ECE 6790

Neuromorphic Computing Algorithm and Hardware Design

Course Description

Course information provided by the 2024-2025 Catalog. Courses of Study 2024-2025 is scheduled to publish mid-June.

Industry and academia have shown large interest in low-power hardware designs for neuromorphic computing (e.g. IBM TrueNorth, Intel Loihi) and deep learning algorithms for a wide range of image, speech, and biomedical applications. In this course, we will learn the underlying theory, basic algorithms, and efficient circuit/architecture design of neuromorphic computing.

Last 4 Terms Offered (None)

Outcomes

• Gain an understanding on neuromorphic computing and neural networks.
• Learn how to design energy-efficient hardware accelerators for neuromorphic computing and neural networks.
• Learn how to properly optimize the performance/power/area of neuromorphic hardware designs.

When Offered Spring.

Comments This course requires the student to be comfortable with either Matlab/Python languages for algorithm development, or RTL coding and computer-aided design (CAD) tool based digital circuit design.

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