Dr. Anne C. Elster is a Professor of HPC in Computer Science at Norwegian University of Science and Technology (NTNU-Trondheim) and established the NTNU HPC-Lab, a well- respected research lab in heterogeneous computing that regularly receives international visitors. She is also a Visiting Scientist at the University of Texas at Austin.
Her current research interests are in high-performance parallel computing, focusing on developing good models and tools for heterogeneous computing and parallel software environments. Methods that include applying machine learning for code optimization and image processing, and developing parallel scientific codes that interact visually with the users by taking advantage of the powers in modern GPUs. Her novel fast linear bit-reversal algorithm is still noteworthy.
She is a Senior member of IEEE, Life member of AGU (American Geophysical Union, as well as a member of ACM, SIAM and Tekna. Funding partners/collaborators include EU H2020, The Research Council of Norway, AMD, ARM, NVIDIA, Statoil and Schlumberger.
Professor Elster is an IEEE Computer Society Distinguished Visitor Program Speaker (DVP 2019-2021)
AI for HPC: Experiences and Opportunities
Anne C. Elster
Director, Heterogeneous and Parallel Computing Lab and Professor of HPC
NTNU, Trondheim, Norway
Tuesday 18 February 2020 – 4:30 pm
This talk will be focused on how AI techniques can be used in the development of HPC environment and tools. As larger HPC systems become more and more heterogeneous by adding GPUs and other devices for performance and energy efficiency, they also become more complex to write and optimize the HPC applications for. For instance, both CPU and GPUs have several types of memories and caches that codes need to be optimized for.
We show how AI techniques can help us pick among tens of thousands of parameters one ends up needing to optimize for the best possible performance of some given complex applications. Ideas for future opportunities will also be discussed.