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).
The AI Hardware research program is sub-divided into six major categories:
• Novel Architectures for Accelerating AI Computation
• Modeling and Simulation/Emulation of AI Hardware for Early System Exploration
• Power Efficient AI Hardware System Design
• 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.
Current28 Research Tasks23 Universities63 Students32 Faculty Researchers84 Liaison Personnel
This Year15 Task Starts61 Research Publications
Last Year3 Task Starts70 Research Publications
Since Inception30 Research Tasks26 Universities72 Students36 Faculty Researchers94 Liaison Personnel200 Research Publications