Topics in Parallel and Distributed Computing: Enhancing the Undergraduate Curriculum: Performance, Concurrency, and Programming on Modern Platforms
暫譯: 平行與分散計算主題：提升本科課程：現代平台上的效能、併發與程式設計

這本書向計算機及計算相關學科的初學本科生介紹現代的平行與分散式程式設計語言和環境，包括 map-reduce、通用圖形處理單元 (GPUs) 以及用於行動應用程式的圖形使用者介面 (GUI)。本書還通過選定的文章指導教師如何將平行與分散式計算主題引入本科課程，包括平行演算法和程式的質量標準、可擴展性、平行性能、容錯性和能效分析。為學生設計的章節作為早期計算核心課程的補充文本材料，學生可以用來學習和練習。插圖、範例以及構建更大概念的小步驟序列也是可以插入現有教學材料中的工具。為教師編寫的章節則以教學層級撰寫，作為嚴謹的參考，包含學習目標、對材料的呈現和使用建議，適用於早期和進階的本科課程。

由於平行與分散式計算 (PDC) 現在滲透到大多數計算活動中，因此在計算機科學 (CS) 和計算機工程 (CE) 課程以及相關計算學科的本科教育中，傳授廣泛的 PDC 技術技能已變得至關重要。本書及本系列的其他書籍旨在解決缺乏適合的教科書支持以將 PDC 相關主題整合進本科課程的需求，特別是在早期課程中。這些章節與 NSF/IEEE-TCPP 平行與分散式計算課程倡議為 CS 和 CE 學生頒布的課程指導方針以及 CS2013 ACM/IEEE 計算機科學課程相一致。

Anshul Gupta is a Principal Research Staff Member in IBM Research AI at IBM T.J. Watson Research Center. His research interests include sparse matrix computations and their applications in optimization and computational sci- ences, parallel algorithms, and graph/combinatorial algo- rithms for scientific computing. He has coauthored several journal articles and conference papers on these topics and a textbook titled "Introduction to Parallel Computing." He is the primary author of Watson Sparse Matrix Package (WSMP), one of the most robust and scalable parallel direct solvers for large sparse systems of linear equations.

Sushil K. Prasad (BTech'85 IIT Kharagpur, MS'86 Washington State, Pullman; PhD'90 Central Florida, Orlando - all in Computer Science/Engineering) is a Professor of Computer Science at Georgia State University and Director of Distributed and Mobile Systems (DiMoS) Lab. Sushil has been honored as an ACM Distinguished Scientist in Fall 2013 for his research on parallel data structures and applications. He was the elected chair of IEEE Technical Committee on Parallel Processing for two terms (2007-11), and received its highest honors in 2012 - IEEE TCPP Outstanding Service Award. Currently, he is leading the NSF-supported IEEE- TCPP curriculum initiative on parallel and distributed computing with a vision to ensure that all computer science and engineering graduates are well-prepared in parallelism through their core courses in this era of multi- and many- cores desktops and handhelds. His current research interests are in Parallel Data Structures and Algorithms, and Computation over Geo-Spatiotemporal Datasets over Cloud, GPU and Multicore Platforms. Sushil is currently a Program Director leading the Office of Advanced Cyberinfrastructure (OAC) Learning and Workforce Development crosscutting programs at U.S. National Science Foundation. H

