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Scaling parallel I/O performance through I/O delegate and caching system

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3 Author(s)
Nisar, A. ; Electr. Eng. & Comput. Sci. Dept., Northwestern Univ., Evanston, IL, USA ; Wei-Keng Liao ; Choudhary, A.

Increasingly complex scientific applications require massive parallelism to achieve the goals of fidelity and high computational performance. Such applications periodically offload checkpointing data to file system for post-processing and program resumption. As a side effect of high degree of parallelism, I/O contention at servers doesn't allow overall performance to scale with increasing number of processors. To bridge the gap between parallel computational and I/O performance, we propose a portable MPI-IO layer where certain tasks, such as file caching, consistency control, and collective I/O optimization are delegated to a small set of compute nodes, collectively termed as I/O Delegate nodes. A collective cache design is incorporated to resolve cache coherence and hence alleviates the lock contention at I/O servers. By using popular parallel I/O benchmark and application I/O kernels, our experimental evaluation indicates considerable performance improvement with a small percentage of compute resources reserved for I/O.

Published in:

High Performance Computing, Networking, Storage and Analysis, 2008. SC 2008. International Conference for

Date of Conference:

15-21 Nov. 2008