Michael A. Matheson

Publication Activity (10 Years)

Years Active: 1992-2023
Publications (10 Years): 15

Top Topics

Physicochemical Properties

Low Rank Approximation

Benchmark Suite

Top Venues

Publications

Darren J. Hsu, Hao Lu, Aditya Kashi, Michael A. Matheson, John Gounley, Feiyi Wang, Wayne Joubert, Jens Glaser
TwoFold: Highly accurate structure and affinity prediction for protein-ligand complexes from sequences. Int. J. High Perform. Comput. Appl. 37 (6) (2023)
Hao Lu, Piyush Sao, Michael A. Matheson, Ramakrishnan Kannan, Feiyi Wang, Thomas E. Potok
Optimizing Communication in 2D Grid-Based MPI Applications at Exascale. EuroMPI (2023)
Hao Lu, Michael A. Matheson, Vladyslav Oles, J. Austin Ellis, Wayne Joubert, Feiyi Wang
Climbing the Summit and Pushing the Frontier of Mixed Precision Benchmarks at Extreme Scale. SC (2022)
Joshua Romero, Junqi Yin, Nouamane Laanait, Bing Xie, M. Todd Young, Sean Treichler, Vitalii Starchenko, Albina Y. Borisevich, Alex Sergeev, Michael A. Matheson
Accelerating Collective Communication in Data Parallel Training across Deep Learning Frameworks. NSDI (2022)
Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Michael A. Matheson, Haesun Park
PLANC: Parallel Low-rank Approximation with Nonnegativity Constraints. ACM Trans. Math. Softw. 47 (3) (2021)
Drew Schmidt, Bronson Messer, M. Todd Young, Michael A. Matheson
Towards the Development of Entropy-Based Anomaly Detection in an Astrophysics Simulation. CoRR (2020)
Srinivas Eswar, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Michael A. Matheson, Haesun Park
PLANC: Parallel Low Rank Approximation with Non-negativity Constraints. CoRR (2019)
Nouamane Laanait, Joshua Romero, Junqi Yin, M. Todd Young, Sean Treichler, Vitalii Starchenko, Albina Y. Borisevich, Alex Sergeev, Michael A. Matheson
Exascale Deep Learning for Scientific Inverse Problems. CoRR (2019)
Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett H. Phillips, Ankur Mahesh, Michael A. Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston
Exascale deep learning for climate analytics. SC (2018)
Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett H. Phillips, Ankur Mahesh, Michael A. Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston
Exascale Deep Learning for Climate Analytics. CoRR (2018)
Drew Schmidt, Junqi Yin, Michael A. Matheson, Bronson Messer, Mallikarjun Shankar
Defining Big Data Analytics Benchmarks for Next Generation Supercomputers. CoRR (2018)
Drew Schmidt, Wei-Chen Chen, Michael A. Matheson, George Ostrouchov
Programming with BIG Data in R: Scaling Analytics from One to Thousands of Nodes. Big Data Res. 8 (2017)
Peter Xenopoulos, Jamison Daniel, Michael A. Matheson, Sreenivas Sukumar
Big data analytics on HPC architectures: Performance and cost. IEEE BigData (2016)
Sreenivas R. Sukumar, Ramakrishnan Kannan, Seung-Hwan Lim, Michael A. Matheson
Kernels for scalable data analysis in science: Towards an architecture-portable future. IEEE BigData (2016)
Sreenivas R. Sukumar, Michael A. Matheson, Ramakrishnan Kannan, Seung-Hwan Lim
Mini-apps for high performance data analysis. IEEE BigData (2016)
Margaret Drouhard, Chad A. Steed, Steven Hahn, Thomas Proffen, Jamison Daniel, Michael A. Matheson
Immersive visualization for materials science data analysis using the Oculus Rift. IEEE BigData (2015)
Michael A. Matheson, Allan D. Grosvenor, Alexander A. Zheltovodov
Shock wave / turbulent boundary layer interactions. SC Companion (2011)
Robert S. MacLeod, Christopher R. Johnson, Michael A. Matheson
Visualization blackboard-visualizing bioelectric fields. IEEE Computer Graphics and Applications 13 (4) (1993)
Christopher R. Johnson, Robert S. MacLeod, Michael A. Matheson
Computational Medicine: Bioelectric Field Problems. Computer 26 (10) (1993)
Robert S. MacLeod, N. E. Harrison, Christopher R. Johnson, Michael A. Matheson
Visualization of Cardiac Bioelectricty - A Case Study. IEEE Visualization (1992)