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IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads
The drug discovery process currently employed in the pharmaceutical indu...
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Using Machine Learning to Augment Coarse-Grid Computational Fluid Dynamics Simulations
Simulation of turbulent flows at high Reynolds number is a computational...
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Hierarchical Roofline Performance Analysis for Deep Learning Applications
This paper presents a practical methodology for collecting performance d...
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Time-Based Roofline for Deep Learning Performance Analysis
Deep learning applications are usually very compute-intensive and requir...
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Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs
Uncertainty quantification for forward and inverse problems is a central...
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Exascale Deep Learning for Climate Analytics
We extract pixel-level masks of extreme weather patterns using variants ...
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Simulating the weak death of the neutron in a femtoscale universe with near-Exascale computing
The fundamental particle theory called Quantum Chromodynamics (QCD) dict...
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Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer
We explore scaling of the standard distributed Tensorflow with GRPC prim...
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Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC
There has been considerable recent activity applying deep convolutional ...
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Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data
This paper presents the first, 15-PetaFLOP Deep Learning system for solv...
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