期刊名称：Bulletin of the Technical Committee on Data Engineering
出版年度：2020
卷号：43
期号：1
页码：35-46
出版社：IEEE Computer Society
摘要：The Adaptable I/O System (ADIOS) represents the culmination of substantial investment in ScientificData Management, and it has demonstrated success for several important extreme-scale science cases.However, looking towards the exascale and beyond, we see the development of yet more stringent datamanagement requirements that require new abstractions. Therefore, there is an opportunity to attempt toconnect the traditional realms of HPC I/O optimization with the Database / Data Management community.In this paper, we offer some specific examples from our ongoing work in managing data structures,services, and performance at the extreme scale for scientific computing. Using the publish/subscribemodel afforded by ADIOS, we demonstrate a set of services that connect data format, metadata, queries,data reduction, and high-performance delivery. The resulting publish/subscribe framework facilitatesconnection to on-line workflow systems to enable the dynamic capabilities that will be required for exascalescience..
