A New Compacting Non-Contiguous Processor Allocation Algorithm for 2D Mesh Multicomputers

Abstract

In non-contiguous allocation, a job request can be split into smaller parts that are allocated possibly non-adjacent free sub-meshes rather than always waiting until a single sub-mesh of the requested size and shape is available. Lifting the contiguity condition is expected to reduce processor fragmentation and increase system utilization. However, the distances traversed by messages can be long, and as a result the communication overhead, especially contention, is likely to increase. The extra communication overhead depends on how the allocation request is partitioned and assigned to free sub-meshes. In this paper, a new non-contiguous processor allocation strategy, referred to as Compacting Non-Contiguous Processor Allocation Strategy (CNCPA), is suggested for the 2D mesh multicomputers. In the proposed strategy, a job is compacted into free locations. The selection of the free locations has for goal leaving large free sub-meshes in the system. To evaluate the performance improvement achieved by the proposed strategy and compare it against well-known existing non-contiguous allocation strategies, the authors conducted extensive simulation experiments. The results show that the proposed strategy can improve performance in terms of job turnaround times and system utilization.