44 citations · 139 across the 20 of their papers we have counts for
5 papers · 1 filter
Data optimization for large batch distributed training of deep neural networks
Shubhankar Gahlot, Junqi Yin, Mallikarjun Shankar
Distributed training in deep learning (DL) is common practice as data and models grow. The current practice for distributed training of deep neural networks faces the challenges of…
Integrating Deep Learning in Domain Sciences at Exascale
Rick Archibald, Edmond Chow, Eduardo D'Azevedo +8
This paper presents some of the current challenges in designing deep learning artificial intelligence (AI) and integrating it with traditional high-performance computing (HPC) simu…
Monte Carlo simulation of order-disorder transition in refractory high entropy alloys: a data-driven approach
Xianglin Liu, Jiaxin Zhang, Junqi Yin +3
High entropy alloys (HEAs) are a series of novel materials that demonstrate many exceptional mechanical properties. To understand the origin of these attractive properties, it is i…
IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads
Aymen Al Saadi, Dario Alfe, Yadu Babuji +33
The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2-3 billion to deliver one new drug. This is both too expensive…
Deep learning of interface structures from the 4D STEM data: cation intermixing vs. roughening
Mark P. Oxley, Junqi Yin, Nikolay Borodinov +6
Interface structures in complex oxides remain one of the active areas of condensed matter physics research, largely enabled by recent advances in scanning transmission electron mic…