HPC@Green IT [recurso electrónico] : Green High Performance Computing Methods / by Ralf Gruber, Vincent Keller.

Por: Gruber, Ralf [author.]Colaborador(es): Keller, Vincent [author.] | SpringerLink (Online service)Tipo de material: TextoTextoEditor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010Descripción: XIV, 215p. 170 illus., 85 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783642017896Tema(s): Computer science | Computer network architectures | Computer system performance | Software engineering | Operating systems (Computers) | Computer Science | Software Engineering/Programming and Operating Systems | Programming Techniques | System Performance and Evaluation | Computer Systems Organization and Communication Networks | Operating SystemsFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 005.1 Clasificación LoC:QA76.758Recursos en línea: Libro electrónicoTexto
Contenidos:
Historical highlights -- Parameterization -- Models -- Core optimization -- Node optimization -- Cluster optimization -- Grid-level Brokering to save energy -- Recommendations.
En: Springer eBooksResumen: The authors present methods to reduce computer energy consumption by a better use of resources and by maximizing the efficiencies of applications. The processor frequency is adjusted to the needs of the running job, leading to a power drop in servers and PCs, and increasing battery life time of laptops. It is shown how computer resources can be optimally adapted to application needs, reducing job run time. The job-related data is stored and reused to help computer managers to stop old machines and to choose new ones better adapted to the application community.
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Tipo de ítem Biblioteca actual Colección Signatura Copia número Estado Fecha de vencimiento Código de barras
Libro Electrónico Biblioteca Electrónica
Colección de Libros Electrónicos QA76.758 (Browse shelf(Abre debajo)) 1 No para préstamo 373404-2001

Historical highlights -- Parameterization -- Models -- Core optimization -- Node optimization -- Cluster optimization -- Grid-level Brokering to save energy -- Recommendations.

The authors present methods to reduce computer energy consumption by a better use of resources and by maximizing the efficiencies of applications. The processor frequency is adjusted to the needs of the running job, leading to a power drop in servers and PCs, and increasing battery life time of laptops. It is shown how computer resources can be optimally adapted to application needs, reducing job run time. The job-related data is stored and reused to help computer managers to stop old machines and to choose new ones better adapted to the application community.

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