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Data Management and Storage Systems

Managing bits and bytes to maximize science insights

Argonne’s Mathematics and Computer Science Division is researching new techniques and tools for storing, transferring, accessing, and manipulating extremely large data. The goal of this work is to enable researchers to analyze, visualize, and query these large datasets to lead to new science discoveries and breakthroughs.  

Image credit: Hanqi Guo


Mathematics and Computer Science General Inquiries
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Data Libraries and Services Enabling Exascale Science

A widening gap between computational and I/O performance, deeper memory and storage hierarchies with complex organization, and massive levels of parallelism (e.g., billions of cores) are but a few of the challenges to data management at the exascale.

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High-performance research data storage system that enables dynamic data mirroring

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Cancer Biomedical Informatics Grid

Collaborative information network to accelerate discovery of new approaches for the detection, diagnosis, treatment, and prevention of cancer

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Exascale Computing in the MCS Division

Accelerating delivery of an exascale computing ecosystem to provide breakthrough modeling and simulation to address the nation’s most critical challenges

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HEP Data Analytics on HPC

Developing and deploying new tools and algorithms to enable HPC facilities to meet new data analysis demands