Organizers

Workshop Chairs

Pete Mendygral (Hewlett Packard Enterprise)

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Pete Mendygral is a Distinguished Technologist in the HPC&AI Cloud Services organization at HPE where he works on HPC in the cloud and technologies focused on productivity and efficiency for complex workloads and workflows. Pete received a PhD in astrophysics from the University of Minnesota in 2011, where he developed HPC applications to study outflows from supermassive blackholes.



Sunita Chandrasekaran (University of Delaware)

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Sunita Chandrasekaran is an Associate Professor with the Department of Computer and Information Sciences and co-directs the AI center of Excellence at the University of Delaware, USA. Her research spans HPC, compilers, exascale computing, benchmarking, machine learning and AI. Her research is also heavily interdisciplinary spanning plasma physics, biophysics, solar physics and bioinformatics. She received her Ph.D. on Tools and Algorithms for High-Level Algorithm Mapping to FPGAs from Nanyang Technological University, Singapore. She is a recipient of the 2016 IEEE-CS TCHPC Award for Excellence for Early Career Researchers in High Performance Computing. She has held various leadership positions in HPC conferences and workshops over the past several years.


Sam Foreman (Argonne National Labs)

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Sam Foreman is a computational scientist with a background in high energy physics at the ALCF. He is generally interested in the application of machine learning to computational problems in physics, particularly within the context of high performance computing. Sam’s current research focuses on using deep generative modeling to help build better sampling algorithms for simulations in lattice gauge theory.



Daniel Margala (National Energy Research Scientific Computing Center)

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Daniel Margala is a Scientific Data Architect in the Programming Environments and Models group at NERSC. Previously, he was a NERSC Exascale Science Application Program (NESAP) postdoctoral fellow at Lawrence Berkeley National Laboratory working with the Dark Energy Spectroscopic Instrument (DESI) data processing team, focusing on high performance computing with GPUs using Python. Daniel has a PhD in Physics from the University of California, Irvine and a BS in Physics from the University of California, Los Angeles.



Technical Program Committee

  • Eric Eilertson (Microsoft)

  • Bjoern Enders (National Energy Research Scientific Computing Center)

  • Fernanda Foertter (Voltron Data)

  • Khalid Hossain (Argonne National Labs)

  • Davin Potts (Appliomics)

  • Sreenivas Rangan Sukumar (Hewlett Packard Enterprise)