Asymmetric load balancing on a heterogeneous cluster of PCs

With commercial supercomputers and homogeneous clusters of PCs, static load balancing is accomplished by assigning equal tasks to each processor. With heterogeneous clusters, system designers have the option of adding newer hardware that is more powerful than existing hardware. When this is done, assignment of equal tasks to each processor yields suboptimal performance. This research addresses techniques by which the sizes of the tasks are suitably matched to the processors and memories. Thus, more powerful nodes do more work, and less powerful nodes perform less work. We find Mat when, the range of processing power is narrow, some benefit can be achieved with asymmetric load balancing. When the range of processing pourer is broad, dramatic improvements in. performance are realized - our experiments have shown up to 92% improvement when asymmetrically load balancing a modified version of the NAS Parallel Benchmarks' LU application on a heterogeneous cluster of Linux-powered PCs.