000			04049nam a2200493 i 4500
001			7347044
003			IEEE
005			20220712204848.0
006			m o d
007			cr |n|||||||||
008			151223s2015 mau ob 001 eng d
010			_z 2015039693 (print)
020			_a9780262332248 _qelectronic
020			_z9780262528818 _qpaperback : alk. paper
035			_a(CaBNVSL)mat07347044
035			_a(IDAMS)0b00006484b080cd
040			_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL
050		4	_aQA76.58 _b.P78 2015eb
082	0	0	_a004/.35 _223
245	0	0	_aProgramming models for parallel computing / _cBalaji, Pavan, ed.
264		1	_aCambridge, Massachusetts : _bMIT Press, _c[2015]
264		2	_a[Piscataqay, New Jersey] : _bIEEE Xplore, _c[2015]
300			_a1 PDF (488 pages).
336			_atext _2rdacontent
337			_aelectronic _2isbdmedia
338			_aonline resource _2rdacarrier
490	1		_aScientific and engineering computation
504			_aIncludes bibliographical references.
506	1		_aRestricted to subscribers or individual electronic text purchasers.
520			_aWith 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. ContributorsTimothy 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.
530			_aAlso available in print.
538			_aMode of access: World Wide Web
588			_aDescription based on PDF viewed 12/23/2015.
650		0	_aParallel processing (Electronic computers) _924751
650		0	_aParallel programs (Computer programs) _924752
655		0	_aElectronic books. _93294
700	1		_aBalaji, Pavan, _d1980- _eeditor. _924753
710	2		_aIEEE Xplore (Online Service), _edistributor. _924754
710	2		_aMIT Press, _epublisher. _924755
776	0	8	_iPrint version _z9780262528818
830		0	_aScientific and engineering computation _921687
856	4	2	_3Abstract with links to resource _uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=7347044
942			_cEBK
999			_c73445 _d73445