Daniel Milroy is a computer scientist at the Center for Applied Scientific Computing. His research focuses on graph-based scheduling and dynamic resource management for high-performance computing (HPC) and cloud-converged environments. He leads an LDRD project on cloud and HPC converged computing and collaborates closely with industry and academia.

Dan is a developer of the Fluxion directed graph-based scheduler in the Flux Framework and has worked on the PRUNERS project.

Dan holds a Ph.D. and M.S. in Computer Science from the University of Colorado Boulder, and an A.B. in Physics from the University of Chicago. His graduate research background is numerical analysis and software quality assurance and correctness for climate simulations. He focused on improving statistical consistency testing for the National Center for Atmospheric Research Community Earth System Model (CESM), and on developing a root cause analysis framework for CESM.

 

Ph.D. Computer Science, University of Colorado Boulder

M.S. Computer Science, University of Colorado Boulder

A.B. Physics, University of Chicago

You can find Dan's publications on his Google Scholar and ResearchGate pages.

• 2022: Director's Science and Technology (S&T) Award for Flux: A Hierarchical Workload Manager for Supercomputing Workflows
• 2022: Best Paper Award, eScience'22
• 2021: R&D 100 Award for Flux: Next-Generation Workload Management Software Framework

Assorted Presentations and Podcasts

• Fluence: Approaching a Converged Computing Environment
• KubeFlux: An HPC Scheduler Plugin for Kubernetes (the project is now called Fluence)
• Let's Talk Exascale podcast: The Flux Software Framework Manages and Schedules Modern Supercomputing Workflows
• KubeFlux, a scheduler plugin bridging the cloud HPC gap