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Ph.D. Dissertation Defense - Aishwarya Natarajan
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Title: Analog and Neuromorphic computing with a framework on a reconfigurable platform
Committee:
Dr. Jennifer Hasler, ECE, Chair, Advisor
Dr. Omer Inan, ECE
Dr. Azad Naeemi, ECE
Dr. Aaron Lanterman, ECE
Dr. Steven Baer, ASU
Abstract: The objective of the proposed research is to demonstrate an energy-efficient computing on a configurable platform, the FPAA, by leveraging the analog strengths, along with the development of a framework, to enable real-time systems on hardware. By taking inspi- ration from biology, fundamental blocks of neurons and synapses are built, understanding the computational advantages of such neural structures. To enable this computation and scale up from these modules, it is significantly important to have an infrastructure as well that adapts by taking care of the non-ideal effects like mismatches and variations, which commonly plague analog implementations. The programmability, through the presence of floating gates, helps to reduce these variations, thereby ultimately paving the path to take physical approaches to build larger systems in a holistic manner.
Status
- Workflow Status:Published
- Created By:Daniela Staiculescu
- Created:12/01/2021
- Modified By:Daniela Staiculescu
- Modified:12/01/2021
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