Globus service enhancements for exascale applications and facilities

Author:

Zheng Weijian1ORCID,Kordas Jack2,Skluzacek Tyler J3,Kettimuthu Raj1,Foster Ian14ORCID

Affiliation:

1. Data Science and Learning Division, Argonne National Laboratory, Lemont, IL, USA

2. Globus, University of Chicago, Chicago, IL, USA

3. National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA

4. Department of Computer Science, University of Chicago, Chicago, IL, USA

Abstract

Many extreme-scale applications require the movement of large quantities of data to, from, and among leadership computing facilities, as well as other scientific facilities and the home institutions of facility users. These applications, particularly when leadership computing facilities are involved, can touch upon edge cases (e.g., terabyte files) that had not been a focus of previous Globus optimization work, which had emphasized rather the movement of many smaller (megabyte to gigabyte) files. We report here on how automated client-driven chunking can be used to accelerate both the movement of large files and the integrity checking operations that have proven to be essential for large data transfers. We present detailed performance studies that provide insights into the benefits of these modifications in a range of file transfer scenarios.

Funder

Exascale Computing Project

U.S. Department of Energy Office of Science

National Nuclear Security Administration

Publisher

SAGE Publications

Reference49 articles.

1. Energy-aware data transfer algorithms

2. Exascale applications: skin in the game

3. Protocols and services for distributed data- intensive science;Allcock W,2001

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