Efficient processor management schemes for mesh-connected multicomputers

This paper investigates various processor management techniques for improving the performance of mesh-connected multicomputers. Unlike almost all prior work where the focus was on improving the submesh recognition ability of the processor allocation algorithms, this research examines other alternatives to improve system performance beyond what is achievable with usually assumed first come first served (FCFS) scheduling and any allocation. First, we use the smallest job first (SJF) policy to improve the spatial parallelism in a mesh. Next, we introduce a generic processor management scheme called multitasking and multiprogramming (M²). Then, an M² policy for mesh-connected multicomputers called virtual mesh (VM) is proposed and analyzed. The proposed VM scheme allows multiprogramming of jobs on several VMs. Finally, a novel approach called limit allocation is used for job allocation. With this scheme, a job (submesh) size is reduced if the job cannot be allocated. The objective here is to reduce the job waiting time and hence improve the overall performance. While all of the three approaches are viable alternatives to reduce the average job response time under various workloads, the VM and the limit allocation techniques are especially attractive for providing some additional features. The VM scheme brings in the concept of time-sharing execution for better efficiency and limit allocation shows how job size restriction can be beneficial for performance and fault-tolerance in a mesh topology. Moreover, the limit allocation scheme using even the simplest allocation policy can outperform any other approach.