In the advent of the data-centric AI era and the imminent end of CMOS scaling laws, the time is ripe to adopt computing units based on non-von Neumann computing architectures. A first step in this direction could be in-memory computing, where certain computational tasks are performed in place in a specialized memory unit called computational memory. Resistive memory devices, where information is represented in terms of atomic arrangements within tiny volumes of material, are poised to play a key role as elements of such computational memory units. I will present a few examples of how the physical attributes and dynamics of these devices can be exploited to achieve in-place computation. We expect that this co-existence of computation and storage at the nanometer scale could enable ultra-dense, low-power, and massively-parallel computing systems.
The Stanford EE Computer Systems Colloquium (EE380) meets on Wednesdays 4:30-5:45 throughout the academic year. Talks are given before a live audience in Room B03 in the basement of the Gates Computer Science Building on the Stanford Campus. The live talks (and the videos hosted at Stanford and on YouTube) are open to the public.
Abu Sebastian is a Research Staff Member and Master Inventor at IBM Research - Zürich. He was a contributor to several key projects in the field of storage and memory technologies. Most recently, he has been pursuing research in the area of non-von Neumann computing with the intent of connecting the technological elements with applications such as machine learning. In 2015, he was awarded a European Research Council (ERC) consolidator grant for this work.