A novel algorithm for mapping parallel applications in computational grid environments

This work explains a heuristic algorithm, task self mapping algorithm (TSMA), for mapping parallel applications in computational grids. The strategy of the algorithm is that each task of a parallel application has an associated execution cost, which is the execution cost of the processor on which the task maps, and each of them minimises its associated execution cost by mapping itself on a new processor. While each task is optimising its execution cost also means that the application execution cost is being optimised. Experimental results have shown that TSMA produces better mapping solutions than graph partitioning based mapping algorithms.