EDBT 2026 Demo / reviewers in the wild / expert
Thomas M. Evans 0001
dblp:131/7398 · also Tom M. Evans 0001
· DBLP profile ↗
4ranked-venue papers
0as first author
2since 2021 · last 2023
0000-0001-5743-3788ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 4 · 2 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
3 papers |
High-performance computing · 83% Energy-efficient computing · 7% Parallel and multicore computing · 5% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Energy systems and smart grids · 100% |
Topics — the 7 heaviest of 9, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Energy systems and smart grids
nuclear reactor simulation |
0.7 | 1 | 2023 | Exascale Multiphysics Nuclear Reactor Simulations for Advanced Designs · SC 2023 |
High-performance computing › supercomputing
exascale computing |
0.7 | 1 | 2023 | Frontier: Exploring Exascale · SC 2023 |
High-performance computing › large-scale simulation
exascale simulation |
0.7 | 1 | 2023 | Exascale Multiphysics Nuclear Reactor Simulations for Advanced Designs · SC 2023 |
High-performance computing › supercomputer architecture
exascale system architecture |
0.7 | 1 | 2023 | Frontier: Exploring Exascale · SC 2023 |
High-performance computing
scalable solver |
0.2 | 1 | 2023 | Exascale Multiphysics Nuclear Reactor Simulations for Advanced Designs · SC 2023 |
Parallel and multicore computing
parallel programming models |
0.1 | 1 | 2012 | High performance radiation transport simulations: preparing for Titan · SC 2012 |
High-performance computing
scientific computing systems |
0.1 | 1 | 2012 | High performance radiation transport simulations: preparing for Titan · SC 2012 |
Methods — techniques the papers use, named apart from their topics
spectral element discretization · 1.3monte carlo transport · 1.3high-order time splitting · 1.3multilevel energy decomposition · 0.1koch-baker-alcouffe algorithm · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Frontier: Exploring ExascaleabstractAs the US Department of Energy (DOE) computing facilities began deploying petascale systems in 2008, DOE was already setting its sights on exascale. In that year, DARPA published a report on the feasibility of reaching exascale. The report authors identified several key challenges in the pursuit of exascale including power, memory, concurrency, and resiliency. That report informed the DOE's computing strategy for reaching exascale. With the deployment of Oak Ridge National Laboratory's Frontier supercomputer, we have officially entered the exascale era. In this paper, we discuss Frontier's architecture, how it addresses those challenges, and describe some early application results from Oak Ridge Leadership Computing Facility's Center of Excellence and the Exascale Computing Project. Scott Atchley, Christopher Zimmer 0001, Jack Lange, David E. Bernholdt, Verónica G. Vergara Larrea, Michael J. Brim, Reuben D. Budiardja, Sunita Chandrasekaran, Markus Eisenbach 0002, Thomas M. Evans 0001, Matthew Ezell, Nicholas Frontiere, Antigoni Georgiadou, Joseph Glenski, Philipp Grete, Steven P. Hamilton, John K. Holmen, Axel Huebl, Daniel A. Jacobson, Wayne Joubert, Kim H. McMahon, Elia Merzari, Stan G. Moore, Andrew Myers 0001, Stephen Nichols, Sarp Oral, Thomas Papatheodore, Danny Perez, David M. Rogers 0001, Evan Schneider, Jean-Luc Vay, P. K. Yeung |
SC | 11 |
| 2023 | Exascale Multiphysics Nuclear Reactor Simulations for Advanced DesignsabstractENRICO is a coupled application developed under the U.S. Department of Energy's Exascale Computing Project (ECP) targeting the modeling of advanced nuclear reactors. It couples radiation transport with heat and fluid simulation, including the high-fidelity, highresolution Monte-Carlo code Shift and the Computational fluid dynamics code NekRS. NekRS is a highly-performant open-source code for simulation of incompressible and low-Mach fluid flow, heat transfer, and combustion with a particular focus on turbulent flows in complex domains. It is based on rapidly convergent high-order spectral element discretizations that feature minimal numerical dissipation and dispersion. State-of-the-art multilevel preconditioners, efficient high-order time-splitting methods, and runtime-adaptive communication strategies are built on a fast OCCA-based kernel library, libParanumal, to provide scalability and portability across the spectrum of current and future high-performance computing platforms. On Frontier, Nek5000/RS has recently achieved an unprecedented milestone in breaching over 1 billion spectral elements and 350 billion degrees of freedom. Shift has demonstrated the capability to transport upwards of 1 billion particles per second in full core nuclear reactor simulations featuring complete temperature-dependent, continuous-energy physics on Frontier. Shift achieved a weak-scaling efficiency of 97.8% on 8192 nodes of Frontier and calculated 6 reactions in 214,896 fuel pin regions below 1% statistical error yielding first-of-a-kind resolution for a Monte Carlo transport application. Elia Merzari, Steven P. Hamilton, Thomas M. Evans 0001, Misun Min, Paul F. Fischer, Stefan Kerkemeier, Jun Fang 0005, Paul K. Romano, Yu-Hsiang Lan, Malachi Phillips, Elliott Biondo, Katherine Royston, Timothy C. Warburton, Noel Chalmers, Thilina Ratnayaka |
SC | 3 |
| 2019 | Optimization of processor allocation for domain decomposed Monte Carlo calculations
J. Austin Ellis, Thomas M. Evans 0001, Steven P. Hamilton, C. T. Kelley, Tara M. Pandya |
Parallel Comput. | 2 |
| 2012 | High performance radiation transport simulations: preparing for TitanabstractIn this paper we describe the Denovo code system. Denovo solves the six-dimensional, steady-state, linear Boltzmann transport equation, of central importance to nuclear technology applications such as reactor core analysis (neutronics), radiation shielding, nuclear forensics and radiation detection. The code features multiple spatial differencing schemes, state-of-the-art linear solvers, the Koch-Baker-Alcouffe (KBA) parallel-wavefront sweep algorithm for inverting the transport operator, a new multilevel energy decomposition method scaling to hundreds of thousands of processing cores, and a modern, novel code architecture that supports straightforward integration of new features. In this paper we discuss the performance of Denovo on the 20+ petaflop ORNL GPU-based system, Titan. We describe algorithms and techniques used to exploit the capabilities of Titan's heterogeneous compute node architecture and the challenges of obtaining good parallel performance for this sparse hyperbolic PDE solver containing inherently sequential computations. Numerical results demonstrating Denovo performance on early Titan hardware are presented. Christopher Baker, Gregory G. Davidson, Thomas M. Evans 0001, Steven P. Hamilton, Joshua J. Jarrell, Wayne Joubert |
SC | 3 |