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Title: Hot-Spot Avoidance With Multi-Pathing Over Infiniband: An MPI Perspective

Conference ·

Large scale InfiniBand clusters are becoming increasingly popular, as reflected by the TOP 500 Supercomputer rankings. At the same time, fat tree has become a popular interconnection topology for these clusters, since it allows multiple paths to be available in between a pair of nodes. However, even with fat tree, hot-spots may occur in the network depending upon the route configuration between end nodes and communication pattern(s) in the application. To make matters worse, the deterministic routing nature of InfiniBand limits the application from effective use of multiple paths transparently and avoid the hot-spots in the network. Simulation based studies for switches and adapters to implement congestion control have been proposed in the literature. However, these studies have focused on providing congestion control for the communication path, and not on utilizing multiple paths in the network for hot-spot avoidance. In this paper, we design an MPI functionality, which provides hot-spot avoidance for different communications, without a priori knowledge of the pattern. We leverage LMC (LID Mask Count) mechanism of InfiniBand to create multiple paths in the network and present the design issues (scheduling policies, selecting number of paths, scalability aspects) of our design. We implement our design and evaluate it with Pallas collective communication and MPI applications. On an InfiniBand cluster with 48 processes, collective operations like MPI All-to-all Personalized and MPI Reduce Scatter show an improvement of 27% and 19% respectively. Our evaluation with MPI applications like NAS Parallel Benchmarks and PSTSWM on 64 processes shows significant improvement in execution time with this functionality.

Research Organization:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
W-7405-ENG-48
OSTI ID:
908380
Report Number(s):
UCRL-CONF-228725; TRN: US200722%%617
Resource Relation:
Conference: Presented at: CCGrid 07 - Seventh IEEE International Symposium on Cluster Computing and the Grid, Rio de Janeiro, Brazil, May 14 - May 17, 2007
Country of Publication:
United States
Language:
English