| Abstract |
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| This paper addresses the problem of load balancing data-parallel computations on heterogeneous and time-shared parallel computing environments, where load imbalance may be introduced by the different capacities of processors populating a computer, or by the sharing of the same computational resources among several users. To solve this problem we propose a run-time support for parallel loops based upon a hybrid (static + dynamic) scheduling strategy. The results obtained on many experiments conducted on SGI/Cray T3E and IBM SP2 systems show that our hybrid scheduling strategy, which first allocates the same amount of work to each processor, and then dynamically balances the load, yields very good performances. The main features of our novel technique are the absence of centralization and synchronization points, the prefetching of work toward slower processors, and the overlap of communication latencies with useful computation. |
| Contact |
| Salvatore Orlando Dip. di Matematica Appl. ed Informatica,Universita' Ca' Foscari di Venezia,Via Torino, 155,30173 Venezia Mestre,ITALY, orlando@dsi.unive.it |