AI has with the help of HPC and access to large datasets evolved from expert systems and hand-tuned model building to using machine learning to auto-generated models, and generative AI technologies such as OpenAI’s ChatGPT and Google’s Bard. At the same time, these technologies are due to their extreme need for computing power now driving forces in hardware design. For instance, modern GPUs thus cater to not only graphics but AI algorithms by providing features such as an increasing number of lower-precision tensor cores. These developments will impact the evolution of HPC programming languages. In this talk, we will discuss some of our work related to utilizing these features, in the context of HPC, and how HPC techniques such as autotuning and GPU-assisted compression, can impact AI. This talk will also highlight some of the ongoing work my group is involved in at The Center for Geophysics Forecasting at the Norwegian University of Science and Technology, Norway.

Anne C. Elster is a Professor in Computer Science at NTNU (Norwegian Univ. of Science and Technology), a HPC Leader at the SFI Center for Geophysical Forecasting at NTNU, and a Senior Research Fellow / Visitor at The Oden Institute, Univ. of Texas at Austin. She currently also serves as a faculty representative on both the NTNU Board and NTNU´s IE College (Faculty) Board. She received her Master and PhD degrees in Electrical Engineering from Cornell University. Before joining NTNU in 2001 she worked at Schlumberger Austin Research as well as an Adjunct faculty member at UT Austin. Anne’s current research includes developing methods and tools for parallelizing, optimizing and auto-tuning codes targeting heterogeneous computing systems. Anne has advised over 100 master students as well as several PhDs and Postdocs in the area parallel and GPU computing,  She is also credited for her Linear Bit-reversal algorithm and served on the original MPI Standards Committee. She is an Associate Editor of IEEE CiSE and has served on numerous program committees, including the Sid Fernbach and Test-of-Time Awards committees. Anne received the IEEE Computer Society Distinguished Contributor Charter member award, and was a Distinguished speaker for IEEE CS (2019-2022).