50 citations · 52 across the 8 of their papers we have counts for
10 papers
Designing FAIR Workflows at OLCF: Building Scalable and Reusable Ecosystems for HPC Science
Sean R. Wilkinson, Patrick Widener, Sarp Oral +1
High Performance Computing (HPC) centers provide advanced infrastructure that enables scientific research at extreme scale. These centers operate with hardware configurations, soft…
From Edge to HPC: Investigating Cross-Facility Data Streaming Architectures
Anjus George, Michael Brim, Christopher Zimmer +3
In this paper, we investigate three cross-facility data streaming architectures, Direct Streaming (DTS), Proxied Streaming (PRS), and Managed Service Streaming (MSS). We examine th…
A Study on Messaging Trade-offs in Data Streaming for Scientific Workflows
Anjus George, Michael J. Brim, Christopher Zimmer +4
Memory-to-memory data streaming is essential for modern scientific workflows that require near real-time data analysis, experimental steering, and informed decision-making during e…
Scaling Up Data Parallelism in Decentralized Deep Learning
Bing Xie, Junqi Yin, Zhenyu Zhou +2
Although it has been extensively explored in theory, decentralized learning is not yet green-lighted for production use, largely due to a lack of stability, scalability, and genera…
Intelligent Sampling of Extreme-Scale Turbulence Datasets for Accurate and Efficient Spatiotemporal Model Training
Wesley Brewer, Murali Meena Gopalakrishnan, Matthias Maiterth +12
With the end of Moore's law and Dennard scaling, efficient training increasingly requires rethinking data volume. Can we train better models with significantly less data via intell…
Data Readiness for Scientific AI at Scale
Wesley Brewer, Patrick Widener, Valentine Anantharaj +4
This paper examines how Data Readiness for AI (DRAI) principles apply to leadership-scale scientific datasets used to train foundation models. We analyze archetypal workflows acros…