A parallel programming interface for out-of-core cluster applications
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Clusters of workstations are a practical approach to parallel computing that provide high performance at a low cost for many scientific and engineering applications. In order to handle problems with increasing data sets, methods supporting parallel out-of-core computations must be investigated. Since writing an out-of-core version of a program is a difficult task and virtual memory systems do not perform well in some cases, we have developed a parallel programming interface and the support library to provide efficient and convenient access to the out-of-core data. This paper focuses on how these components extend the range of problem sizes that can be solved on the cluster of workstations. Execution time of Jacobi iteration when using our interface, virtual memory and PVFS are compared to characterize the performance for various problem sizes, and it is concluded that our new interface significantly increases the sizes of problems that can be efficiently solved.
KeywordsOut-of-core computation Cluster of workstations Global out-of-core array Local array file In-core data
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- 1.J. Mache, J. Bower-Cooley, R. Broadhurst, J. Cranfill, and C. Kirkman IV, Parallel i/o performance of pc clusters, In: 10th SIAM Conf. on Parallel Processing for Scientific Computing, Portsmouth, VA, USA, (March 2001).Google Scholar
- 2.High performance computing and communications: Grand challenges 1993 report. Technical report, A Report by the Committee on Physical, Mathematical and Engineering Sciences, Federal Coordinating Council for Science, Engineering and Technology, (1993).Google Scholar
- 3.D. Womble, D. Greenberg, R. Riesen, and S. Wheat, s Out of core, out of mind: Practical parallel i/o. In: Proceedings of the Conference on Scalable Parallel Libraries, A. Skjellum, Washington DC, USA, (1993). IEEE Computer Society.Google Scholar
- 4.T. Jones, A. Koniges, and R.K. Yates, Performance of the ibm general parallel file system. In: Proceedings of 14th International Parallel and Distributed Processing Symposium, (May 2000) pp. 673–681.Google Scholar
- 5.R. Thakur, W. Gropp, and E. Lusk, Data sieving and collective i/o in romio. In: Proceedings of the Seventh Symposium on the Frontiers of Massively Parallel Computation, (February 1999) pp. 182– 189.Google Scholar
- 6.J.V. Huber, A.A. Chien, C. L. Elford, D. S. Blumenthal, and D.A. Reed, Ppfs: A high performance portable parallel file system. In: Proceedings of the 9th ACM international conference on Supercomputing, (July 1995) pp. 385–394.Google Scholar
- 7.R. Thakur, A. Choudhary, R. Bordawekar, S. More, and S. Kuditipudi, Passion: Optimized i/o for parallel applications. Computer 29(6) (1996) 70–78.Google Scholar
- 8.P.H. Carns, W.B. Ligon III, R.B. Ross, and R. Thakur, Pvfs: A parallel file system for linux clusters. In: Proceidings of the 4th Annual Linux Showcase and Conference, Atlanta, GA, USA, (October 2000) pp. 317–327.Google Scholar
- 9.A. Ching, A. Choudhary, W. Liao, R. Ross and W. Gropp, Noncontiguous i/o through pvfs. In: Proceedings of IEEE International Conference on Cluster Computing, (September 2002) pp. 405–414.Google Scholar
- 11.M.M. Cettei, W.B. Ligon III, and R.B. Ross, Support for parallel out of core applications on beowulf workstations. In: Proceidings of the 1998 IEEE Aerospace Conference, (March 1998).Google Scholar
- 12.D. Gannon, X.Y. Shelby, and P. Beckman, User guide for a portable parallel c++ programming system: pc++. Technical report, Indiana University, (September 1994).Google Scholar