On characterizing bandwidth requirements of parallel applications

Author:

Sivasubramaniam Anand1,Singla Aman1,Ramachandran Umakishore1,Venkateswaran H.1

Affiliation:

1. College of Computing, Georgia Institute of Technology, Atlanta, GA

Abstract

Synthesizing architectural requirements from an application viewpoint can help in making important architectural design decisions towards building large scale parallel machines. In this paper, we quantify the link bandwidth requirement on a binary hypercube topology for a set of five parallel applications. We use an execution-driven simulator called SPASM to collect data points for system sizes that are feasible to be simulated. These data points are then used in a regression analysis for projecting the link bandwidth requirements for larger systems. The requirements are projected as a function of the following system parameters: number of processors, CPU clock speed, and problem size. These results are also used to project the link bandwidths for other network topologies. Our study quantifies the link bandwidth that has to be made available to limit the network overhead in an application to a specified tolerance level. The results show that typical link bandwidths (200-300 MBytes/sec) found in current commercial parallel architectures (such as Intel Paragon and Cray T3D) would have fairly low network overhead for the applications considered in this study. For two of the applications, this overhead is negligible. For the other applications, this overhead can be limited to about 30% of the execution time provided the problem sizes are increased commensurate with the processor clock speed. The technique presented can be useful to a system architect to synthesize the bandwidth requirements for realizing well-balanced parallel architectures.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Performance Modeling of Big Data-Oriented Architectures;Computer Communications and Networks;2016

2. Exploiting mean field analysis to model performances of big data architectures;Future Generation Computer Systems;2014-07

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