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Record Nr. |
UNINA9910583334103321 |
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Autore |
Sarbazi-Azad Hamid |
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Titolo |
Advances in GPU research and practice / / edited by Hamid Sarbazi-Azad |
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Pubbl/distr/stampa |
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Amsterdam : , : Elsevier, , [2017] |
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©2017 |
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ISBN |
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Edizione |
[First edition.] |
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Descrizione fisica |
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1 online resource (776 pages) : illustrations (some color) |
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Collana |
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Emerging trends in computer science and applied computing |
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Soggetti |
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Graphics processing units - Programming |
Imaging systems |
Computer graphics |
Image processing - Digital techniques |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di bibliografia |
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Includes bibliographical references and indexes. |
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Sommario/riassunto |
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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 |
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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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