Seminar: ceClub: The Technion Computer Engineering Club
Towards Energy-Efficient AI Hardware: Mixed-Signal In-Memory Computing and Ultra-Dense Die-to-Die Links
Lecturer:
Dr. Nicolás Wainstein
Research Areas:
| The rapid advancement of artificial intelligence (AI) is pushing the limits of conventional digital computing architectures. Key performance bottlenecks–computational efficiency, memory bandwidth, and interconnect performance–are becoming increasingly critical, especially for edge AI applications that demand low latency and ultra-low power consumption. In this talk, I will present my recent research aimed at overcoming these challenges through a multidisciplinary approach focusing on three main pillars: 1) analog/mixed-signal circuits, 2) in-memory computing (IMC), and 3) high-speed die-to-die (D2D) links. I will show how time-domain IMC using nonvolatile emerging memory technologies, such as ferroelectric FETs, can improve the energy-efficiency of AI hardware, as demonstrated by a prototype in 28 nm CMOS. I will also present a mixed-mode fast-locking delay-locked loop for latency-critical parallel links (such as D2D), implemented in a 3 nm FinFET CMOS process. These works span CMOS and emerging device technologies, combining insights from device physics, circuit design, and system architecture to enable the next generation of high-performance, energy-efficient AI hardware. |
| Nicolas Wainstein is a Research Fellow at the ECE faculty at the Technion. From 2021 to 2024, he was a Senior Analog/Mixed-Signal Design Engineer and Technical Lead at Intel, Israel, working on high-speed parallel wireline links, such as DDR and die-to-die (D2D) communication. He earned his PhD in Electrical Engineering from the Technion, supervised by Prof. Shahar Kvatinsky and Prof. Eilam Yalon. Nicolás was the recipient of several awards, including the Hershel Rich Innovation Award, the IEEE Electron Devices Society Ph.D. Student Fellowship (Europe and Middle East region), the Yablonovitch Research Prize, the 1st place in the RBNI Prize for Excellence in Nanoscience and Nanotechnology, and the Jury Award for Outstanding Students.
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