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