This paper surveys and places into perspective a number of results concerning the D-BSP (Decomposable Bulk Synchronous Parallel) model of computation, a variant of the popular BSP model proposed byValiant in the early nineties. D-BSP captures part of the proximity structure of the computing platform, modeling it by suitable decompositions into clusters, each characterized by its own bandwidth and latency parameters. Quantitative evidence is provided that, when modeling realistic parallel architectures, D-BSP achieves higher effectiveness and portability than BSP, without significantly affecting the ease of use. It is also shown that D-BSP avoids some of the shortcomings of BSP which motivated the definition of other variants of the model. Finally, the paper discusses how the aspects of network proximity incorporated in the model allow for a better management of network congestion and bank contention, when supporting a shared-memory abstraction in a distributed-memory environment.

On the Effectiveness of D-BSP as a Bridging Model of Parallel Computation

BILARDI, GIANFRANCO;FANTOZZI, CARLO;PIETRACAPRINA, ANDREA ALBERTO;PUCCI, GEPPINO
2001

Abstract

This paper surveys and places into perspective a number of results concerning the D-BSP (Decomposable Bulk Synchronous Parallel) model of computation, a variant of the popular BSP model proposed byValiant in the early nineties. D-BSP captures part of the proximity structure of the computing platform, modeling it by suitable decompositions into clusters, each characterized by its own bandwidth and latency parameters. Quantitative evidence is provided that, when modeling realistic parallel architectures, D-BSP achieves higher effectiveness and portability than BSP, without significantly affecting the ease of use. It is also shown that D-BSP avoids some of the shortcomings of BSP which motivated the definition of other variants of the model. Finally, the paper discusses how the aspects of network proximity incorporated in the model allow for a better management of network congestion and bank contention, when supporting a shared-memory abstraction in a distributed-memory environment.
2001
Computational Science - ICCS 2001 Proceedings, Part II
9783540422334
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2430263
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