摘要
提出并行计算熵的概念以及基于并行计算熵的同构集群负载均衡算法．理论分析证明并行计算熵作为系统负载均衡程度度量的合理性．算法以并行计算熵来衡量集群系统中节点之间负载均衡程度,以节点任务运算量来衡量节点的负载信息,并根据并行计算熵来进行负载迁移决策．实验证明相对基于任务数阈值的负载均衡算法并行计算性能有一定提高．
The parallel computing entropy （PCE） was defined to measure the load equilibrium in Beowulf systems and the rule of PCE maximization was proposed. On this basis, a novel algorithm was presented to balance the loads among computing nodes. Task amount instead of task number was employed to measure the load dispatched to nodes in the algorithm. A load was transferred from its original node to another if such a transfer could increase the PCE. The association between the entropy and the program executing time was evaluated. The algorithm was applied to the multiplication of large scale matrices as an example to show its effectiveness. The experimental results indicate that the PCE and executing time are highly associated and the algorithm is effective.
出处
《深圳大学学报（理工版）》
EI
CAS
北大核心
2007年第1期64-68,共5页
Journal of Shenzhen University(Science and Engineering)
基金
国家自然科学基金资助项目(60572102)
深圳市科技计划项目(200506)
关键词
同构集群
并行计算
并行计算熵
负载均衡
负载迁移
isomorphic beowulf
parallel computing
parallel computing entropy
load balance
load transfer
