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Proposer
Rob Stewart
Title
Comparing deep learning accelerator hardware
Goal
Measure the performance and usability of the TPU and Neural Compute Stick neural network accelerators
Description
"AI at the edge" allows autonomous devices and smart sensors to perform tasks such as object detection, classification, speech recognition and complex text processing tasks -- in real time and with very low power requirements. This project will compare the performance and usability of two neural network accelerator devices: The a Google TPU on a Coral.AI USB, and an Intel Neural Compute stick USB. If the student wishes to go further, a third comparator would be programming a neural network into hardware fabric with an FPGA.
Resources
Background
Url
Difficulty Level
Moderate
Ethical Approval
None
Number Of Students
1
Supervisor
Rob Stewart
Keywords
Degrees
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