A visualization model has been developed to analyze the performance of a massively parallel algorithm. Most visualization tools that have been developed so far for performance analysis are based generally on individual processor information and communication patterns. These tools, however, are inadequate for massively parallel computations. It is difficult to comprehend the visual information for many processors. The model, SMILI (Scientific visualization in Multicomputing for Interpretation of Large amounts of Information), addresses this problem by using abstract representations to attain a composite picture which gives better insight to the behavior of the algorithm. Chernoff s Faces have been selected to represent the multidimensional data because of their ability to portray multidimensional data in a very perceptible manner. SMILI has been used on an asynchronous massively parallel PDE (partial differential equation) solver that is based on the multigrid paradigm. The visualization tool helps in tuning the control parameters of the multigrid algorithm to get optimal results.
R. Khanna and B. M. McMillin, "A Visualization Model For Massively Parallel Algorithms," 6th Distributed Memory Computing Conference, DMCC 1991 - Proceedings, pp. 617 - 620, article no. 633346, Institute of Electrical and Electronics Engineers, Jan 1991.
The definitive version is available at https://doi.org/10.1109/DMCC.1991.633346
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01 Jan 1991