Arnold L. Rosenberg holds the rank of Distinguished University Professor Emeritus in the School of Computer Science at the University of Massachusetts Amherst. Prior to joining UMass, Rosenberg was a Professor of Computer Science at Duke University from 1981 to 1986, and a Research Staff Member at the IBM Watson Research Center from 1965 to 1981. He has held visiting positions at Yale University and the University of Toronto, as well as research professorships at Colorado State University and Northeastern University. He was a Lady Davis Visiting Professor at the Technion (Israel Institute of Technology) in 1994, and a Fulbright Senior Research Scholar at the University of Paris-South in 2000. Rosenberg's research focuses on developing algorithmic models and techniques to exploit the new modalities of "collaborative computing" (wherein multiple computers cooperate to solve a computational problem) that result from emerging computing technologies. Rosenberg is the author or coauthor of more than 190 technical papers on these and other topics in theoretical computer science and discrete mathematics. He is the coauthor of the research book Graph Separators, with Applications and the author of the textbook The Pillars of Computation Theory: State, Encoding, Nondeterminism; additionally, he has served as coeditor of several books. Rosenberg is a Life Fellow of the ACM, a Life Fellow of the IEEE, a Golden Core member of the IEEE Computer Society, and a member of the Sigma Xi Research Society. Rosenberg received an A.B. in mathematics at Harvard College and an A.M. and Ph.D. in applied mathematics at Harvard University.

Alan Sussman is a Professor in the Department of Computer Science and Institute for Advanced Computer Studies at the University of Maryland. Working with students and other researchers at Maryland and other institutions he has published numerous conference and journal papers and re- ceived several best paper awards in various topics related to software tools for high performance parallel and distributed computing, and has contributed chapters to 6 books. His research interests include peer-to-peer distributed systems, software engineering for high performance computing, and large scale data intensive computing. Software tools he has built with his graduate students have been widely dis- tributed and used in many computational science applica- tions, in areas such as earth science, space science, and med- ical informatics. He is a subject area editor for the Parallel Computing journal and an associate editor for IEEE Trans- actions on Services Computing, and edited a previous book on teaching parallel and distributed computing. He is a founding member of the Center for Parallel and Distributed Computing Curriculum Development and Educational Re- sources (CDER). He received his Ph.D. in computer science from Carnegie Mellon University.

Charles Weems is co-director of the Architecture and Language Implementation lab at the University of Massachusetts. His current research interests include architectures for media and embedded applications, GPU computing, and high precision arithmetic, and he has over 100 conference and journal publications. Previously he led development of two generations of a heterogeneous parallel processor for machine vision, called the Image Understanding Architecture, and co-directed initial work on the Scale compiler that was eventually used for the TRIPS architecture. He is the author of numerous articles, has served on many program committees, chaired the 1997 IEEE CAMP Workshop, the 1999 IEEE Frontiers Symposium, co-chaired IEEE IPDPS in 1999, 2000, and 2013, was general vice-chair for IPDPS from 2001 through 2005, is on the steering committees of EduPar and EduHPC. He has co-authored twenty-eight introductory CS texts. He is a member of ACM, Senior Member of IEEE, a member of the Executive Committee of the IEEE TC on Parallel Processing, has been an editor for IEEE TPDS, Elsevier JPDC, and is an editor with Parallel Computing.

安舒爾·古普塔（Anshul Gupta）是IBM T.J. Watson研究中心IBM Research AI的首席研究員。他的研究興趣包括稀疏矩陣計算及其在優化和計算科學中的應用、並行算法，以及用於科學計算的圖形/組合算法。他共同撰寫了多篇期刊文章和會議論文，並編寫了一本名為《Introduction to Parallel Computing》的教科書。他是Watson Sparse Matrix Package (WSMP)的主要作者，這是針對大型稀疏線性方程組的最穩健且可擴展的並行直接求解器之一。

蘇希爾·K·普拉薩德（Sushil K. Prasad）（BTech'85 IIT Kharagpur, MS'86 Washington State, Pullman; PhD'90 Central Florida, Orlando - 均為計算機科學/工程領域）是喬治亞州立大學的計算機科學教授及分佈式與移動系統（DiMoS）實驗室的主任。蘇希爾因其在並行數據結構及應用方面的研究於2013年秋季被授予ACM傑出科學家榮譽。他曾於2007至2011年兩屆擔任IEEE並行處理技術委員會的選舉主席，並於2012年獲得其最高榮譽 - IEEE TCPP傑出服務獎。目前，他正在領導由NSF支持的IEEE-TCPP課程倡議，專注於並行和分佈式計算，旨在確保所有計算機科學和工程畢業生在這個多核和多核心桌面及手持設備的時代，通過核心課程充分準備好並行計算。他目前的研究興趣包括並行數據結構和算法，以及在雲端、GPU和多核平台上對地理時空數據集的計算。蘇希爾目前是美國國家科學基金會（NSF）高級網絡基礎設施辦公室（OAC）學習和勞動力發展跨領域計劃的項目主任。

