학술논문

Mochi: A Case Study in Translational Computer Science for High-Performance Computing Data Management
Document Type
Periodical
Source
Computing in Science & Engineering Comput. Sci. Eng. Computing in Science & Engineering. 25(4):35-41 Aug, 2023
Subject
Computing and Processing
Bioengineering
Communication, Networking and Broadcast Technologies
High performance computing
Database systems
Information management
Translational research
Computer science
Language
ISSN
1521-9615
1558-366X
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.