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Priority research directions for in situ data management: Enabling scientific discovery from diverse data sources

机译:优先级研究方向,用于原位数据管理:从不同的数据源启用科学发现

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摘要

In January 2019, the US Department of Energy, Office of Science program in Advanced Scientific Computing Research, convened a workshop to identify priority research directions (PRDs) for in situ data management (ISDM). A fundamental finding of this workshop is that the methodologies used to manage data among a variety of tasks in situ can be used to facilitate scientific discovery from many different data sources—simulation, experiment, and sensors, for example—and that being able to do so at numerous computing scales will benefit real-time decision-making, design optimization, and data-driven scientific discovery. This article describes six PRDs identified by the workshop, which highlight the components and capabilities needed for ISDM to be successful for a wide variety of applications—making ISDM capabilities more pervasive, controllable, composable, and transparent, with a focus on greater coordination with the software stack and a diversity of fundamentally new data algorithms.
机译:2019年1月,美国能源部,科学研究计划中的科学计划办公室召开了一个讲习班,以确定原位数据管理(ISDM)的优先研究方向(PRD)。该研讨会的基本发现是,用于管理原位各种任务之间的数据的方法可用于促进来自许多不同的数据源 - 模拟,实验和传感器的科学发现 - 并且能够做到这一点因此,在许多计算尺度上,将有利于实时决策,设计优化和数据驱动的科学发现。本文介绍了由研讨会识别的六个PRD,它突出了ISDM所需的组件和功能,为各种各样的应用程序制作ISDM能力更加普遍,可控,可兼容和透明,重点是与之重新协调软件堆栈和基本上新数据算法的多样性。

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