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Author : Guy E. Blelloch
Release : 1990
Genre : Computers
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Vector Models for Data-parallel Computing by : Guy E. Blelloch
Download or read book Vector Models for Data-parallel Computing written by Guy E. Blelloch. This book was released on 1990. Available in PDF, EPUB and Kindle. Book excerpt: Mathematics of Computing -- Parallelism.
Author : Guy-Rene Perrin
Release : 1996-09-11
Genre : Computers
Kind : eBook
Book Rating : 365/5 ( reviews)
Book Synopsis The Data Parallel Programming Model by : Guy-Rene Perrin
Download or read book The Data Parallel Programming Model written by Guy-Rene Perrin. This book was released on 1996-09-11. Available in PDF, EPUB and Kindle. Book excerpt: This monograph-like book assembles the thorougly revised and cross-reviewed lectures given at the School on Data Parallelism, held in Les Menuires, France, in May 1996. The book is a unique survey on the current status and future perspectives of the currently very promising and popular data parallel programming model. Much attention is paid to the style of writing and complementary coverage of the relevant issues throughout the 12 chapters. Thus these lecture notes are ideally suited for advanced courses or self-instruction on data parallel programming. Furthermore, the book is indispensable reading for anybody doing research in data parallel programming and related areas.
Author : Pavan Balaji
Release : 2015-11-06
Genre : Computers
Kind : eBook
Book Rating : 819/5 ( reviews)
Book Synopsis Programming Models for Parallel Computing by : Pavan Balaji
Download or read book Programming Models for Parallel Computing written by Pavan Balaji. This book was released on 2015-11-06. Available in PDF, EPUB and Kindle. Book excerpt: An overview of the most prominent contemporary parallel processing programming models, written in a unique tutorial style. With the coming of the parallel computing era, computer scientists have turned their attention to designing programming models that are suited for high-performance parallel computing and supercomputing systems. Programming parallel systems is complicated by the fact that multiple processing units are simultaneously computing and moving data. This book offers an overview of some of the most prominent parallel programming models used in high-performance computing and supercomputing systems today. The chapters describe the programming models in a unique tutorial style rather than using the formal approach taken in the research literature. The aim is to cover a wide range of parallel programming models, enabling the reader to understand what each has to offer. The book begins with a description of the Message Passing Interface (MPI), the most common parallel programming model for distributed memory computing. It goes on to cover one-sided communication models, ranging from low-level runtime libraries (GASNet, OpenSHMEM) to high-level programming models (UPC, GA, Chapel); task-oriented programming models (Charm++, ADLB, Scioto, Swift, CnC) that allow users to describe their computation and data units as tasks so that the runtime system can manage computation and data movement as necessary; and parallel programming models intended for on-node parallelism in the context of multicore architecture or attached accelerators (OpenMP, Cilk Plus, TBB, CUDA, OpenCL). The book will be a valuable resource for graduate students, researchers, and any scientist who works with data sets and large computations. Contributors Timothy Armstrong, Michael G. Burke, Ralph Butler, Bradford L. Chamberlain, Sunita Chandrasekaran, Barbara Chapman, Jeff Daily, James Dinan, Deepak Eachempati, Ian T. Foster, William D. Gropp, Paul Hargrove, Wen-mei Hwu, Nikhil Jain, Laxmikant Kale, David Kirk, Kath Knobe, Ariram Krishnamoorthy, Jeffery A. Kuehn, Alexey Kukanov, Charles E. Leiserson, Jonathan Lifflander, Ewing Lusk, Tim Mattson, Bruce Palmer, Steven C. Pieper, Stephen W. Poole, Arch D. Robison, Frank Schlimbach, Rajeev Thakur, Abhinav Vishnu, Justin M. Wozniak, Michael Wilde, Kathy Yelick, Yili Zheng
Author : Thomas H. Cormen
Release : 1993
Genre : Computer science
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Vector Layout in Virtual-memory Systems for Data-parallel Computing by : Thomas H. Cormen
Download or read book Vector Layout in Virtual-memory Systems for Data-parallel Computing written by Thomas H. Cormen. This book was released on 1993. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yidi Song
Release : 2013
Genre :
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis Parallel Vector Fitting of Systems Characterised by Measured Or Simulated Data by : Yidi Song
Download or read book Parallel Vector Fitting of Systems Characterised by Measured Or Simulated Data written by Yidi Song. This book was released on 2013. Available in PDF, EPUB and Kindle. Book excerpt: "During the past decade, technology in the electronics industry has advanced considerably. The integrated circuits we are using today are becoming more and more complex. As a result, modeling those complex systems has become a difficult task. The vector fitting method is a very efficient tool for building a model based on measured or simulated data. However, for large scale systems, the vector fitting method runs slowly or even fails to converge at the end. One of the solutions to the problem is the parallel vector fitting which was introduced a few years ago. Recently, the parallel computing and cloud computing have become more popular. It would be much more efficient if we can use the concept of parallel computing to do the vector fitting. Since each column in the admittance matrix Y is independent from each other. Calculations on one column will not affect the results of another column. Thus, we can do multiple column vector fittings at the same time. This concept leads to the idea of doing the vector fitting in a parallel way. During the algorithm, many columns are being vector fitted at the same time. There is one small model for each column. After all columns are done, an extra routine will be executed to combine all sub-models into one complete model. In this way, we can achieve a descent speedup factor which leads to less total computing time. The final model is verified so that it is as accurate as the one generated by the traditional vector fitting. In this thesis, detailed concepts will be presented. Methods will be explained step by step and examples will be tested and analyzed." --
