ANDES - EVALUATING MAPPING STRATEGIES WITH SYNTHETIC PROGRAMS

This paper presents the ANDES performance evaluation tool, ANDES is ba sed on the synthetic execution of parallel programs and it is used for the evaluation of mapping strategies. The Meganode, a distributed mem ory parallel computer, is considered as our target architecture, ANDES takes into account a benchmark of quantitative models of parallel alg orithms and a set of mapping strategies (greedy and iterative algorith ms are used), We show how this tool allows an extensive comparison of mapping strategies by using the benchmark the mapping strategies and d ifferent cost functions.