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Yi Pan Department of Computer Science The University of Dayton 300 College Park Dayton, OH 45469-2160 pan@cps.udayton.eduBrief Description of Application:
Number of Lines of Code: 1726
Target Platforms and HPF Compilers Used:
Coding Styles (data decompositions, computational methods):
Performance Information, if Available (including any possible comparisons to MPI and/or OpenMP):
Experimental runs show that the execution time is reduced drastically through parallel computing. Due to the requirement of the HPF compiler I used, many huge arrays have to be initialized before their usage, a lot of overhead is introduced. However, the code is still scalable up to 98 processors on the Cray T3E. Compared with MPI and PFA implementations, the HPF implementation has almost the similar efficiency with much less porting effort. Based on the experimentation carried out in this researc, we believe that a high level parallel programming language such as the High Performance Fortran is a fast, viable and economical approach to parallelize many existing sequential codes which exhibit a lot of parallelism.
Please comment on any aspects of the application that might be interesting, including any problems using HPF effectively:
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