A Visualization Model For Massively Parallel Algorithms

A visualization model has been deireloped to analyse the performance of a massively parallel algorithm. Most visualization tools that have beten developed so far for performance analysis are based generally on individual processor information and commltrnication patterns. These tools, however, are inadequate ,for massively parallel computations. It is difSlcult to comprehend the visual information for many processors. The model, SMIW (Scientific visualization in Multicomputing for Interpretation of Large amounts of Injformation), addresses this problem by using abstract rqpresentations to attain a composite picture which gives better insight to the behavior of the algorithm. Chernoffs Faces have been selected to represent the multidimensional data because of their abiliry to portray multidimensional data in a very perceptible manner. SMILS has been used on an asynchronous massively parallel PDE (partial direrential 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.