Abstract
Large scale applications typically contain parallel loopswith many iterates. The iterates of a parallel loop may havevariable execution times which translate into performancedegradation of an application due to load imbalance. Thispaper describes a tool for load balancing parallel loopson distributed-memory systems. The tool assumes that thedata for a parallel loop to be executed is already partitionedamong the participating processors. The tool utilizesthe MPI library for interprocessor coordination, anddetermines processor workloads by loop scheduling techniques.The tool was designed independent of any application;hence, it must be supplied with a routine that encapsulatesthe computations for a chunk of loop iterates, as wellas the routines to transfer data and results between processors.Performance evaluation on a Linux cluster indicatesthat the tool reduces the cost of executing a simulated irregularloop without load balancing by up to 73%. The toolis useful for parallelizing sequential applications with parallelloops, or as an alternate load balancing routine forexisting parallel applications.
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