Distributed I/O with ParaMEDIC: Experiences with a Worldwide Supercomputer
Pavan Balaji, Wu-chun Feng, Heshan Lin, Jeremy Archuleta, Satoshi Matsuoka, Andrew S. Warren, João Carlos Setúbal, Ewing L. Lusk, Rajeev Thakur, Ian T Foster, Daniel S. Katz, Subhesh Saurabh Jha, Kevin A. Shinpaugh, Susan Coghlan, Daniel A. Reed · 2008
Achieving high performance for distributed I/O on a wide-area network continues to be an elusive holy grail. Despite enhancements in network hardware as well as software stacks, achieving high-performance remains a challenge. In this paper, our worldwide team took a completely new and non-traditional approach to distributed I/O, called ParaMEDIC: Parallel Metadata Environment for Distributed I/O and Computing, by utilizing application-specific transformation of data to orders-of-magnitude smaller meta-data before performing the actual I/O. Specifically, this paper details our experiences in deploying a large-scale system to facilitate the discovery of missing genes and constructing a genome similarity tree by encapsulating the mpiBLAST sequence-search algorithm into ParaMEDIC. The overall project involved nine different computational sites spread across the U.S. generating more than a petabyte of data, that was “teleported ” to a large-scale facility in Tokyo for storage. Keywords: distributed I/O, bioinformatics, BLAST, grid computing, cluster computing. 1