Efficient Scaling of Large Language Models with Mixture of Experts and 3D Analog In-Memory Computing
- 2025
- Nat. Comput. Sci.
Geoffrey W. Burr received his Ph.D. in Electrical Engineering from the California Institute of Technology in 1996. Since that time, Dr. Burr has worked at IBM Research--Almaden in San Jose, California, where he is currently a Distinguished Research Scientist. He has worked in a number of diverse areas, including holographic data storage, photon echoes, computational electromagnetics, nanophotonics, computational lithography, phase-change memory, storage class memory, and novel access devices based on Mixed-Ionic-Electronic-Conduction (MIEC) materials. Dr. Burr's current research interests involve AI/ML acceleration using non-volatile memory. Geoff is an IEEE Fellow (2020), and is also a member of MRS, SPIE, OSA, Tau Beta Pi, Eta Kappa Nu, and the Institute of Physics (IOP).
Making Deep Neural Network systems more capable and energy-efficient.