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Keywords: data distribution visualization, scientific visualization
The next generation of language compilers for parallel architectures offers levels of abstraction above those currently available. Languages such as High Performance Fortran (HPF) and Parallel C++ (pC++) allow the programmer to specify how data structures are to be aligned relative to each other and then distributed across processors. Since a program's performance is often directly related to how its data is distributed, a means of evaluating data distributions and alignments is necessary. Since there is a natural tendency to explain data distributions by drawing pictures, graphical visualizations may be helpful in assessing the benefits and detriments of a given data decomposition. This paper formulates an experimental framework for exploring visualization techniques appropriate to evaluating data distributions. Visualizations are created using IBM's Data Explorer visualization software in conjunction with other software developed by the author. An informal assessment of the resulting visualizations and an explanation of how this research will be extended is also given.
Created: Thu Dec 12 12:34:50 1996
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