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Scalable Parallel Computing by Kai Hwang,Zhiwei Xu Pdf
This book covers four areas of parallel computing: principles, technology, architecture, and programming. It is suitable for professionals and undergraduates taking courses in computer engineering, parallel processing, computer architecture, scaleable computers or distributed computing.
Instructor's Solutions Manual to Accompany Scaladle Parallel Computing, Technology, Architecture and Programming [by] Kai Hwang, Zhiwei Xu by Kwai Hwang,Zhiwei Xu Pdf
Annual Review of Scalable Computing by Yuen Chung Kwong Pdf
This book contains four review articles in the area of scalable computing. Two of the articles discuss methods and tools for the parallel solution of irregular problems, which have been satisfactorily worked out in heterogeneous systems. One surveys the technology and applications of multimedia server clusters, which are playing an increasing role in the current networked environment. An additional article discusses SilkRoad, which adds distributed shared memory capabilities to the Cilk parallel programming system. Once again, the book represents a new set of steps forward in parallel systems. Graduate students, academics and researchers in supercomputing and computer engineering.
Scalable Parallel Programming Applied to H.264/AVC Decoding by Ben Juurlink,Mauricio Alvarez-Mesa,Chi Ching Chi,Arnaldo Azevedo,Cor Meenderinck,Alex Ramirez Pdf
Existing software applications should be redesigned if programmers want to benefit from the performance offered by multi- and many-core architectures. Performance scalability now depends on the possibility of finding and exploiting enough Thread-Level Parallelism (TLP) in applications for using the increasing numbers of cores on a chip. Video decoding is an example of an application domain with increasing computational requirements every new generation. This is due, on the one hand, to the trend towards high quality video systems (high definition and frame rate, 3D displays, etc) that results in a continuous increase in the amount of data that has to be processed in real-time. On the other hand, there is the requirement to maintain high compression efficiency which is only possible with video codes like H.264/AVC that use advanced coding techniques. In this book, the parallelization of H.264/AVC decoding is presented as a case study of parallel programming. H.264/AVC decoding is an example of a complex application with many levels of dependencies, different kernels, and irregular data structures. The book presents a detailed methodology for parallelization of this type of applications. It begins with a description of the algorithm, an analysis of the data dependencies and an evaluation of the different parallelization strategies. Then the design and implementation of a novel parallelization approach is presented that is scalable to many core architectures. Experimental results on different parallel architectures are discussed in detail. Finally, an outlook is given on parallelization opportunities in the upcoming HEVC standard.
Annual Review of Scalable Computing by Yuen Chung Kwong Pdf
This book contains four review articles in the area of scalable computing. Two of the articles discuss methods and tools for the parallel solution of irregular problems, which have been satisfactorily worked out in heterogeneous systems. One surveys the technology and applications of multimedia server clusters, which are playing an increasing role in the current networked environment. An additional article discusses SilkRoad, which adds distributed shared memory capabilities to the Cilk parallel programming system. Once again, the book represents a new set of steps forward in parallel systems. Contents:Parallel Computing Strategies for Irregular AlgorithmsA Runtime Support for Large-Scale Irregular Computing on Clusters and GridsMemory Model Support for Mixed Programming Paradigm in SilkRoadClustered Multimedia Servers: Architectures and Storage Systems Readership: Graduate students, academics and researchers in supercomputing and computer engineering. Keywords:Clusters;Distributed Shared Memory;Heterogeneous Systems;Irregular Problems;Multimedia Servers;Parallel Processing;Scalable Computing
Compiler Optimizations for Scalable Parallel Systems by Santosh Pande,Dharma P. Agrawal Pdf
Scalable parallel systems or, more generally, distributed memory systems offer a challenging model of computing and pose fascinating problems regarding compiler optimization, ranging from language design to run time systems. Research in this area is foundational to many challenges from memory hierarchy optimizations to communication optimization. This unique, handbook-like monograph assesses the state of the art in the area in a systematic and comprehensive way. The 21 coherent chapters by leading researchers provide complete and competent coverage of all relevant aspects of compiler optimization for scalable parallel systems. The book is divided into five parts on languages, analysis, communication optimizations, code generation, and run time systems. This book will serve as a landmark source for education, information, and reference to students, practitioners, professionals, and researchers interested in updating their knowledge about or active in parallel computing.
Annual Review of Scalable Computing by Yuen Chung Kwong Pdf
This book provides a forum for researchers in scalable computing to publish extended-length articles on significant new developments. An article may present comprehensive results from a major project, review recent work in a sub-domain, or expound new ideas in a detailed, tutorial fashion, at a length which most journals and conference proceedings cannot accommodate. The five articles in this book give an excellent illustration of the different types of material requiring such extensive treatment, and should serve well to encourage future authors with similar ideas to consider publishing in the Series on Scalable Computing. Contents:Active Objects: A Software Structure for Cluster-Based Systems (C K Yuen)Scalable Optimistic Parallel Simulation (Y M Teo & S C Tay)High Performance Fortran for Advanced Applications (S Benkner)Inter Process Communication Optimization in a Scalable Computing Cluster (O La'adan & A Barak)Designing Superservers with Clusters and Commodity Components (Z Xu & K Hwang) Readership: Researchers in computer science. Keywords:Active Objects;BaLinda;Clusters;High Performance;Fortran;IPC;Parallel Programming;Simulation;Superservers
Languages, Compilers, and Run-Time Systems for Scalable Computers by David O'Hallaron Pdf
This book constitutes the strictly refereed post-workshop proceedings of the 4th International Workshop on Languages, Compilers, and Run-Time Systems for Scalable Computing, LCR '98, held in Pittsburgh, PA, USA in May 1998. The 23 revised full papers presented were carefully selected from a total of 47 submissions; also included are nine refereed short papers. All current issues of developing software systems for parallel and distributed computers are covered, in particular irregular applications, automatic parallelization, run-time parallelization, load balancing, message-passing systems, parallelizing compilers, shared memory systems, client server applications, etc.