阿諾德·L·羅森伯格（Arnold L. Rosenberg）在馬薩諸塞大學阿默斯特分校計算機科學學院擔任榮譽傑出大學教授。在加入UMass之前，羅森伯格於1981年至1986年擔任杜克大學的計算機科學教授，並於1965年至1981年在IBM Watson研究中心擔任研究人員。他曾在耶魯大學和多倫多大學擔任訪問職位，並在科羅拉多州立大學和東北大學擔任研究教授。他於1994年擔任以色列理工學院（Technion）的Lady Davis訪問教授，並於2000年在巴黎南大學擔任富布賴特高級研究學者。羅森伯格的研究專注於開發算法模型和技術，以利用新興計算技術所帶來的“協作計算”（多台計算機協作解決計算問題）的新模式。羅森伯格是超過190篇技術論文的作者或共同作者，這些論文涉及理論計算機科學和離散數學等主題。他是研究書籍《Graph Separators, with Applications》的共同作者，並是教科書《The Pillars of Computation Theory: State, Encoding, Nondeterminism》的作者；此外，他還擔任過幾本書的共同編輯。羅森伯格是ACM的終身會士、IEEE的終身會士、IEEE計算機學會的Golden Core成員，以及Sigma Xi研究學會的成員。羅森伯格在哈佛學院獲得數學學士學位，並在哈佛大學獲得應用數學碩士和博士學位。

艾倫·薩斯曼（Alan Sussman）是馬里蘭大學計算機科學系及高級計算研究所的教授。他與馬里蘭大學及其他機構的學生和研究人員合作，發表了大量會議和期刊論文，並在與高性能並行和分佈式計算相關的各種主題中獲得了幾個最佳論文獎，並為六本書貢獻了章節。他的研究興趣包括點對點分佈式系統、高性能計算的軟體工程以及大規模數據密集型計算。他與研究生共同開發的軟體工具已廣泛分發並應用於許多計算科學應用領域，如地球科學、太空科學和醫療資訊學。他是《Parallel Computing》期刊的主題區域編輯，也是《IEEE Transactions on Services Computing》的副編輯，並編輯過一本關於教學並行和分佈式計算的書籍。他是並行和分佈式計算課程開發及教育資源中心（CDER）的創始成員。他在卡內基梅隆大學獲得計算機科學博士學位。

查爾斯·威姆斯（Charles Weems）是馬薩諸塞大學架構與語言實現實驗室的共同主任。他目前的研究興趣包括媒體和嵌入式應用的架構、GPU計算和高精度算術，並擁有超過100篇會議和期刊出版物。此前，他領導開發了兩代用於機器視覺的異構並行處理器，稱為圖像理解架構，並共同指導了最初的Scale編譯器工作，該編譯器最終用於TRIPS架構。他是多篇文章的作者，曾在許多程序委員會任職，擔任1997年IEEE CAMP研討會、1999年IEEE Frontiers研討會的主席，並於1999、2000和2013年共同主持IEEE IPDPS，從2001年至2005年擔任IPDPS的總副主席，並在EduPar和EduHPC的指導委員會中任職。他共同編寫了二十八本計算機科學入門教材。他是ACM的成員、IEEE的高級會員、IEEE並行處理技術委員會的執行委員會成員，曾擔任IEEE TPDS、Elsevier JPDC的編輯，並擔任《Parallel Computing》的編輯。