1 citations · 1 across the 1 of their papers we have counts for
5 papers
Automated Data Readiness for Scientific AI
Sean R. Wilkinson, Valentine G. Anantharaj, Jong Youl Choi +8
Leadership computing facilities steward large-scale scientific datasets that routinely require substantial transformation before serving as AI training data. However, no existing f…
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…
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…
Enabling Seamless Transitions from Experimental to Production HPC for Interactive Workflows
Brian D. Etz, David M. Rogers, Michael J. Brim +13
The evolving landscape of scientific computing requires seamless transitions from experimental to production HPC environments for interactive workflows. This paper presents a struc…
FAIR Ecosystems for Science at Scale
Sean R. Wilkinson, Patrick Widener
High Performance Computing (HPC) centers provide resources to users who require greater scale to "get science done". They deploy infrastructure with singular hardware architectures…