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Enhancing the Performance of MPI-IO Applications by Overlapping I/O, Computation and Communication (poster presentation)

Christina Patrick, Seung Son and Mahmut Kandemir

The 13th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP 2008)
Salt Lake City, Utah, February 20-23, 2008


Many scientific applications use parallel I/O to meet the low latency and high bandwidth I/O requirement. Among many available parallel I/O operations, Collective I/O is one of the most popular methods when the storage layouts and access patterns of data do not match. The implementation of collective I/O typically involves disk I/O operations followed by interprocessor communications. Also, in many I/O-intensive applications, parallel I/O operations are usually followed by parallel computations. This paper presents a comparative study of different overlap strategies in parallel applications. We have experimented with four different overlap strategies 1) Overlapping I/O and communication; 2) Overlapping I/O and computation; 3) Overlapping computation and communication; and 4) Overlapping I/O, communication, and computation. All experiments have been conducted on a Linux Cluster and the performance results obtained are very encouraging. On an average, we have enhanced the performance of a generic collective read call by 38%, the MxM benchmark by 26%, and the FFT benchmark by 34%.

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