The results more » are extended further to implement an allocation strategy using more than one GC and derive the relationship between the GC's used and the corresponding ability of detecting the availability of various subcubes. Both are shown to be optimal but it is shown that the GC strategy outperforms the buddy strategy in detecting the availability of subcubes.
Hypercube scheme code#
A processor allocation strategy using the buddy system, called the buddy strategy, is discussed first and then a new allocation strategy using a Gracy code (GC), called the GC strategy, is proposed. The main objective in both problems is to maximize the utilization of available resources as well as minimize the inherent system fragmentation. The processor allocation problem in a n-dimensional hypercube (or an n-cube) multiprocessor is similar to the conventional memory allocation problem. As for minimizing mesh-connected system fragmentation caused by this strategy, two approaches-one by limiting the number of allowable submesh sizes and the other by using compaction-are simulated and discussed. To reduce the cost, the possibility of parallel migration was investigated, especially in systems under circuit-switched mode of operation. Compaction is considered for minimizing hypercube-connected system fragmentation. An efficient implementation is presented, with results indicating the strategy performs empirically better than a previous strategy based on the buddy principle. The strategy is able to allocate a submesh of the exact size requested by an incoming task, completely avoiding internal fragmentation. On the recognition of available submeshes, a strategy is developed which applies to any mesh system and recognizes submeshes with arbitrary sizes at any locations. Analytical and experimental more » results show that it compared favorably, in most of the situations, with any other known allocation schemes of the same subcube recognition ability. The strategy has two efficient implementations. In this research, the author develops a strategy, which involves collapsing the binary tree representations of a hypercube successively, capable of complete subcube recognition. Some of them recognize only part of possible subcubes others achieve complete subcube recognition but with high complexity. Several schemes have been proposed to recognize available subcubes. The main objective of this research is to investigate these two key issues in hypercube-connected and mesh-connected systems. There are two key issues for processor resource management in partitionable parallel computers-maximizing the recognition of available subsystems and minimizing system fragmentation. The characteristic of the hypercube fragmentation is that even if a sufficient number of processors are available in the hypercube, they do not form a subcube large enough to accommodate an incoming job. Using this algorithm, one may obtain a minimum-finishing-time schedule in polynomial time. The allocation policy is called ) algorithm is presented that decides if all k jobs can be finished by a given deadline. Since it uses similar types of hardware to the hypercube, it is relatively easy to adapt existing hypercube multiprocessors to the suggested network for better performance.This paper presents an efficient processor allocation policy for hypercube computers. A network with better performance and less hardware is proposed as an alternative to the hypercube. Since it uses similar types of hardware to the hypercube, it is relatively easy to adapt existing hypercube multiprocessors to the suggested network for better performance.ĪB - Previous research showed that the hypercube network does not use its extra hardware very efficiently. N2 - Previous research showed that the hypercube network does not use its extra hardware very efficiently. T1 - ENHANCEMENT SCHEME FOR HYPERCUBE INTERCONNECTION NETWORKS.
0 kommentar(er)
