| Abstract: |
| The US Department of Energy (DOE) makes substantial investments in the production and collection of massive amounts of scientific data through supporting the user facilities and scientific software. The high performance computing (HPC) resources supported by the Office of Advanced Scientific Computing Research (ASCR) provide an ideal platform for applying scientific machine learning (SciML) on these massive data to accelerate scientific discoveries. However, an efficient, scalable, federated algorithm is necessary to apply SciML to distributed data produced at scientific user facilities. There is a push at Oak Ridge National Laboratory (ORNL) to develop the next generation of smart laboratories (https://www.ornl.gov/intersect), locally developing connections between experimental and computational facilities at ORNL. This talk will focus on recent efforts by IBM/INTERSECT/ORNL/REDHAT/SLAC to connect experimental facilities at different laboratories using federated learning. |
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