Multicore computing : algorithms, architectures, and applications /
Every area of science and engineering today has to process voluminous data sets. Using exact, or even approximate, algorithms to solve intractable problems in critical areas, such as computational biology, takes time that is exponential in some of the underlying parameters. Parallel computing addres...
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Full text (MCPHS users only) |
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| Other Authors: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Boca Raton [Florida] :
Chapman and Hall/CRC,
2013
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| Series: | Chapman & Hall/CRC computer and information science series ;
29. |
| Subjects: | |
| Local Note: | ProQuest Ebook Central |
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| 245 | 0 | 0 | |a Multicore computing : |b algorithms, architectures, and applications / |c edited by Sanguthevar Rajasekaran [and three others]. |
| 264 | 1 | |a Boca Raton [Florida] : |b Chapman and Hall/CRC, |c 2013. | |
| 300 | |a 1 online resource (451 pages) | ||
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| 490 | 1 | |a Chapman & Hall/CRC computer & information science series ; |v 29 | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Front Cover; Dedication; Content; Preface; Acknowledgements; List of Contributing Editors; List of Contributing Authors; Chapter 1 -- Memory Hierarchy for Multicore and Many-Core Processors; Chapter 2 -- FSB: A Flexible Set-Balancing Strategy for Last-Level Caches; Chapter 3 -- The SPARC Processor Architecture; Chapter 4 -- The Cilk and Cilk++ Programming Languages; Chapter 5 -- Multithreading in the PLASMA Library; Chapter 6 -- Ecient Aho-Corasick String Matching on Emerging Multicore Architectures; Chapter 7 -- Sorting on a Graphics Processing Unit (GPU). | |
| 505 | 8 | |a Chapter 8 -- Scheduling DAG-Structured ComputationsChapter 9 -- Evaluating Multicore Processors and Accelerators for Dense Numerical Computations; Chapter 10 -- Sorting on the Cell Broadband Engine; Chapter 11 -- GPU Matrix Multiplication; Chapter 12 -- Backprojection Algorithms for Multicore and GPU Architectures; Back Cover. | |
| 520 | |a Every area of science and engineering today has to process voluminous data sets. Using exact, or even approximate, algorithms to solve intractable problems in critical areas, such as computational biology, takes time that is exponential in some of the underlying parameters. Parallel computing addresses this issue and has become affordable with the advent of multicore architectures. However, programming multicore machines is much more difficult due to oddities existing in the architectures. Offering insights into different facets of this area, Multicore Computing: Algori. | ||
| 546 | |a English. | ||
| 588 | 0 | |a Online resource; title from PDF title page (ebrary, viewed January 17, 2014). | |
| 590 | |a ProQuest Ebook Central |b Ebook Central College Complete | ||
| 650 | 0 | |a Multiprocessors. | |
| 650 | 0 | |a Computers. | |
| 650 | 0 | |a Electronic digital computers. | |
| 650 | 7 | |a computers. |2 aat | |
| 700 | 1 | |a Rajasekaran, Sanguthevar. | |
| 758 | |i has work: |a Multicore computing (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGw6dfbH3YcxYMpbFJQtTd |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
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