9783031006098 - performance analysis and tuning for general purpose graphics processing units (gpgpu) (synthesis lectures on computer architecture) de kim, hyesoon; vuduc, richard; baghsorkhi, sara; choi, jee; hwu, wen-mei w. (17 resultados)
Performance Analysis and Tunin
Kim, Hyesoon; Vuduc, Richard; Baghsorkhi, Sara; Choi, Jee; Hwu, Wen-mei W.
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Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
Kim, Hyesoon; Vuduc, Richard; Baghsorkhi, Sara; Choi, Jee; Hwu, Wen-mei W.
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Paperback. Condición: new. Paperback. General-purpose graphics processing units (GPGPU) have emerged as an important class of shared memory parallel processing architectures, with widespread deployment in every computer class from high-end supercomputers to embedded mobile platforms. Relative to more traditional multicore system…s of today, GPGPUs have distinctly higher degrees of hardware multithreading (hundreds of hardware thread contexts vs. tens), a return to wide vector units (several tens vs. 1-10), memory architectures that deliver higher peak memory bandwidth (hundreds of gigabytes per second vs. tens), and smaller caches/scratchpad memories (less than 1 megabyte vs. 1-10 megabytes). In this book, we provide a high-level overview of current GPGPU architectures and programming models. We review the principles that are used in previous shared memory parallel platforms, focusing on recent results in both the theory and practice of parallel algorithms, and suggest a connection to GPGPU platforms. We aim to provide hints to architects about understanding algorithm aspect to GPGPU. We also provide detailed performance analysis and guide optimizations from high-level algorithms to low-level instruction level optimizations. As a case study, we use n-body particle simulations known as the fast multipole method (FMM) as an example. We also briefly survey the state-of-the-art in GPU performance analysis tools and techniques. Table of Contents: GPU Design, Programming, and Trends / Performance Principles / From Principles to Practice: Analysis and Tuning / Using Detailed Performance Analysis to Guide Optimization General-purpose graphics processing units (GPGPU) have emerged as an important class of shared memory parallel processing architectures, with widespread deployment in every computer class from high-end supercomputers to embedded mobile platforms. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
Kim, Hyesoon; Vuduc, Richard; Baghsorkhi, Sara; Choi, Jee; Hwu, Wen-mei W.
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Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU) (Synthesis Lectures on Computer Architecture)
Kim, Hyesoon; Vuduc, Richard; Baghsorkhi, Sara; Choi, Jee; Hwu, Wen-mei W.
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Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
Kim, Hyesoon; Vuduc, Richard; Baghsorkhi, Sara; Choi, Jee; Hwu, Wen-mei W.
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Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU) (Synthesis Lectures on Computer Architecture)
Kim, Hyesoon; Vuduc, Richard; Baghsorkhi, Sara; Choi, Jee; Hwu, Wen-mei W.
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Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
Kim, Hyesoon; Vuduc, Richard; Baghsorkhi, Sara; Choi, Jee; Hwu, Wen-mei W.
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Paperback. Condición: new. Paperback. General-purpose graphics processing units (GPGPU) have emerged as an important class of shared memory parallel processing architectures, with widespread deployment in every computer class from high-end supercomputers to embedded mobile platforms. Relative to more traditional multicore system…s of today, GPGPUs have distinctly higher degrees of hardware multithreading (hundreds of hardware thread contexts vs. tens), a return to wide vector units (several tens vs. 1-10), memory architectures that deliver higher peak memory bandwidth (hundreds of gigabytes per second vs. tens), and smaller caches/scratchpad memories (less than 1 megabyte vs. 1-10 megabytes). In this book, we provide a high-level overview of current GPGPU architectures and programming models. We review the principles that are used in previous shared memory parallel platforms, focusing on recent results in both the theory and practice of parallel algorithms, and suggest a connection to GPGPU platforms. We aim to provide hints to architects about understanding algorithm aspect to GPGPU. We also provide detailed performance analysis and guide optimizations from high-level algorithms to low-level instruction level optimizations. As a case study, we use n-body particle simulations known as the fast multipole method (FMM) as an example. We also briefly survey the state-of-the-art in GPU performance analysis tools and techniques. Table of Contents: GPU Design, Programming, and Trends / Performance Principles / From Principles to Practice: Analysis and Tuning / Using Detailed Performance Analysis to Guide Optimization General-purpose graphics processing units (GPGPU) have emerged as an important class of shared memory parallel processing architectures, with widespread deployment in every computer class from high-end supercomputers to embedded mobile platforms. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - General-purpose graphics processing units (GPGPU) have emerged as an important class of shared memory parallel processing architectures, with widespread deployment in every computer class from high-end supercomputers to embedded mobile platforms. R…elative to more traditional multicore systems of today, GPGPUs have distinctly higher degrees of hardware multithreading (hundreds of hardware thread contexts vs. tens), a return to wide vector units (several tens vs. 1-10), memory architectures that deliver higher peak memory bandwidth (hundreds of gigabytes per second vs. tens), and smaller caches/scratchpad memories (less than 1 megabyte vs. 1-10 megabytes). In this book, we provide a high-level overview of current GPGPU architectures and programming models. We review the principles that are used in previous shared memory parallel platforms, focusing on recent results in both the theory and practice of parallel algorithms, and suggest a connection to GPGPU platforms. We aim to provide hints to architects about understanding algorithm aspect to GPGPU. We also provide detailed performance analysis and guide optimizations from high-level algorithms to low-level instruction level optimizations. As a case study, we use n-body particle simulations known as the fast multipole method (FMM) as an example. We also briefly survey the state-of-the-art in GPU performance analysis tools and techniques. Table of Contents: GPU Design, Programming, and Trends / Performance Principles / From Principles to Practice: Analysis and Tuning / Using Detailed Performance Analysis to Guide Optimization.
