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A Software Based Approach for Providing Network Fault Tolerance in Clusters with uDAPL interface: MPI Level Design and Performance Evaluation

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4 Author(s)
Vishnu, A. ; Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH ; Prachi Gupta ; Mamidala, A.R. ; Panda, D.K.

In the arena of cluster computing, MPI has emerged as the de facto standard for writing parallel applications. At the same time, introduction of high speed RDMA-enabled interconnects like InfiniBand, Myrinet, Quadrics, RDMA-enabled Ethernet has escalated the trends in cluster computing. Network APIs like uDAPL (user direct access provider library) are being proposed to provide a network-independent interface to different RDMA-enabled interconnects. Clusters with combination(s) of these interconnects are being deployed to leverage their unique features, and network failover in wake of transmission errors. In this paper, we design a network fault tolerant MPI using uDAPL interface, making this design portable for existing and upcoming interconnects. Our design provides failover to available paths, asynchronous recovery of the previous failed paths and recovery from network partitions without application restart. In addition, the design is able to handle network heterogeneity, making it suitable for the current state of the art clusters. We implement our design and evaluate it with micro-benchmarks and applications. Our performance evaluation shows that the proposed design provides significant performance benefits to both homogeneous and heterogeneous clusters. Using a heterogeneous combinations of IBA and Ammasso-GigE, we are able to improve the performance by 10-15% for different NAS parallel benchmarks on 8 times 1 configuration. For simple micro-benchmarks on a homogeneous configuration, we are able to achieve an improvement of 15-20% in throughput. In addition, experiments with simple MPI micro-benchmarks and NAS applications reveal that network fault tolerance modules incur negligible overhead and provide optimal performance in wake of network partitions

Published in:

SC 2006 Conference, Proceedings of the ACM/IEEE

Date of Conference:

Nov. 2006