Semantics-based distributed I/O with the ParaMEDIC framework.

Conference · Tue Jan 01 04:00:00 EST 2008

DOI:https://doi.org/10.1145/1383422.1383444· OSTI ID:1001595

Balaji, P; Feng, W; Lin, H; Tech, Virginia

Many large-scale applications simultaneously rely on multiple resources for efficient execution. For example, such applications may require both large compute and storage resources; however, very few supercomputing centers can provide large quantities of both. Thus, data generated at the compute site oftentimes has to be moved to a remote storage site for either storage or visualization and analysis. Clearly, this is not an efficient model, especially when the two sites are distributed over a wide-area network. Thus, we present a framework called 'ParaMEDIC: Parallel Metadata Environment for Distributed I/O and Computing' which uses application-specific semantic information to convert the generated data to orders-of-magnitude smaller metadata at the compute site, transfer the metadata to the storage site, and re-process the metadata at the storage site to regenerate the output. Specifically, ParaMEDIC trades a small amount of additional computation (in the form of data post-processing) for a potentially significant reduction in data that needs to be transferred in distributed environments.

• Research Organization: Argonne National Laboratory (ANL)
• Sponsoring Organization: SC; Virginia Tech
• DOE Contract Number: AC02-06CH11357
• OSTI ID: 1001595
• Report Number(s): ANL/MCS/CP-61623
• Country of Publication: United States
• Language: ENGLISH

Related Subjects

99 GENERAL AND MISCELLANEOUS
COMPUTERS
PERFORMANCE
STORAGE