Publications (5)
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…
Integrating State of the Art Compute, Communication, and Autotuning Strategies to Multiply the Performance of the Application Programm CPMD for Ab Initio Molecular Dynamics Simulations
Tobias Klöffel, Gerald Mathias, Bernd Meyer
We present our recent code modernizations of the of the ab initio molecular dynamics program CPMD (www.cpmd.org) with a special focus on the ultra-soft pseudopotential (USPP) code…
Extreme Scale-out SuperMUC Phase 2 - lessons learned
Nicolay Hammer, Ferdinand Jamitzky, Helmut Satzger +36
In spring 2015, the Leibniz Supercomputing Centre (Leibniz-Rechenzentrum, LRZ), installed their new Peta-Scale System SuperMUC Phase2. Selected users were invited for a 28 day extr…
Node-Level Performance and Energy Characterization of Flagship Science Applications on SuperMUC-NG Phase 2
Salvatore Cielo, Elmira Birang, Alexander Pöppl +5
We present a systematic performance and energy-efficiency characterization of five flagship scientific workloads on SuperMUC-NG phase 2, the 28 PetaFLOPs system at the Leibniz Supe…
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…