collaborators

5 papers

cs.DC2021

ExaWorks: Workflows for Exascale

Aymen Al-Saadi, Dong H. Ahn, Yadu Babuji +12

Exascale computers will offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications to accelerate scientific dis…

cs.DC2021

Pandemic Drugs at Pandemic Speed: Infrastructure for Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers

Agastya P. Bhati, Shunzhou Wan, Dario Alfè +26

The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottle…

cs.DC2021

Design and Performance Characterization of RADICAL-Pilot on Leadership-class Platforms

Andre Merzky, Matteo Turilli, Mikhail Titov +2

Many extreme scale scientific applications have workloads comprised of a large number of individual high-performance tasks. The Pilot abstraction decouples workload specification,…

cs.DC2020

Scalable HPC and AI Infrastructure for COVID-19 Therapeutics

Hyungro Lee, Andre Merzky, Li Tan +15

COVID-19 has claimed more 1 million lives and resulted in over 40 million infections. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. In response, the DOE re…

cs.DC2020

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…