Akshay Subramaniam

According to our database, Akshay Subramaniam authored at least 10 papers between 2018 and 2023.

Collaborative distances:

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

2023

ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators.

Sungduk Yu, Walter M. Hannah, Liran Peng, Mohamed Aziz Bhouri, Ritwik Gupta, Jerry Lin, Björn Lütjens, Justus C. Will, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Anima Anandkumar, Noah D. Brenowitz, Veronika Eyring, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Carl Vondrick, Rose Yu, Laure Zanna, Ryan P. Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Gunnar Behrens, Christopher S. Bretherton, Julius J. M. Busecke, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Akshay Subramaniam, Mark A. Taylor, et al.

CoRR, 2023

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation.

Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Scalable parallel linear solver for compact banded systems on heterogeneous architectures.

Hang Song, Kristen V. Matsuno, Jacob R. West, Akshay Subramaniam, Aditya S. Ghate, Sanjiva K. Lele

J. Comput. Phys., 2022

DL-Corrector-Remapper: A grid-free bias-correction deep learning methodology for data-driven high-resolution global weather forecasting.

Tao Ge, Jaideep Pathak, Akshay Subramaniam, Karthik Kashinath

CoRR, 2022

2021

NVIDIA SimNet™: An AI-Accelerated Multi-Physics Simulation Framework.

Oliver Hennigh, Susheela Narasimhan, Mohammad Amin Nabian, Akshay Subramaniam, Kaustubh Tangsali, Zhiwei Fang, Max Rietmann, Wonmin Byeon, Sanjay Choudhry

Proceedings of the Computational Science - ICCS 2021, 2021

2020

NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework.

Oliver Hennigh, Susheela Narasimhan, Mohammad Amin Nabian, Akshay Subramaniam, Kaustubh Tangsali, Max Rietmann, José del Águila Ferrandis, Wonmin Byeon, Zhiwei Fang, Sanjay Choudhry

CoRR, 2020

ContainerStress: Autonomous Cloud-Node Scoping Framework for Big-Data ML Use Cases.

Guang Chao Wang, Kenny Gross, Akshay Subramaniam

CoRR, 2020

Turbulence Enrichment using Physics-informed Generative Adversarial Networks.

Akshay Subramaniam, Man Long Wong, Raunak D. Borker, Sravya Nimmagadda, Sanjiva K. Lele

CoRR, 2020

2019

A high-order weighted compact high resolution scheme with boundary closures for compressible turbulent flows with shocks.

Akshay Subramaniam, Man Long Wong, Sanjiva K. Lele

J. Comput. Phys., 2019

2018

A unified high-order Eulerian method for continuum simulations of fluid flow and of elastic-plastic deformations in solids.

Niranjan S. Ghaisas, Akshay Subramaniam, Sanjiva K. Lele

J. Comput. Phys., 2018