activity
20182026
most citedTurbulence Enrichment using Physics-informed Generative Adversarial Networks

48 citations · 149 across the 7 of their papers we have counts for

collaborators

8 papers

physics.ao-ph2026

reGRAF: a global MPAS reforecast data set with convection-allowing refinements over the US and Europe

Thomas M Hamill, Akshay Subramaniam, Montgomery Flora +8

NVIDIA and The Weather Company (TWC) have generated a data set of reforecasts from TWC's GRAF (Global high-Resolution Atmospheric Forecasting) model, a version of the National Cent…

cs.LG2023★ 19 cited

ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation

Sungduk Yu, Zeyuan Hu, Akshay Subramaniam +44

Modern climate projections lack adequate spatial and temporal resolution due to computational constraints, leading to inaccuracies in representing critical processes like thunderst…

physics.ao-ph2022

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 +1

Data-driven models, such as FourCastNet (FCN), have shown exemplary performance in high-resolution global weather forecasting. This performance, however, is based on supervision on…

cs.DC2021★ 12 cited

Scalable Parallel Linear Solver for Compact Banded Systems on Heterogeneous Architectures

Hang Song, Kristen V. Matsuno, Jacob R. West +3

A scalable algorithm for solving compact banded linear systems on distributed memory architectures is presented. The proposed method factorizes the original system into two levels…

physics.flu-dyn2020★ 31 cited

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

Oliver Hennigh, Susheela Narasimhan, Mohammad Amin Nabian +7

We present SimNet, an AI-driven multi-physics simulation framework, to accelerate simulations across a wide range of disciplines in science and engineering. Compared to traditional…

cs.DC2020

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

Guang Chao Wang, Kenny Gross, Akshay Subramaniam

Deploying big-data Machine Learning (ML) services in a cloud environment presents a challenge to the cloud vendor with respect to the cloud container configuration sizing for any g…

physics.comp-ph2020★ 48 cited

Turbulence Enrichment using Physics-informed Generative Adversarial Networks

Akshay Subramaniam, Man Long Wong, Raunak D Borker +2

Generative Adversarial Networks (GANs) have been widely used for generating photo-realistic images. A variant of GANs called super-resolution GAN (SRGAN) has already been used succ…

physics.comp-ph2018★ 39 cited

A High-Order Weighted Compact High Resolution Scheme with Boundary Closures for Compressible Turbulent Flows with Shocks

A. Subramaniam, M. L. Wong, S. K. Lele

We present an improved high-order weighted compact high resolution (WCHR) scheme that extends the idea of weighted compact nonlinear schemes (WCNS's) using nonlinear interpolations…