SWAS: Stealing Work Using Approximate System-Load Information

Paper in proceeding, 2017

This paper explores the potential of utilizing approximate system load information to enhance work stealing for dynamic load balancing in hierarchical multicore systems. Maintaining information about the load of a system has not been extensively researched since it is assumed to introduce performance overheads. We propose SWAS, a lightweight approximate scheme for retrieving and using such information, based on compact bit vector structures and lightweight update operations. This approximate information is used to enhance the effectiveness of work stealing decisions. Evaluating SWAS for a number of representative scenarios on a multi-socket multi-core platform showed that work stealing guided by approximate system load information achieves considerable performance improvements: up to 18.5% for dynamic, severely imbalanced workloads; and up to 34.4% for workloads with complex task dependencies, when compared with random work stealing.