Dr Beau Johnston

Computer Scientist, Future Technologies Group, ORNL
Visiting Fellow, Research School of Computer Science, ANU
PhD, Australian National University

My capacity is as a Computer Scientist at the Future Technologies Group at Oak Ridge National Laboratory, Tennessee, but having received my PhD at the ANU and still being physically based in Canberra, I am well placed to continue my research which originates from my time at the ANU and targeted for current Oak Ridge objectives. This presents the opportunity of having student projects that are directly focused on current HPC research problems which should strengthen a partnership between the ANU and Oak Ridge.

My thesis was in High-Performance Computing (HPC) and Programming Languages. More specifically, I investigated the patterns/characteristics of scientific workloads and their impact on performance over a range of accelerator hardware.

I developed a tool to perform Architecture-Independent Workload Characterization (AIWC -- pronounced | \ 'air-wik) -- which extracts features critical to performance. I then built models using machine learning to perform accurate predictions of AIWC features to their performance on different accelerators.

Scientific discovery is becoming increasingly dependant on supercomputers, which require increasingly large and more complex simulations. Accelerators are critical for the next generation of these supercomputers -- offering energy-efficiency where it is sorely needed. My work is applicable to workload scheduling (to better use these massive machines) and evaluating prospective hardware before manufacture (to allow the most appropriate supercomputers to be built based on the envisaged scientific workloads).

AIWC is also useful to guide developers to potential software optimizations -- and is my active area of research. On a day to day basis, my work focuses on enabling the full suite of programming languages used in HPC (OpenMP, OpenACC, OpenCL and CUDA) to use AIWC and the predictive framework.

My mission is to develop tools which allow the better use of computational resources for scientific discovery -- facilitating computer scientists and computational/data scientists to make more discoveries, faster. 

To this end, my current primary research topic is on 'Workload Characterization for Heterogeneous Computing'.
I am broadly interested in Algorithms, Programming Languages and Parallel Computing.
I am also a Researcher at the University of New England where I work in data science, computational modeling and computer vision applied to ecology. I also get to exercise these interests collaborating on developing tools for neuroscience with The Dehorter - Neuronal Development Group.


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