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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Single-threaded software applications have ceased to see signi cant gains in p- formance on a general-purpose CPU, even with further scaling in very large scale integration (VLSI) technology. This is a signi cant problem for electronic design automation (EDA) applications, since the design complexity of VLSI integrated circuits (ICs) is continuously growing. In this research monograph, we evaluate custom ICs, eld-programmable gate arrays (FPGAs), and graphics processors as platforms for accelerating EDA algorithms, instead of the general-purpose sing- threaded CPU. We study applications which are used in key time-consuming steps of the VLSI design ow. Further, these applications also have different degrees of inherent parallelism in them. We study both control-dominated EDA applications and control plus data parallel EDA applications. We accelerate these applications on these different hardware platforms. We also present an automated approach for accelerating certain uniprocessor applications on a graphics processor. This monograph compares custom ICs, FPGAs, and graphics processing units (GPUs) as potential platforms to accelerate EDA algorithms. It also provides details of the programming model used for interfacing with the GPUs.
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Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This text covers the acceleration of EDA algorithms using hardware platforms such as FPGAs and GPUs. In it, widely applied CAD algorithms are evaluated and compared for potential acceleration on FPGAs and GPUs.
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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This text covers the acceleration of EDA algorithms using hardware platforms such as FPGAs and GPUs. In it, widely applied CAD algorithms are evaluated and compared for potential acceleration on FPGAs and GPUs.
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Language: English
Published by SPRINGER NATURE Apr 2010, 2010
ISBN 10: 1441909435 ISBN 13: 9781441909435
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Single-threaded software applications have ceased to see signi cant gains in p- formance on a general-purpose CPU, even with further scaling in very large scale integration (VLSI) technology. This is a signi cant problem for electronic design automation (EDA) applications, since the design complexity of VLSI integrated circuits (ICs) is continuously growing. In this research monograph, we evaluate custom ICs, eld-programmable gate arrays (FPGAs), and graphics processors as platforms for accelerating EDA algorithms, instead of the general-purpose sing- threaded CPU. We study applications which are used in key time-consuming steps of the VLSI design ow. Further, these applications also have different degrees of inherent parallelism in them. We study both control-dominated EDA applications and control plus data parallel EDA applications. We accelerate these applications on these different hardware platforms. We also present an automated approach for accelerating certain uniprocessor applications on a graphics processor. This monograph compares custom ICs, FPGAs, and graphics processing units (GPUs) as potential platforms to accelerate EDA algorithms. It also provides details of the programming model used for interfacing with the GPUs. 192 pp. Englisch.
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Add to basketGebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides guidelines on whether to use GPUs or FPGAs when accelerating a given EDA algorithm, with validation by a concrete example implemented on both platformsDemonstrates the acceleration of several popular EDA algorithms on GPUs, with speedups .
Language: English
Published by Springer-Verlag New York Inc., 2014
ISBN 10: 1489983333 ISBN 13: 9781489983336
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides guidelines on whether to use GPUs or FPGAs when accelerating a given EDA algorithm, with validation by a concrete example implemented on both platformsDemonstrates the acceleration of several popular EDA algorithms on GPUs, with speedups .