Annual Review of Scalable Computing by Yuen Chung Kwong Pdf
The third volume in the Series on Scalable Computing, this book contains five new articles describing significant developments in the field. Included are such current topics as clusters, parallel tools, load balancing, mobile systems, and architecture independence.
Handbook of Research on Scalable Computing Technologies by Li, Kuan-Ching,Hsu, Ching-Hsien,Yang, Laurence Tianruo,Dongarra, Jack,Zima, Hans Pdf
"This book presents, discusses, shares ideas, results and experiences on the recent important advances and future challenges on enabling technologies for achieving higher performance"--Provided by publisher.
Languages, Compilers and Run-Time Systems for Scalable Computers by Boleslaw K. Szymanski,Balaram Sinharoy Pdf
Language, Compilers and Run-time Systems for Scalable Computers contains 20 articles based on presentations given at the third workshop of the same title, and 13 extended abstracts from the poster session. Starting with new developments in classical problems of parallel compiler design, such as dependence analysis and an exploration of loop parallelism, the book goes on to address the issues of compiler strategy for specific architectures and programming environments. Several chapters investigate support for multi-threading, object orientation, irregular computation, locality enhancement, and communication optimization. Issues of the interface between language and operating system support are also discussed. Finally, the load balance issues are discussed in different contexts, including sparse matrix computation and iteratively balanced adaptive solvers for partial differential equations. Some additional topics are also discussed in the extended abstracts. Each chapter provides a bibliography of relevant papers and the book can thus be used as a reference to the most up-to-date research in parallel software engineering.
Scaling Up Machine Learning by Ron Bekkerman,Mikhail Bilenko,John Langford Pdf
This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies.
High Performance Computing: Technology, Methods and Applications by J.J. Dongarra,L. Grandinetti,J. Kowalik,G.R. Joubert Pdf
High Performance Computing is an integrated computing environment for solving large-scale computational demanding problems in science, engineering and business. Newly emerging areas of HPC applications include medical sciences, transportation, financial operations and advanced human-computer interface such as virtual reality. High performance computing includes computer hardware, software, algorithms, programming tools and environments, plus visualization. The book addresses several of these key components of high performance technology and contains descriptions of the state-of-the-art computer architectures, programming and software tools and innovative applications of parallel computers. In addition, the book includes papers on heterogeneous network-based computing systems and scalability of parallel systems. The reader will find information and data relative to the two main thrusts of high performance computing: the absolute computational performance and that of providing the most cost effective and affordable computing for science, industry and business. The book is recommended for technical as well as management oriented individuals.
Shared-Memory Parallelism Can be Simple, Fast, and Scalable by Julian Shun Pdf
Parallelism is the key to achieving high performance in computing. However, writing efficient and scalable parallel programs is notoriously difficult, and often requires significant expertise. To address this challenge, it is crucial to provide programmers with high-level tools to enable them to develop solutions easily, and at the same time emphasize the theoretical and practical aspects of algorithm design to allow the solutions developed to run efficiently under many different settings. This thesis addresses this challenge using a three-pronged approach consisting of the design of shared-memory programming techniques, frameworks, and algorithms for important problems in computing. The thesis provides evidence that with appropriate programming techniques, frameworks, and algorithms, shared-memory programs can be simple, fast, and scalable, both in theory and in practice. The results developed in this thesis serve to ease the transition into the multicore era. The first part of this thesis introduces tools and techniques for deterministic parallel programming, including means for encapsulating nondeterminism via powerful commutative building blocks, as well as a novel framework for executing sequential iterative loops in parallel, which lead to deterministic parallel algorithms that are efficient both in theory and in practice. The second part of this thesis introduces Ligra, the first high-level shared memory framework for parallel graph traversal algorithms. The framework allows programmers to express graph traversal algorithms using very short and concise code, delivers performance competitive with that of highly-optimized code, and is up to orders of magnitude faster than existing systems designed for distributed memory. This part of the thesis also introduces Ligra+, which extends Ligra with graph compression techniques to reduce space usage and improve parallel performance at the same time, and is also the first graph processing system to support in-memory graph compression. The third and fourth parts of this thesis bridge the gap between theory and practice in parallel algorithm design by introducing the first algorithms for a variety of important problems on graphs and strings that are efficient both in theory and in practice. For example, the thesis develops the first linear-work and polylogarithmic-depth algorithms for suffix tree construction and graph connectivity that are also practical, as well as a work-efficient, polylogarithmic-depth, and cache-efficient shared-memory algorithm for triangle computations that achieves a 2–5x speedup over the best existing algorithms on 40 cores. This is a revised version of the thesis that won the 2015 ACM Doctoral Dissertation Award.
