Abstract
Load balancing involves assigning to each processor work proportional to its performance, thereby minimizing the execution time of a program. Although static load balancing can solve many problems (e.g., those caused by processor heterogeneity and nonuniform loops) for most regular applications, the transient external load due to multiple users on a network of workstations necessitates a dynamic approach to load balancing. In this paper we show that different load balancing schemes are best for different applications under varying program and system parameters. Therefore, application-driven customized dynamic load balancing becomes essential for good performance. We present a hybrid compile-time and run-time modeling and decision process which selects (customizes) the best scheme, along with automatic generation of parallel code with calls to a run-time library for load balancing.
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