An Extension of the StarSs Programming Model for Platforms with Multiple GPUs
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Otros documentos de la autoría: Ayguadé, Eduardo; Badía Sala, Rosa María; Igual, Francisco D.; Labarta Mancho, Jesús; Mayo, Rafael; Quintana-Orti, Enrique S.
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
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Título
An Extension of the StarSs Programming Model for Platforms with Multiple GPUsAutoría
Fecha de publicación
2009Editor
Springer Berlin HeidelbergISBN
978-3-642-03869-3Cita bibliográfica
AYGUADE, Eduardo, et al. An Extension of the StarSs Programming Model for Platforms with Multiple GPUs. En: Euro-Par 2009 Parallel Processing: 15th International Euro-Par Conference, Delft, The Netherlands, August 25-28, 2009. Proceedings, p. 851-862. Springer Berlin Heidelberg, 2009. (Lecture Notes in Computer Science; 5704) ISBN 978-3-642-03869-3Tipo de documento
info:eu-repo/semantics/bookPartVersión de la editorial
http://link.springer.com/chapter/10.1007/978-3-642-03869-3_79Palabras clave / Materias
Resumen
While general-purpose homogeneous multi-core architectures are becoming ubiquitous, there are clear indications that, for a number of important applications, a better performance/power ratio can be attained using ... [+]
While general-purpose homogeneous multi-core architectures are becoming ubiquitous, there are clear indications that, for a number of important applications, a better performance/power ratio can be attained using specialized hardware accelerators. These accelerators require specific SDK or programming languages which are not always easy to program. Thus, the impact of the new programming paradigms on the programmer’s productivity will determine their success in the high-performance computing arena. In this paper we present GPU Superscalar (GPUSs), an extension of the Star Superscalar programming model that targets the parallelization of applications on platforms consisting of a general-purpose processor connected with multiple graphics processors. GPUSs deals with architecture heterogeneity and separate memory address spaces, while preserving simplicity and portability. Preliminary experimental results for a well-known operation in numerical linear algebra illustrate the correct adaptation of the runtime to a multi-GPU system, attaining notable performance results. [-]
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