PIC’s computing resources at the service of COVID-19 research
April 9, 2020Port d'Informació Científica
The Port d’Informació Científica (PIC), a research facility created by IFAE and CIEMAT to support scientific groups that require lots of computing for processing data, is putting its computing capacitiy at the service of the COVID-19 research.
PIC has been running clients of the Folding@Home collaborative computational project in part of its GPU nodes since April 1st. These nodes are normally used by IFAE researchers to analyze astrophysics or particle physics data and now they have been reconfigured to simulate protein folding as part of the Folding@Home worldwide network.
The Folding@Home project uses computer simulations to understand how proteins fold into 3D shapes to perform various functions. Viruses have proteins that they use to suppress our immune systems and reproduce themselves. To help tackle coronavirus, the simulations aim to understand how these viral proteins work to help design therapeutics to stop them.
In the coming days, the amount of resources at PIC devoted to the Folding@Home effort are expected to grow substantially, as the LHC experiments at CERN roll out a coordinated effort to dedicate part of the world-wide LHC data processing infrastructure to COVID-19 research boosting Folding@Home computing capacity. As one of the nodes in the LHC infrastructure, PIC will participate in this initiative. The results of the simulations will be published in the open repository Zenodo, run by CERN.
The Folding@Home project has got a lot of attention in the last weeks and thousands of volunteer computing resources are joining this common effort. More than one million computers are now part of the system, adding up to an estimated computing capacity of 1.5 exaflops, ten times higher than that of the world’s most powerful supercomputer.
PIC contributes to the ESCAPE Data Analysis Challenge 2021
November 23, 2021
The PIC team is running tests for the ESCAPE DAC21 to evaluate the solutions proposed for the construction of the project’s Data Lake and Science Analysis Platform. The results will be published as part of the ESCAPE project output.