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Design and Implementation of a Convolutional Neural Network Accelerator ASIC

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Revision as of 19:16, 6 December 2014 by Lukasc (talk | contribs) (Detailed Task Description)
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Short Description

todo

Status: In Progress

David Gschwend, Christoph Mayer, Samuel Willi
Supervision: Lukas Cavigelli, Beat Muheim
Date: Fall Semester 2014 (sem14h17, sem14h18, sem14h19)

Prerequisites

Knowledge of Matlab
Interest in video processing and VLSI design
VLSI 1 and enrolment in VLSI 2 is required
At least one student has to test the chip as part of the VLSI 3 lecture, if the ASIC should be manufactured.


Character

10% Theory / Literature Research
60% VLSI Architecture, Implementation & Verification
30% VLSI back-end Design

Professor

Luca Benini

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Detailed Task Description

Goals

Explore various architectures to perform the 2D convolutions used in convolutional networks, considering the constraints of an ASIC design project.
Get to know the ASIC design flow from specification through architecture exploration to implementation, functional verification, back-end design and silicon testing.

Literature

Practical Details

Results

Links

The EDA wiki with lots of information on the ETHZ ASIC design flow (internal only) [[1]]


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