式模型 ····················································.286 10.6 優(yōu)化算法設(shè)計與實現(xiàn) ·······································································.289 10.6.1 數(shù)據(jù)并行上的優(yōu)化 ·································································.289 10.6.2 模型并行上的優(yōu)化 ·································································.297 10.7 實驗環(huán)境配置 ················································································.304 10.7.1 硬件環(huán)境 ··············································································.304 10.7.2 軟件環(huán)境 ··············································································.304 10.7.3 實驗對象 ··············································································.305 10.7.4 實驗數(shù)據(jù) ··············································································.305 10.8 實驗結(jié)果展示與分析 ·······································································.307 10.8.1 數(shù)據(jù)并行算法測試··································································.307 10.8.2 模型并行算法測試··································································.312 本章小結(jié) ·······························································································.314 思考題 ··································································································.314 參考文獻 ·······························································································.314 第11章 基于深度強化學(xué)習(xí)和模仿學(xué)習(xí)的任務(wù)完工時間優(yōu)化調(diào)度 ···········.317 11.1 任務(wù)調(diào)度 ······················································································.318 11.2 相關(guān)研究 ······················································································.321 11.3 云資源調(diào)度問題定義 ·······································································.322 11.4 調(diào)度方案 ······················································································.327 11.4.1 DeepRM_Online介紹 ······························································.327 11.4.2 強化學(xué)習(xí)模型 ········································································.328 11.4.3 深度強化學(xué)習(xí)訓(xùn)練算法····························································.330 11.5 算法分析 ······················································································.333 11.6 實驗分析與驗證 ·············································································.337 11.6.1 實驗準(zhǔn)備 ··············································································.337 11.6.2 數(shù)據(jù)準(zhǔn)備 ··············································································.337 11.6.3 基線算法 ··············································································.338 11.6.4 結(jié)果分析 ··············································································.339 本章小結(jié) ·······························································································.341 思考題 ··································································································.341 參考文獻 ·······························································································.342 第12章 總結(jié)與展望 ······································································.345 12.1 綠色節(jié)能數(shù)據(jù)中心的綜合解決方案·····················································.346 12.2 多數(shù)據(jù)中心(多調(diào)度域)的調(diào)度策略和算法動態(tài)可選擇 ·························.348 12.3 支持深度學(xué)習(xí)模型的分布式并行調(diào)度 ·················································.349 12.4 從基礎(chǔ)資源調(diào)度拓展到應(yīng)用任務(wù)調(diào)度 ·················································.350 參考文獻 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