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Publicado por Éditions Universitaires Européennes Sep 2016, 2016
ISBN 10: 3841726674 ISBN 13: 9783841726674
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -High performance computing (HPC) plays a fundamental role in tackling the most intractable problems across a wide range of disciplines and pushing the frontiers of science. It now becomes a third way to explore the unknown world besides theory and experiments. Manycore architecture and heterogeneous system is the main trend for future supercomputers. The programming methods, computing kernels, and parallel algorithms need to be thoroughly investigated on the basis of such parallel infrastructure. This book is driven by the real computational needs coming from scientific and industrial applications. For example in different fields of reactor physics such as neutronics or thermohydraulics, the eigenvalue problem and resolution of linear system are the key challenges that consume substantial computing resources. In this context, our objective is to design and improve the parallel computing techniques, including proposing efficient linear algebraic kernels and parallel numerical methods.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 152 pp. Englisch.
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Publicado por Éditions universitaires européennes, 2016
ISBN 10: 3841726674 ISBN 13: 9783841726674
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Añadir al carritoTaschenbuch. Condición: Neu. Efficient Algorithms for the Multicore and Heterogeneous Architecture | A Shortcut to the Efficient Utilization of the Multicore and Heterogeneous Architecture | Fan Ye | Taschenbuch | 152 S. | Englisch | 2016 | Éditions universitaires européennes | EAN 9783841726674 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
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Publicado por Éditions Universitaires Européennes Sep 2016, 2016
ISBN 10: 3841726674 ISBN 13: 9783841726674
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -High performance computing (HPC) plays a fundamental role in tackling the most intractable problems across a wide range of disciplines and pushing the frontiers of science. It now becomes a third way to explore the unknown world besides theory and experiments. Manycore architecture and heterogeneous system is the main trend for future supercomputers. The programming methods, computing kernels, and parallel algorithms need to be thoroughly investigated on the basis of such parallel infrastructure. This book is driven by the real computational needs coming from scientific and industrial applications. For example in different fields of reactor physics such as neutronics or thermohydraulics, the eigenvalue problem and resolution of linear system are the key challenges that consume substantial computing resources. In this context, our objective is to design and improve the parallel computing techniques, including proposing efficient linear algebraic kernels and parallel numerical methods. 152 pp. Englisch.
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Publicado por Éditions Universitaires Européennes, 2016
ISBN 10: 3841726674 ISBN 13: 9783841726674
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High performance computing (HPC) plays a fundamental role in tackling the most intractable problems across a wide range of disciplines and pushing the frontiers of science. It now becomes a third way to explore the unknown world besides theory and experiments. Manycore architecture and heterogeneous system is the main trend for future supercomputers. The programming methods, computing kernels, and parallel algorithms need to be thoroughly investigated on the basis of such parallel infrastructure. This book is driven by the real computational needs coming from scientific and industrial applications. For example in different fields of reactor physics such as neutronics or thermohydraulics, the eigenvalue problem and resolution of linear system are the key challenges that consume substantial computing resources. In this context, our objective is to design and improve the parallel computing techniques, including proposing efficient linear algebraic kernels and parallel numerical methods.