Research

Three-Dimensional (3D) Integrated Circuits

With Moore's Law reaching limitations in transistor scaling, one solution is to expand vertically by stacking multiple silicon layers interconnected by vias. Our focus is on designing 3D architectures, such as memory stacks (SRAM, eDRAM, ReRAM, etc.), and converting conventional 2D architectures to 3D.

Neuromorphic Computing

Inspired by the human brain, we design neuromorphic chips featuring physical artificial neurons made of silicon. These chips perform computations that mimic biological brain functions. Our approach combines digital methods with 3D Integrated Circuits and Network-on-Chip (NoC) structures, developed in both hardware (Verilog HDL) and software (Python) models.

Carbon-efficient & Sustainable Computing

Computers, data centers, and devices use a lot of energy, often from fossil fuels, which release carbon and cause climate change. By making computing carbon neutral/efficient, we can protect the environment by cutting carbon emissions. Our carbon-efficient computing aims to designing and operating computing systems to minimize their carbon footprint, aiming for greater energy efficiency and reduced environmental impact.

Fault-Tolerant Computing

Fault-tolerant computing improves system reliability by enabling hardware and software systems to continue operating correctly even in the presence of faults such as noise, timing violations, or transient errors. Our research focuses on analyzing the sources and characteristics of faults in modern computing platforms and developing efficient fault-detection and fault-mitigation techniques. The goal is to ensure reliable and resilient operation while maintaining high performance and energy efficiency.