2022 R&D 100 Award for Flash-X, a Multiphysics Simulation Software

  • Dubey, Anshu (Recipient), Messer II, Bronson (Recipient), Harris, Austin (Recipient), Papatheodore, Thomas (Recipient), Endeve, Eirik (Recipient), Hix, W Raphael (Recipient), Weide, Klaus (Recipient), O'Neal, Jared (Recipient), Dhruv, Akash (Recipient), Rudi, Johann (Recipient), Klosterman, Tom (Recipient), Jain, Rajeev (Recipient), Rich, Paul M. (Recipient), Riley, Katherine M. (Recipient), Couch, Sean (Recipient), Wahib, Mohammed (Recipient), Ricker, Paul (Recipient), Lee, Dongwook (Recipient), Ganapathy, Muralikrishnan (Recipient), Pajkos, Michael (Recipient), Chu, Ran (Recipient), Daley, Christopher (Recipient), Antypas, Katie (Recipient), Gopal, Shravan Kumar (Recipient), Bachan, John (Recipient) & Townsley, Dean M. (Recipient)

Prize: Honorary award

Description

Flash-X is a highly flexible software instrument that uses a combination of partial and ordinary differential and algebraic equations to simulate different types of physical phenomena, including astrophysics, computational fluid dynamics and cosmology.

The technology is highly accessible; Flash-X has a performance portability layer that is language agnostic, making it compatible with a variety of computer systems. The open-source software features components in an easily customizable plug-and-play mode for most scientific applications. The configuration of specific applications is divided into smaller portions so that each individual configuration tool remains relatively simple. Flash-X also publishes its auditing and quality control processes and features.

A previous version of the software, FLASH, was employed for a variety of scientific discovery purposes over the past decade but is no longer fully compatible with state-of-the-art computing systems and supercomputers, especially hybrid CPU-GPU systems like the Frontier and upcoming Aurora supercomputers at ORNL and ANL, respectively. FLASH was used as a tool to teach astrophysical concepts, and Flash-X could be employed for teaching purposes, as well.

Funding for this project was provided by the DOE Office of Science’s Advanced Scientific Computing Research program as part of the Exascale Computing Project, a joint effort of two DOE organizations, the Office of Science and the National Nuclear Security Administration.

Argonne’s Anshu Dubey led the development. Research contributors included ORNL’s Bronson Messer, J. Austin Harris, Thomas Papatheodore, Eirik Endeve and William Raphael Hix; Argonne’s Klaus Weide, Jared O’Neal, Akash Dhruv, Johann Rudi, Tom Klosterman, Rajeev Jain, Paul M. Rich and Katherine M. Riley; Michigan State University’s Sean M. Couch; RIKEN Center for Computational Science’s Mohammed Wahib; the University of Illinois’ Paul Ricker; the University of California Santa Cruz’s Dongwook Lee; Google’s Muralikrishnan Ganapathy; California Institute of Technology’s Michael Pajkos; the University of Tennessee’s Ran Chu; Lawrence Berkeley National Laboratory’s Christopher Steven Daley and Katie Antypas; Amazon’s Shravan Kumar Gopal; Nvidia’s John Bachan; and the University of Alabama’s Dean M. Townsley.

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