Plenary Talk 2 : Parallel Computing and AI: Impact and Opportunities
Anne Cathrine Elster · 2021
Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. Parallel Computing has for many years now been needed in order to be able to get the desired performance for computational intensive tasks, ranging from image processing to astro-physics and weather simulations. Traditionally, the HPC field drove companies like Cray, IBM and others to develop processors for supercomputing. However, the market forces in other fields have-since the proliferation of COTS (commercial off-the shelf) processors, including GPUs for gaming and now more recently AI- driven the innovation in processor design. This means that algorithms, tools and applications now should adapt and take advantage of tensor processor, Machine Learning techniques, and other related technology, rather than expecting that old computational models will hold true. In this talk, we will discuss these issues, including how this is also an opportunity to help develop better graph algorithms for AI, and apply some of the techniques from AI to HPC challenges.