A Simulation Study of Data Partitioning Algorithms for Multiple Clusters

Abstract— Recently we proposed algorithms for concurrent execution on multiple clusters [9]. In this case, data partitioning is done at two levels; first, the data is distributed to a collection of heterogeneous parallel systems with different resources and startup time, then, on each system the data is evenly partitioned to the available nodes. In this paper, we report on a simulation study of the algorithms.

• Type: Conference
• Year: 2007
• Where: CCGRID
• Authors: Chen Yu, Dan C. Marinescu, Howard Jay Siegel, John P. Morrison
• Keywords: CCGRID 2007, Cluster Computing, Concurrent Execution, Heterogeneous Parallel Systems, Multiple Clusters