000			02174cam a2200277 a 4500
008			110928s2010 maua b 001 0 eng
010			_a2009048259
020			_a9780123814722
035			_a(Sirsi) u7908
040			_aEG-CaNU _c EG-CaNU _d EG-CaNU
042			_ancode
082	0	0	_a004.35 _2 22
100	1		_aKirk, David, _d 1960- _914276
245	1	0	_aProgramming massively parallel processors hands-on with CUDA / _c by David Kirk and Wen-mei Hwu.
260			_aBurlington, MA : _b Morgan Kaufmann Publishers, _c c2010.
300			_axviii, 258 p. : _b ill. ; _c 24 cm.
504			_aIncludes bibliographical references and index.
505	0		_a1. Introduction -- 2. History of GPU Computing -- 3. Introduction to CUDA -- 4. CUDA Threads -- 5. CUDA Memories -- 6. Performance Considerations -- 7. Floating-Point Format -- 8. Application Case Study I - Advanced MRI Reconstruction -- 9. Application Case Study II - Molecular Visualization and Analysis -- 10. Parallel Programming and Computational Thinking -- 11. A Brief Introduction to OpenCL -- 12. Conclusion and Future Outlook.
520			_aMulti-core processors are no longer the future of computing-they are the present day reality. A typical mass-produced CPU features multiple processor cores, while a GPU (Graphics Processing Unit) may have hundreds or even thousands of cores. With the rise of multi-core architectures has come the need to teach advanced programmers a new and essential skill: how to program massively parallel processors. Programming Massively Parallel Processors: A Hands-on Approach shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Various techniques for constructing parallel programs are explored in detail. Case studies demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs.
650		0	_aParallel programming (Computer science) _92166
650		0	_aParallel processing (Electronic computers) _92166
650		0	_aMultiprocessors. _98805
650		0	_aComputer architecture. _914277
700	1		_aHwu, Wen-mei. _914278
596			_a1
999			_c6833 _d6833