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Creators/Authors contains: "Chard, Ryan"

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  1. ; ; ; ; ; ( , SC'23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis)
  2. ; ; ; ; ; ; ; ( , Future Generation Computer Systems)
    Free, publicly-accessible full text available May 1, 2024
  3. ; ; ; ; ; ( , IEEE/ACM International Workshop on Interoperability of Supercomputing and Cloud Technologies (SuperCompCloud))
  4. ; ; ; ; ; ; ; ( , 18th International Conference on e-Science (e-Science))
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  5. ; ; ; ; ; ; ; ; ; ; et al ( , IEEE Transactions on Parallel and Distributed Systems)
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  6. ; ; ; ; ; ; ; ; ; ( , Scientific Data)
    Abstract

    A concise and measurable set of FAIR (Findable, Accessible, Interoperable and Reusable) principles for scientific data is transforming the state-of-practice for data management and stewardship, supporting and enabling discovery and innovation. Learning from this initiative, and acknowledging the impact of artificial intelligence (AI) in the practice of science and engineering, we introduce a set of practical, concise, and measurable FAIR principles for AI models. We showcase how to create and share FAIR data and AI models within a unified computational framework combining the following elements: the Advanced Photon Source at Argonne National Laboratory, the Materials Data Facility, the Data and Learning Hub for Science, and funcX, and the Argonne Leadership Computing Facility (ALCF), in particular the ThetaGPU supercomputer and the SambaNova DataScale®system at the ALCF AI Testbed. We describe how this domain-agnostic computational framework may be harnessed to enable autonomous AI-driven discovery.

     
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  7. ; ; ; ; ; ; ; ; ; ; et al ( , Patterns)
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  8. ; ; ; ; ; ; ; ( , 2021 IEEE 17th International Conference on eScience (eScience))
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  9. ; ; ; ; ; ( , Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing (HPDC))
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  10. ; ; ; ; ; ; ( , 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW))
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