Mochi:高性能计算数据管理的转化计算机科学案例研究

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computing in Science & Engineering Pub Date : 2024-02-15 DOI:10.1109/mcse.2023.3326436
Philip Carns, Matthieu Dorier, Rob Latham, Robert B. Ross, Shane Snyder, Jerome Soumagne
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引用次数: 0

摘要

高性能计算(HPC)已成为解决科学和工程领域各种问题不可或缺的工具。然而,利用高性能计算的威力不仅仅是高效计算的问题,它还要求对大量科学数据进行高效管理。这就带来了严峻的挑战:快速发展的存储技术促使存储架构向日益复杂、难以优化的异构存储架构转变,而科学数据管理的需求也与驱动这些需求的应用领域一样变得多种多样。显然,我们需要灵活、适应性强的存储解决方案,可以根据手头的任务和平台进行定制。因此,Mochi 可组合数据服务项目应运而生。Mochi 项目提供了一个强大的、可重用的、模块化的、可连接的数据管理组件和微服务库,以及将它们组合成专门的分布式数据服务的方法。Mochi 能够快速部署定制数据服务,提高开发人员的工作效率,同时还能有效利用最先进的高性能计算硬件。本文将探讨如何将转化计算机科学的原理应用到 Mochi 的实践中,以实现这些目标。
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Mochi: A Case Study in Translational Computer Science for High-Performance Computing Data Management
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.
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来源期刊
Computing in Science & Engineering
Computing in Science & Engineering 工程技术-计算机:跨学科应用
CiteScore
4.20
自引率
0.00%
发文量
77
审稿时长
6-12 weeks
期刊介绍: Physics, medicine, astronomy -- these and other hard sciences share a common need for efficient algorithms, system software, and computer architecture to address large computational problems. And yet, useful advances in computational techniques that could benefit many researchers are rarely shared. To meet that need, Computing in Science & Engineering presents scientific and computational contributions in a clear and accessible format. The computational and data-centric problems faced by scientists and engineers transcend disciplines. There is a need to share knowledge of algorithms, software, and architectures, and to transmit lessons-learned to a broad scientific audience. CiSE is a cross-disciplinary, international publication that meets this need by presenting contributions of high interest and educational value from a variety of fields, including—but not limited to—physics, biology, chemistry, and astronomy. CiSE emphasizes innovative applications in advanced computing, simulation, and analytics, among other cutting-edge techniques. CiSE publishes peer-reviewed research articles, and also runs departments spanning news and analyses, topical reviews, tutorials, case studies, and more.
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