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Video: Managing large-scale cosmology simulations with Parsl and Singularity

Rick Wagner from Globus gave this talk at the Singularity User Group “We package the imSim software inside a Singularity container so that it can be developed independently, packaged to include all dependencies, trivially scaled across thousands of computing nodes, and seamlessly moved between computing systems. To date, the simulation workflow has consumed more than 30M core hours using 4K nodes (256K cores) on Argonne’s Theta supercomputer and 2K nodes (128K cores) on NERSC’s Cori supercomputer.”

ExaLearn Project to bring Machine Learning to Exascale

As supercomputers become ever more capable in their march toward exascale levels of performance, scientists can run increasingly detailed and accurate simulations to study problems ranging from cleaner combustion to the nature of the universe. Enter ExaLearn, a new machine learning project supported by DOE’s Exascale Computing Project (ECP), aims to develop new tools to help scientists overcome this challenge by applying machine learning to very large experimental datasets and simulations.