Hardware Aware Acceleration For Deep Neural Networks

The result of this project (which will be demonstrated by a use case) can make health equipments to be used outside of hospitals. This is achieved by reducing the computation cost of running Deep Learning models by 3rd party tools and use our accelerator solution to run the size reduced and optimized model. This greatly helps to lower the barrier for using costly equipments and make them more affordable and reachable to people in need of these equipments.

Faculty Supervisor:

Jean-Pierre David;Yvon Savaria

Student:

Partner:

CMC Microsystems

Discipline:

Engineering

Sector:

Nanotechnology; Information and Communications Technology; Technology

University:

Polytechnique Montréal

Program:

Accelerate

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