Computer Science – Distributed – Parallel – and Cluster Computing
Scientific paper
2008-08-26
Computer Science
Distributed, Parallel, and Cluster Computing
13 pages, 18 figures
Scientific paper
Our work addresses the enabling of the execution of highly parallel computations composed of loosely coupled serial jobs with no modifications to the respective applications, on large-scale systems. This approach allows new-and potentially far larger-classes of application to leverage systems such as the IBM Blue Gene/P supercomputer and similar emerging petascale architectures. We present here the challenges of I/O performance encountered in making this model practical, and show results using both micro-benchmarks and real applications on two large-scale systems, the BG/P and the SiCortex SC5832. Our preliminary benchmarks show that we can scale to 4096 processors on the Blue Gene/P and 5832 processors on the SiCortex with high efficiency, and can achieve thousands of tasks/sec sustained execution rates for parallel workloads of ordinary serial applications. We measured applications from two domains, economic energy modeling and molecular dynamics.
Foster Ian
Raicu Ioan
Wilde Mike
Zhang Zhao
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