Abstract: The interest in AI has exploded over the past few years and the use of AI in applications is poised to increase dramatically for many years. However, AI already demands very large amounts of compute, memory, and bandwidth; how to deliver these levels is becoming a pervasive challenge in computing system design. This explosive growth has provided a huge impetus to accelerate AI workloads by employing a mix of diverse components, including CPUs, GPUs, specialized accelerators, and memories. The requirement of high bandwidth interconnectivity between different components has been a major driver for heterogeneous integration. In addition, the diminishing node-to-node returns from scaling have propelled heterogeneous integration to the forefront of technology focus. This raises several questions. How does the current state-of-the-art in heterogeneous integration meet the ever-growing demands of AI? What novel integration schemes are needed to deliver continued gains in system performance? How can emerging memories and analog technologies, which show promise for accelerating AI workloads, be effectively integrated with conventional technologies? Finally, what is the path forward to deploy heterogeneous integration as a pervasive technology in this arena? We will examine both the architecture requirements for AI as well as the heterogeneous integration methods needed to enable an upward trajectory for system performance.
Arvind Kumar is a manager of AI Hardware Technologies at the IBM T.J. Watson Research Center. His research focuses on the requirements of AI systems and the heterogeneous integration innovations to accelerate them. He has presented a number of invited talks and been a panelist in this area. In addition, he has chaired and organized a number of future computing events, including the 2017 IEEE Rebooting Computing Conference. Prior to concentrating on AI, he worked extensively on device design, characterization, and simulation for several IBM SOI technologies. Dr. Kumar holds S.B., S.M., and Ph.D. degrees in electrical engineering and computer science, all from the Massachusetts Institute of Technology.
Mukta Ghate Farooq is a metallurgist and materials scientist with expertise in heterogeneous integration, CMOS BEOL, lead-free alloys, and chip-package interaction. She is currently the 3D Integration Leader for the Artificial Intelligence Center (AIC) at IBM Research. Mukta was the IBM technology leader who delivered the semiconductor industry’s first high-volume 3D logic wafer in 2013. Mukta is an IEEE Fellow, an IEEE EDS Distinguished Lecturer, and a Distinguished Alumna of IIT-Bombay. She has 216 granted US patents and is an IBM Lifetime Master Inventor and an IBM Academy of Technology member. She received her B.S. from the Indian Institute of Technology, Bombay, M.S. from Northwestern University, Evanston, IL, and Ph.D. from Rensselaer Polytechnic Institute, Troy, NY.