Thorsten Kurth | DeepAI

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∙ 06/14/2023

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

Modern climate projections lack adequate spatial and temporal resolution...

8 Sungduk Yu, et al. ∙

∙ 06/06/2023

Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere

Fourier Neural Operators (FNOs) have proven to be an efficient and effec...

6 Boris Bonev, et al. ∙

∙ 08/08/2022

FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators

Extreme weather amplified by climate change is causing increasingly deva...

8 Thorsten Kurth, et al. ∙

∙ 02/22/2022

FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

FourCastNet, short for Fourier Forecasting Neural Network, is a global d...

64 Jaideep Pathak, et al. ∙

∙ 10/21/2021

MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems

Scientific communities are increasingly adopting machine learning and de...

29 Steven Farrell, et al. ∙

∙ 10/13/2020

IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads

The drug discovery process currently employed in the pharmaceutical indu...

0 Aymen Al Saadi, et al. ∙

∙ 09/30/2020

Using Machine Learning to Augment Coarse-Grid Computational Fluid Dynamics Simulations

Simulation of turbulent flows at high Reynolds number is a computational...

0 Jaideep Pathak, et al. ∙

∙ 09/11/2020

Hierarchical Roofline Performance Analysis for Deep Learning Applications

This paper presents a practical methodology for collecting performance d...

0 Charlene Yang, et al. ∙

∙ 09/09/2020

Time-Based Roofline for Deep Learning Performance Analysis

Deep learning applications are usually very compute-intensive and requir...

0 Charlene Yang, et al. ∙

∙ 10/29/2019

Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs

Uncertainty quantification for forward and inverse problems is a central...

42 Liu Yang, et al. ∙

∙ 10/03/2018

Exascale Deep Learning for Climate Analytics

We extract pixel-level masks of extreme weather patterns using variants ...

0 Thorsten Kurth, et al. ∙

∙ 10/03/2018

Simulating the weak death of the neutron in a femtoscale universe with near-Exascale computing

The fundamental particle theory called Quantum Chromodynamics (QCD) dict...

0 Evan Berkowitz, et al. ∙

∙ 12/26/2017

Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer

We explore scaling of the standard distributed Tensorflow with GRPC prim...

0 Amrita Mathuriya, et al. ∙

∙ 11/09/2017

Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC

There has been considerable recent activity applying deep convolutional ...

0 Wahid Bhimji, et al. ∙

∙ 08/17/2017

Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data

This paper presents the first, 15-PetaFLOP Deep Learning system for solv...

0 Thorsten Kurth, et al. ∙

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