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With the rapid advance of computing technologies, it becomes more and more common to construct high-performance computing environments with heterogeneous commodity computers. Previous loop scheduling schemes were not designed for this kind of environments. Therefore, better loop scheduling schemes are needed to further increase the performance of the emerging heterogeneous PC cluster environments. In this paper, we propose a new heuristic for the performance-based approach to partition loop iterations according to the performance weighting of cluster/grid nodes. In particular, a new parameter is proposed to consider HPCC benchmark results as part of performance estimation. A heterogeneous cluster and grid were built to verify the proposed approach, and three kinds of application program were implemented for execution on cluster testbed. Experimental results show that the proposed approach performs better than the previous schemes on heterogeneous computing environments.

Loop scheduling on parallel and distributed systems has been a critical problem. Furthermore, it becomes more difficult to deal with on the emerging heterogeneous grid environments. In the past, some loop self-scheduling schemes have been proposed to be applicable to heterogeneous gird environments. In this paper, we propose a performance-based approach, which partitions loop iterations according to the performance weight of nodes. To verify the proposed approach, a grid testbed that consists four schools is built, and matrix multiplication example is implemented to be executed in this testbed. Experimental results show that the proposed approach performs better than previous schemes.