Improving Performance of Batch Point-to-Point Communications by Active Contention Reduction Through Congestion-Avoiding Message Scheduling

Abstract

Communication performance plays a crucial role in both the scalability and the time-to-solution of parallel applications. The share of links in modern high-performance computer networks inevitably introduces contention for communications involving multiple point-to-point messages, thus hinders their performance. Passive contention reduction such as the congestion control of the networks can mitigate network contention but with extra protocol cost, while application-level active contention reduction such as topology mapping techniques can only reduce contention of applications with static communication patterns. In this paper, we explore a different approach to actively reduce network contention through a congestion-avoiding message scheduling algorithm, namely CAMS. CAMS determines how to inject the messages in groups to reduce contention just in time before injecting them into the network, thus it is useful in applications with dynamic communication patterns. Experiments with a 2D halo-exchange benchmark on the Tianhe-2A supercomputer shows that it can improve communication performance up to 27% when messages get large. The proposed approach can be used in conjunction with topology mapping to further improve communication performance.