Link-Heterogeneous Work Stealing

Random work-stealing has been proved to be extremely beneficial in dynamically load-balancing irregular applications. However, it is known to perform loosely in non-homogenous distributed systems where communications costs are a major obstacle for high performance. In this paper, we investigate the design of an effective work-stealing protocol dealing with the heterogeneity of network link latencies. We propose a generic distributed algorithm which can be easily implemented to fit different types of heterogeneity. The proposed algorithm extends on reference approaches, namely Probabilistic Work Stealing (PWS), and Adaptive Cluster-aware Random Stealing (ACRS), by introducing new adaptive control operations that are shown to be highly accurate in increasing work locality and decreasing steals cost. We provide a comprehensive analysis including: (i) a comparative study on a broad range of harsh network scenarios, and (ii) an in-depth analysis of protocols' behavior at the aim of gaining new insights into dynamic load-balancing in heterogeneous distributed environments. Over all experimented configurations, our results show that although the proposed protocol is not tailored for a specific networked platform, it can save 30% execution time in average compared to its competitors, while demonstrating high quality self-adjusting capabilities.