Abstract
This paper presents a cohesive, practical load balancing framework that improves upon existing strategies. These techniques are portable to a broad range of prevalent architectures, including massively parallel machines, such as the Cray T3D/E and Intel Paragon, shared memory systems, such as the Silicon Graphics PowerChallenge, and networks of workstations. As part of the work, an adaptive heat diffusion scheme is presented, as well as a task selection mechanism that can preserve or improve communication locality. Unlike many previous efforts in this arena, the techniques have been applied to two large-scale industrial applications on a variety of multicomputers. In the process, this work exposes a serious deficiency in current load balancing strategies, motivating further work in this area.
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