Nalini Kumar

According to our database, Nalini Kumar authored at least 13 papers between 2015 and 2023.

Collaborative distances:

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

2023

Artificial Intelligence for Scientific Discovery at High-Performance Computing Scales.

Kin Long Kelvin Lee, Nalini Kumar

Computer, April, 2023

Physics-Informed Representation Learning for Emergent Organization in Complex Dynamical Systems.

Adam Rupe, Karthik Kashinath, Nalini Kumar, James P. Crutchfield

CoRR, 2023

Enabling Multi-level Network Modeling in Structural Simulation Toolkit for Next-Generation HPC Network Design Space Exploration.

Sai P. Chenna, Nalini Kumar, Leonardo Borges, Michael Steyer, Philippe Thierry, Maria Garzaran

Proceedings of the High Performance Computing, 2023

Enabling Performant Thermal Conductivity Modeling with DeePMD and LAMMPS on CPUs.

Nariman Piroozan, Nalini Kumar

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Towards Foundation Models for Materials Science: The Open MatSci ML Toolkit.

Kin Long Kelvin Lee, Carmelo Gonzales, Matthew Spellings, Mikhail Galkin, Santiago Miret, Nalini Kumar

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

2019

Towards Unsupervised Segmentation of Extreme Weather Events.

Adam Rupe, Karthik Kashinath, Nalini Kumar, Victor W. Lee, Prabhat, James P. Crutchfield

CoRR, 2019

Using FPGAs to Accelerate HPC and Data Analytics on Intel-Based Systems.

Thomas Steinke, Estela Suarez, Taisuke Boku, Nalini Kumar, David E. Martin

Proceedings of the High Performance Computing, 2019

DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems.

Adam Rupe, Prabhat, James P. Crutchfield, Nalini Kumar, Vladislav Epifanov, Karthik Kashinath, Oleksandr Pavlyk, Frank Schlimbach, Mostofa Patwary, Sergey Maidanov, Victor W. Lee

Proceedings of the 2019 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2019

2018

CosmoFlow: using deep learning to learn the universe at scale.

Amrita Mathuriya, Deborah Bard, Peter Mendygral, Lawrence Meadows, James Arnemann, Lei Shao, Siyu He, Tuomas Kärnä, Diana Moise, Simon J. Pennycook, Kristyn J. Maschhoff, Jason Sewall, Nalini Kumar, Shirley Ho, Michael F. Ringenburg, Prabhat, Victor W. Lee

Proceedings of the International Conference for High Performance Computing, 2018

Scalable Behavioral Emulation of Extreme-Scale Systems Using Structural Simulation Toolkit.

Ajay Ramaswamy, Nalini Kumar, Aravind Neelakantan, Herman Lam, Greg Stitt

Proceedings of the 47th International Conference on Parallel Processing, 2018

2017

Multi-fidelity Surrogate Modeling for Application/Architecture Co-design.

Yiming Zhang, Aravind Neelakantan, Nalini Kumar, Chanyoung Park, Raphael T. Haftka, Nam H. Kim, Herman Lam

Proceedings of the High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation, 2017

2016

Behavioral Emulation for Scalable Design-Space Exploration of Algorithms and Architectures.

Nalini Kumar, Carlo Pascoe, Christopher Hajas, Herman Lam, Greg Stitt, Alan D. George

Proceedings of the High Performance Computing, 2016

2015

CMT-bone: A Mini-App for Compressible Multiphase Turbulence Simulation Software.

Nalini Kumar, Mrugesh Sringarpure, Tania Banerjee, Jason Hackl, S. Balachandar, Herman Lam, Alan D. George, Sanjay Ranka

Proceedings of the 2015 IEEE International Conference on Cluster Computing, 2015