Overview

This research program highlights the importance of hardware in pushing the frontiers of artificial intelligence across a broad spectrum of applications from the edge to the cloud. The program has roots in two previous efforts: System Level Design (SLD) and Efficiency and Performance for Connectivity Constrained Computing (EP3C).

Research Focus

The AI Hardware research program is comprised of five major categories:

• Architectures for Power Efficient AI Acceleration

• Modeling, Analysis, and Simulation/Emulation of AI Hardware for Early System Exploration

• HW/SW Co-design of AI Compute Systems

• Fairness, Robustness, Privacy, and Explainability of Models and Algorithms for AI Hardware

• Interplay of AI and System Architecture/Microarchitecture Design

In each category, there may be research covering large systems to small (datacenter and the edge/end node) as well as a broad range of applications, including high-performance processors for data centers, automotive, industrial, mobile computing and communication, and healthcare.