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Optimal Many-to-Many Personalized Concurrent Communication in RapidIO-based Fat-trees
Shu Lin; Hao,Jie; Song,Yafang; Li,Chengcheng; Wang,Donglin; Shu,Lin
2016-05
Conference Name17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2016)
Source Publication17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2016)
Conference Date2016.05.30-2016.06.01
Conference PlaceShanghai,China
AbstractMany-to-many (M-to-N) personalized concurrent communication is one of the most dense traffic patterns in high performance computing system. Each node in group M sends different messages to every node in group N. Hot-spot congestions are the bottleneck of this communication pattern. In this paper, a proactive congestion avoidance mechanism is proposed to optimize many-to-many personalized concurrent traffic in RapidIO-based fat-trees. And a heuristic scheme of virtual destination is proposed to deal with the case that messages from each node in M group to every other node in N group are not of the same size. Our proactive congestion avoidance mechanism has been used in a practical network, which is a part of digital signal processing platform for “the TianLai Pathfinder”. The network delay is effectively improved, reducing from about 34.784 us to 1.484 us. And the communication overhead is decreased by twice.
KeywordMany-to-many Personalized Rapidio Fat-tree Node-level Congestion-avoidance
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11730
Collection国家专用集成电路设计工程技术研究中心
Corresponding AuthorShu,Lin
AffiliationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Shu Lin,Hao,Jie,Song,Yafang,et al. Optimal Many-to-Many Personalized Concurrent Communication in RapidIO-based Fat-trees[C],2016.
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