Trace-based simulations of processor co-allocation policies in multiclusters

In systems consisting of multiple clusters of processors which employ space sharing for scheduling jobs, such as our Distributed ASCI (Advanced School for Computing Imaging) Supercomputer (DAS), co-allocation, i.e., the simultaneous allocation of processors to single jobs in multiple clusters, may be required. In this paper we study the performance of several scheduling policies for co-allocating unordered requests in multiclusters with a workload derived from the DAS. We find that beside the policy, limiting the total job size significantly improves the performance, and that for a slowdown of jobs due to global communication bounded by 1.25, co-allocation is a viable choice.