J. Austin Ellis

According to our database, J. Austin Ellis authored at least 10 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Optimizing Distributed Training on Frontier for Large Language Models.

Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, J. Austin Ellis, Matthias Maiterth, Guojing Cong, Feiyi Wang, Prasanna Balaprakash

Proceedings of the ISC High Performance 2024 Research Paper Proceedings (39th International Conference), 2024

2022

Training-free hyperparameter optimization of neural networks for electronic structures in matter.

Lenz Fiedler, Nils Hoffmann, Parvez Mohammed, Gabriel A. Popoola, Tamar Yovell, Vladyslav Oles, J. Austin Ellis, Sivasankaran Rajamanickam, Attila Cangi

Mach. Learn. Sci. Technol., December, 2022

Climbing the Summit and Pushing the Frontier of Mixed Precision Benchmarks at Extreme Scale.

Hao Lu, Michael A. Matheson, Vladyslav Oles, J. Austin Ellis, Wayne Joubert, Feiyi Wang

Proceedings of the SC22: International Conference for High Performance Computing, 2022

2021

Co-design Center for Exascale Machine Learning Technologies (ExaLearn).

Francis J. Alexander, James A. Ang, Jenna A. Bilbrey, Jan Balewski, Tiernan Casey, Ryan Chard, Jong Choi, Sutanay Choudhury, Bert J. Debusschere, Anthony M. DeGennaro, Nikoli Dryden, J. Austin Ellis, Ian T. Foster, Cristina Garcia-Cardona, Sayan Ghosh, Peter Harrington, Yunzhi Huang, Shantenu Jha, Travis Johnston, Ai Kagawa, Ramakrishnan Kannan, Neeraj Kumar, Zhengchun Liu, Naoya Maruyama, Satoshi Matsuoka, Erin McCarthy, Jamaludin Mohd-Yusof, Peter Nugent, Yosuke Oyama, Thomas Proffen, David Pugmire, Sivasankaran Rajamanickam, Vinay Ramakrishnaiah, Malachi Schram, Sudip K. Seal, Ganesh Sivaraman, Christine Sweeney, Li Tan, Rajeev Thakur, Brian Van Essen, Logan T. Ward, Paul M. Welch, Michael Wolf, Sotiris S. Xantheas, Kevin G. Yager, Shinjae Yoo, Byung-Jun Yoon

Int. J. High Perform. Comput. Appl., 2021

Revealing power, energy and thermal dynamics of a 200PF pre-exascale supercomputer.

Woong Shin, Vladyslav Oles, Ahmad Maroof Karimi, J. Austin Ellis, Feiyi Wang

Proceedings of the International Conference for High Performance Computing, 2021

2020

Accelerating Finite-temperature Kohn-Sham Density Functional Theory with Deep Neural Networks.

J. Austin Ellis, Attila Cangi, Normand A. Modine, J. Adam Stephens, Aidan P. Thompson, Sivasankaran Rajamanickam

CoRR, 2020

ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization.

Gordon Euhyun Moon, J. Austin Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

Optimization of processor allocation for domain decomposed Monte Carlo calculations.

J. Austin Ellis, Thomas M. Evans, Steven P. Hamilton, C. T. Kelley, Tara M. Pandya

Parallel Comput., 2019

Scalable Inference for Sparse Deep Neural Networks using Kokkos Kernels.

J. Austin Ellis, Sivasankaran Rajamanickam

Proceedings of the 2019 IEEE High Performance Extreme Computing Conference, 2019

2017

Local Improvement Results for Anderson Acceleration with Inaccurate Function Evaluations.

Alex Toth, J. Austin Ellis, Thomas M. Evans, Steven P. Hamilton, C. T. Kelley, Roger P. Pawlowski, Stuart R. Slattery

SIAM J. Sci. Comput., 2017