An optimal lower bound on the maximum speedup in multiprocessors with clusters

We consider an ideal multiprocessor system with q processors and a centralized scheduler without overhead that selects processes from one common pool, permitting dynamic relocation of processes. A parallel program P consisting of n processes is executed on this system and terminates when all processes are completed. Due to synchronizations, processes may be blocked while waiting for events in other processes. The parallel program is executed using some schedule of processes to processors, resulting in a speedup /spl sigma/. We then consider an ideal multiprocessor with k clusters containing u processors each. In this system processes may not be relocated between clusters. Finding a schedule which results in maximum speedup is NP-hard. Here, we present a formula for the optimal lower bound on the maximum speedup for program P, as a function of q, n, /spl sigma/, k and u. We also present a formula for the optimal lower bound when the number of processes (n) is unknown. Using these results we are able to decide if a certain schedule is close to optimal or if it is worth-while to look for other schedules. This is demonstrated by evaluating the speedup of a specific schedule of a particular program.<
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