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Taschenbuch. Condición: Neu. Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU) | Hyesoon Kim (u. a.) | Taschenbuch | Synthesis Lectures on Computer Architecture | xii | Englisch | 2012 | Springer | EAN 9783031006098 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17,…69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU) (Synthesis Lectures on Computer Architecture)
Kim, Hyesoon; Vuduc, Richard; Baghsorkhi, Sara; Choi, Jee; Hwu, Wen-mei W.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -General-purpose graphics processing units (GPGPU) have emerged as an important class of shared memory parallel processing architectures, with widespread deployment in every computer class from high-end supercomputers to embedded mob…ile platforms. Relative to more traditional multicore systems of today, GPGPUs have distinctly higher degrees of hardware multithreading (hundreds of hardware thread contexts vs. tens), a return to wide vector units (several tens vs. 1-10), memory architectures that deliver higher peak memory bandwidth (hundreds of gigabytes per second vs. tens), and smaller caches/scratchpad memories (less than 1 megabyte vs. 1-10 megabytes). In this book, we provide a high-level overview of current GPGPU architectures and programming models. We review the principles that are used in previous shared memory parallel platforms, focusing on recent results in both the theory and practice of parallel algorithms, and suggest a connection to GPGPU platforms. We aim to provide hints to architects about understanding algorithm aspect to GPGPU. We also provide detailed performance analysis and guide optimizations from high-level algorithms to low-level instruction level optimizations. As a case study, we use n-body particle simulations known as the fast multipole method (FMM) as an example. We also briefly survey the state-of-the-art in GPU performance analysis tools and techniques. Table of Contents: GPU Design, Programming, and Trends / Performance Principles / From Principles to Practice: Analysis and Tuning / Using Detailed Performance Analysis to Guide Optimization 100 pp. Englisch.
Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU) (Synthesis Lectures on Computer Architecture)
Kim, Hyesoon; Vuduc, Richard; Baghsorkhi, Sara; Choi, Jee; Hwu, Wen-mei W.
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Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
Hyesoon Kim|Richard Vuduc|Sara Baghsorkhi|Jee Choi|Wen-mei W. Hwu
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Hyesoon Kim is an Assistant professor in the School of Computer Science at Georgia Institute of Technology.Her research interests include high-performance energy-efficient heterogeneous architectures, programmer-compi…ler = microarchitecture interaction and .
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -General-purpose graphics processing units (GPGPU) have emerged as an important class of shared memory parallel processing architectures, with widespread deployment in every computer class from high-end supercomputers to embedded mobile…platforms. Relative to more traditional multicore systems of today, GPGPUs have distinctly higher degrees of hardware multithreading (hundreds of hardware thread contexts vs. tens), a return to wide vector units (several tens vs. 1-10), memory architectures that deliver higher peak memory bandwidth (hundreds of gigabytes per second vs. tens), and smaller caches/scratchpad memories (less than 1 megabyte vs. 1-10 megabytes). In this book, we provide a high-level overview of current GPGPU architectures and programming models. We review the principles that are used in previous shared memory parallel platforms, focusing on recent results in both the theory and practice of parallel algorithms, and suggest a connection to GPGPU platforms. We aim to provide hints to architects about understanding algorithm aspect to GPGPU. We also provide detailed performance analysis and guide optimizations from high-level algorithms to low-level instruction level optimizations. As a case study, we use n-body particle simulations known as the fast multipole method (FMM) as an example. We also briefly survey the state-of-the-art in GPU performance analysis tools and techniques. Table of Contents: GPU Design, Programming, and Trends / Performance Principles / From Principles to Practice: Analysis and Tuning / Using Detailed Performance Analysis to Guide OptimizationSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 100 pp. Englisch.
