The week's pick
Reseach Article
Pre-Parallelization Exercises in Budget-Constrained HPC Projects: A Case Study in CFD
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 26 |
| Year of Publication: 2010 |
| Authors: Shamsheer Ahmed, Suma Bhat, Mohammed Isham, Waseem Ahmed, Ramis M. K. |
10.5120/474-780
|
Shamsheer Ahmed, Suma Bhat, Mohammed Isham, Waseem Ahmed, Ramis M. K. . Pre-Parallelization Exercises in Budget-Constrained HPC Projects: A Case Study in CFD. International Journal of Computer Applications. 1, 26 ( February 2010), 93-95. DOI=10.5120/474-780
Abstract
Projects associated with the Grand Challenge Applications (GCAs) often involve large multi-disciplinary teams, are well funded and have access to good computational resources. The code base used in these projects is mature and well maintained and may have gone through multiple revisions spanning decades. Parallelization of this serial code to enable execution on a distributed multi-computer architecture or a shared memory multi-processor system is the next immediate step. Parallelization of serial code used by young researchers working on GCA-related applications in privately-funded institutions, on the other-hand, is not as straightforward. These researchers work under tight budget and resource constraints and do not have much access to funds or experienced programmers as their other counterparts. Initial findings from a case study are presented that show how such limitations can be alleviated by inter-departmental collaboration involving undergraduate students’ final year projects. Code developed by a single programmer over a period of about three years for the Conjugate Heat Transfer problem in Computational Fluid Dynamics (CFD) has been used for the study.
References
- K. Asanovic, R. Bodik, B. C. Catanzaro, J. J. Gebis, P. Husbands, K. Keutzer, D. A. Patterson, W. L.Plishker, J. Shalf, S. W. Williams, and K. A. Yelick. The landscape of parallel computing research: A View from Berkeley. Technical Report, UCB/EECS-2006-183, EECS Department, University of California, Berkeley, Dec 2006.
- P. Boulet, A. Darte, G.-A. Silber, and F. Vivien. Loop parallelization algorithms: From parallelism extraction to code generation. Parallel Computing, 24(3-4), 1988.
- D. E. Culler, J. P. Singh, and A. Gupta. Parallel Computer Architecture. Morgan Kauffman, 1999.
- T. R. Halfhill. Parallel processing with CUDA. Microprocessor Report, Reed Electronics Group,January 2008.
- L. Hochstein and V. R. Basili. The ASC-Alliance projects: A case study of large-scale parallel scientific code development. IEEE Computer, 41(3), 2008.
- K. Hwang. Advanced Computer Architecture. McGraw Hill, 1993.
- W.-M. Hwu, S. Ryoo, S.-Z. Ueng, J. H. Kelm,I. Gelado, S. S. Stone, R. E. Kidd, S. S. Baghsorkhi, A. A. Mahesri, S. C. Tsao, N. Navarro, S. S. Lumetta,M. I. Frank, and S. J. Patel. Implicitly parallel programming models for thousand-core microprocessors. In DAC ’07: Proceedings of the 44th annual conference on Design automation, pages 754–759, New York, NY, USA, 2007. ACM.
- D. E. Knuth. The Art of Computer Programming, Volume 1. Pearson Education, Third Edition.
- P. Lee and Z. M. Kedem. Automatic data and computation decomposition on distributed memory parallel computers. ACM Transactions on Programming Languages and Systems, 24(1), January 2002.
- S.-W. Liao. SUIF Explorer: An Interactive and Inter-procedural Parallelizer. PhD thesis, Stanford, 2000.
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