A heterogeneity-aware approach to load balancing of computational tasks: a theoretical and simulation study |
| |
| Authors: | Jun Huang Soo-Young Lee |
| |
| Institution: | (1) Department of Electrical and Computer Engineering, Auburn University, Auburn, AL 36849, USA |
| |
| Abstract: | One of the distinct characteristics of computing platforms shared by multiple users such as a cluster and a computational
grid is heterogeneity on each computer and/or among computers. Temporal heterogeneity refers to variation, along the time
dimension, of computing power available for a task on a computer, and spatial heterogeneity represents the variation among
computers. In minimizing the average parallel execution time of a target task on a spatially heterogeneous computing system, it is not optimal to distribute the target task linearly proportional
to the average computing powers available on computers. In this paper, effects of the temporal and spatial heterogeneity on
performance of a target task have been analyzed in terms of the mean and standard deviation of parallel execution time. Based
on the analysis results, an approach to load balancing for minimizing the average parallel execution time of a target task
is described. The proposed approach whose validity has been verified through simulation considers temporal and spatial heterogeneities
in addition to the average computing power on each computer.
|
| |
| Keywords: | Average execution time Load balancing Random variables Spatial heterogeneity Stochastic model Temporal heterogeneity |
| 本文献已被 SpringerLink 等数据库收录！ |
|
