Effect of task allocation methods for mesh-connected parallel computers considering task size limitation and machine size extension

We analyzed the behavior of task allocation methods "Two Dimensional Buddy", "Adaptive Scan" and time sharing systems that use them for mesh-connected parallel computers under task size limitation and machine size extension. The efficiency of task allocation methods for mesh-connected parallel computers is expected to be impressed by the shapes and sizes of rectangular processor partitions which are required by tasks and a machine. In general the task allocation methods are expected to improve packing ability of tasks if the number of processor for a task is limited. However the execution time of the task is expanded. We examined performance trade-off between increased packing ability and task size limitation under task size scalability. Furthermore, we examined how to extend a parallel computer efficiently. From simulation results we confirmed that task size limitation improved performance of task allocation methods and that rectangular extension is better than square extension.