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.
AIHW Metrics
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Current
29 Projects24 Universities94 Research Scholars40 Faculty Researchers110 Liaisons -
This Year
13 Project Starts355 Research Data1 Patent Applications -
Last Year
16 Project Starts384 Research Data1 Patent Applications -
Since Inception
81 Projects47 Universities259 Research Scholars92 Faculty Researchers278 Liaisons1,634 Research Data14 Patent Applications1 Patents Granted
Pillar Science Links
SRC.org Links