Scientific Computing and Imaging Institute

Background

Martin comes to SCI from the University of Leeds in the UK where he was Professor of Scientific Computing and Research Dean for Engineering. He earned his PhD in Computer Science at Leeds in 1981. He has worked in the fields of mathematical software, numerical analysis, parallel computing and more recently problem solving environments and grid computing. Much of Martin’s past work has centered around software for solving challenging applications problems in computational fluid dynamics, combustion, atmospheric modeling and lubrication modeling.

Research Interests

• Software Abstractions for Extreme-Scale Scalability of Computational Frameworks
• Extreme-scale parallel solution of complex science and engineering problems
• Runtime systems for DAG-based software at extreme parallel scales.
• Adaptive computational algorithms in scientific computing
• Interdisciplinary solution approaches to challenging applications
• High performance solution of large graph-based applications

My research is concerned with developing algorithms and software for the solution of challenging science and engineering problems both serial and parallel computers. Much of this research at present involves the use of the Uintah computational framework on a number of challenging example cases from combustion and multi-scale materials science. For example, the uintah code was used to solve complex engineering problems on some of the fastest and most powerful computers in the world.

• Program Manger (2012-2016) – Alliance for Computationally-guided Design of Energy Efficient Electronic Materials // News Release here
• CS Lead – Multidisciplinary Simulation Center (MSC) under the NNSA’s Predictive Science Academic Alliance Program II
• Advisory Committee  (2015-) – Advanced Scientific Computing Advisory Committee (ASCAC) Chair from 2024-

Media

• U of U Team Finishes Study of Massive, Mysterious Explosion
• Simulations Aimed at Safer Transport of Explosives
• Software Abstractions for Extreme-Scale Scalability of Computational Framework
• Porting Uintah to Heterogeneous Systems PASC22 Best Paper

Student Theses

• Chris Gritton – “Modeling Electrochemistry Problems using the Material Point and Finite Volume Methods.” Ph.D 2024
• John Holmen – “Portable, Scalable Approaches for Improving Asynchronous Many-Task Runtime Node Use.” Ph.D 2022
• Damodar Sahasrabudhe – :Enhancing Asynchronous Many-Task Runtime Systems for Next-Generation Architectures and Exascale Supercomputers.” Ph.D 2021
• Bradley Peterson – “Portable and Performant GPU/Heterogeneous Asynchronous Many-Task Runtime System.” Ph.D. 2019
• Alan Humphrey – “Scalable Asynchronous Many-Task Runtime Solutions to Globally Coupled Problems.” Ph.D. 2019
• Qingyu Meng – “Large-Scale Distributed Runtime System for DAG-Based Computational Framework“, Ph.D., August 2014
• Lethuy Thi Tran – “Numerical Study and Improvement of the Methods in Uintah Framework: The Material Point Method and the Implicit Continuous-Fluid Eulerian Method“, Ph.D., December 2012.
• Justin Paul Luitjens – “The Scalability of Parallel Adaptive Mesh Refinement Within Uintah“, Ph.D., May 2011.
• Daniel Edward Hart – “Adjoint Error Estimation for Elastohydrodynamic Lubrication“, Ph.D., January 2008.
• Hongqiang Lu – “High Order Finite Element Solution of Elastohydrodynamic Lubrication Problems“, Ph.D., September 2006.