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Mochi: A Case Study in Translational Computer Science for High-Performance Computing Data Management.

Authors :
Carns, Philip
Dorier, Matthieu
Latham, Rob
Ross, Robert B.
Snyder, Shane
Soumagne, Jerome
Parashar, Manish
Abramson, David
Source :
Computing in Science & Engineering; Jul/Aug2023, Vol. 25 Issue 4, p35-41, 7p
Publication Year :
2023

Abstract

High-performance computing (HPC) has become an indispensable tool for solving diverse problems in science and engineering. Harnessing the power of HPC is not just a matter of efficient computation, however; it also calls for the efficient management of vast quantities of scientific data. This presents daunting challenges: rapidly evolving storage technology has motivated a shift toward increasingly complex, heterogeneous storage architectures that are difficult to optimize, and scientific data management needs have become every bit as diverse as the application domains that drive them. There is a clear need for agile, adaptable storage solutions that can be customized for the task and platform at hand. This motivated the establishment of the Mochi composable data service project. The Mochi project provides a library of robust, reusable, modular, and connectable data management components and microservices along with a methodology for composing them into specialized distributed data services. Mochi enables rapid deployment of custom data services with a high degree of developer productivity while still effectively leveraging cutting-edge HPC hardware. This article explores how the principles of translational computer science have been applied in practice in Mochi to achieve these goals. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15219615
Volume :
25
Issue :
4
Database :
Complementary Index
Journal :
Computing in Science & Engineering
Publication Type :
Academic Journal
Accession number :
175527643
Full Text :
https://doi.org/10.1109/MCSE.2023.3326436