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Michael A. Matheson
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2020 – today
- 2023
- [j5]Darren J. Hsu, Hao Lu
, Aditya Kashi
TwoFold: Highly accurate structure and affinity prediction for protein-ligand complexes from sequences. Int. J. High Perform. Comput. Appl. 37(6): 666-682 (2023) - [c10]Hao Lu
Optimizing Communication in 2D Grid-Based MPI Applications at Exascale. EuroMPI 2023: 9:1-9:11 - 2022
- [c9]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: 1027-1040 - [c8]Hao Lu
Climbing the Summit and Pushing the Frontier of Mixed Precision Benchmarks at Extreme Scale. SC 2022: 78:1-78:15 - 2021
- [j4]Srinivas Eswar
PLANC: Parallel Low-rank Approximation with Nonnegativity Constraints. ACM Trans. Math. Softw. 47(3): 20:1-20:37 (2021) - 2020
- [i5]Drew Schmidt, Bronson Messer, M. Todd Young, Michael A. Matheson:
Towards the Development of Entropy-Based Anomaly Detection in an Astrophysics Simulation. CoRR abs/2009.02430 (2020)
2010 – 2019
- 2019
- [i4]Srinivas Eswar, Koby Hayashi, Grey Ballard
PLANC: Parallel Low Rank Approximation with Non-negativity Constraints. CoRR abs/1909.01149 (2019) - [i3]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 abs/1909.11150 (2019) - 2018
- [c7]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: 51:1-51:12 - [i2]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 abs/1810.01993 (2018) - [i1]Drew Schmidt, Junqi Yin, Michael A. Matheson, Bronson Messer, Mallikarjun Shankar
Defining Big Data Analytics Benchmarks for Next Generation Supercomputers. CoRR abs/1811.02287 (2018) - 2017
- [j3]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: 1-11 (2017) - 2016
- [c6]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: 1026-1031 - [c5]Sreenivas R. Sukumar, Michael A. Matheson, Ramakrishnan Kannan, Seung-Hwan Lim:
Mini-apps for high performance data analysis. IEEE BigData 2016: 1483-1492 - [c4]Peter Xenopoulos, Jamison Daniel, Michael A. Matheson, Sreenivas R. Sukumar:
Big data analytics on HPC architectures: Performance and cost. IEEE BigData 2016: 2286-2295 - 2015
- [c3]Margaret Drouhard
Immersive visualization for materials science data analysis using the Oculus Rift. IEEE BigData 2015: 2453-2461 - 2011
- [c2]Michael A. Matheson, Allan D. Grosvenor, Alexander A. Zheltovodov:
Shock wave / turbulent boundary layer interactions. SC Companion 2011: 131-132
1990 – 1999
- 1993
- [j2]Robert S. MacLeod, Christopher R. Johnson, Michael A. Matheson:
Visualization blackboard-visualizing bioelectric fields. IEEE Computer Graphics and Applications 13(4): 10-12 (1993) - [j1]Christopher R. Johnson, Robert S. MacLeod, Michael A. Matheson:
Computational Medicine: Bioelectric Field Problems. Computer 26(10): 59-67 (1993) - 1992
- [c1]Robert S. MacLeod, N. E. Harrison, Christopher R. Johnson, Michael A. Matheson:
Visualization of Cardiac Bioelectricty - A Case Study. IEEE Visualization 1992: 411-418
Coauthor Index
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