J. Austin Ellis is an HPC Research Scientist in the Analytics and AI Methods at Scale group within the Oak Ridge Leadership Computing Facility (OLCF). His research is primarily focused on high performance computing, machine learning, data analytics, scalable algorithms, and GPU computing. He received the SC21 Best Paper for “Revealing power, energy and thermal dynamics of a 200PF pre-exascale supercomputer”. He has a PhD in Applied Mathematics from North Carolina State University and was a postdoc in the Scalable Algorithms group at Sandia National Laboratories.
Extreme Scale Computing
Memory Systems
Parallel Programming Systems
State of the Practice
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