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  • Format: ePub

Advances in GPU Research and Practice focuses on research and practices in GPU based systems. The topics treated cover a range of issues, ranging from hardware and architectural issues, to high level issues, such as application systems, parallel programming, middleware, and power and energy issues.
Divided into six parts, this edited volume provides the latest research on GPU computing. Part I: Architectural Solutions focuses on the architectural topics that improve on performance of GPUs, Part II: System Software discusses OS, compilers, libraries, programming environment, languages, and
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Produktbeschreibung
Advances in GPU Research and Practice focuses on research and practices in GPU based systems. The topics treated cover a range of issues, ranging from hardware and architectural issues, to high level issues, such as application systems, parallel programming, middleware, and power and energy issues.

Divided into six parts, this edited volume provides the latest research on GPU computing. Part I: Architectural Solutions focuses on the architectural topics that improve on performance of GPUs, Part II: System Software discusses OS, compilers, libraries, programming environment, languages, and paradigms that are proposed and analyzed to help and support GPU programmers. Part III: Power and Reliability Issues covers different aspects of energy, power, and reliability concerns in GPUs. Part IV: Performance Analysis illustrates mathematical and analytical techniques to predict different performance metrics in GPUs. Part V: Algorithms presents how to design efficient algorithms and analyze their complexity for GPUs. Part VI: Applications and Related Topics provides use cases and examples of how GPUs are used across many sectors.

  • Discusses how to maximize power and obtain peak reliability when designing, building, and using GPUs
  • Covers system software (OS, compilers), programming environments, languages, and paradigms proposed to help and support GPU programmers
  • Explains how to use mathematical and analytical techniques to predict different performance metrics in GPUs
  • Illustrates the design of efficient GPU algorithms in areas such as bioinformatics, complex systems, social networks, and cryptography
  • Provides applications and use case scenarios in several different verticals, including medicine, social sciences, image processing, and telecommunications

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Autorenporträt
Hamid Sarbazi-Azad is currently a professor of computer science and engineering at Sharif University of Technology, and a research professor of computer science at the Institute for Research in Fundamental Sciences, both in Tehran, Iran . His research interests include high-performance computer/memory architectures, NoCs and SoCs, learning architectures,, social networks, and storage systems, on which he has published over 400 refereed papers. He received Khwarizmi International Award in 2006, TWAS Young Scientist Award in engineering sciences in 2007, and Sharif University Distinguished Researcher awards in years 2004, 2007, 2008, 2010 and 2013. He is now an associate editor of ACM Computing Surveys, IEEE Computer Architecture Letters, and Elsevier's Computers and Electrical Engineering.