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SWAS: Stealing Work using Approximate System-load Information

机译:SWAS:使用近似系统负载信息窃取工作

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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.
机译:本文探讨了利用近似系统负载信息的潜力,以增强分层多核系统中动态负载平衡的工作窃取工作。维护有关系统的负载的信息尚未被广泛研究,因为假设介绍性能开销。我们提出了一种基于紧凑位向量结构和轻量级更新操作来检索和使用此类信息的轻量级近似方案。这种近似信息用于增强工作窃取决策的有效性。评估SWAS在多套接字多核平台上的许多代表性场景显示,通过近似系统负载信息引导的工作窃取可实现相当大的性能改进:动态,严重不平衡的工作负载最高可达18.5%;与随机工作窃取相比,具有复杂任务依赖性的工作负载高达34.4%。

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