Paper Info
Title
Using MPI file caching to improve parallel write performance for large-scale scientific applications
Abstract
Typical large-scale scientific applications periodically write checkpoint files to save the computational state throughout execution. Existing parallel file systems improve such write-only I/O patterns through the use of client-side file caching and write-behind strategies. In distributed environments where files are rarely accessed by more than one client concurrently, file caching has achieved significant success; however, in parallel applications where multiple clients manipulate a shared file, cache coherence control can serialize I/O. We have designed a thread based caching layer for the MPI I/O library, which adds a portable caching system closer to user applications so more information about the application's I/O patterns is available for better coherence control. We demonstrate the impact of our caching solution on parallel write performance with a comprehensive evaluation that includes a set of widely used I/O benchmarks and production application I/O kernels.
Year
DOI
Venue
2007
10.1145/1362622.1362634
SC
Keywords
DocType
ISBN
data mining,message passing,servers,collaboration,application software,combustion,coherence,coherent control,information model,concurrent computing,control systems,cache coherence,data structures
Conference
978-1-59593-764-3
Citations 
PageRank 
References 
8
0.74
15
Authors
8
Name
Order
Citations
PageRank
Wei-keng Liao1109587.98
Avery Ching222116.21
Kenin Coloma31379.36
Arifa Nisar4744.08
Alok N. Choudhary526024.04
Jacqueline Chen624013.69
Ramanan Sankaran71158.76
Scott Klasky8154799.00