Domain-Specific Analog Accelerators for Artificial Intelligent Algorithms Implementation

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Creator: 

Liu, Guoxin

Date: 

2022

Abstract: 

This thesis discusses some circuit designs for AI algorithm acceleration. Instead of using digital computing components for algorithm implementations, this thesis describes new ideas to design and implement algorithms directly at the circuit-level. The first large section is about feedforward algorithm implementations that include using 1*4 analog multiply-accumulation arrays for DSP algorithm implementation and 2*3*3 analog multiply-accumulation matrices for computer vision algorithm and artificial intelligent algorithm implementations. The second large section concerns backward algorithm implementations that include using programmable resistor-based feedback loop, 'Add-division circuit' for convolutional kernel training algorithm implementation, and 'Random matrix generator' for solving Diophantine equations of neural networks.

Subject: 

Engineering - Electronics and Electrical
System Science

Language: 

English

Publisher: 

Carleton University

Thesis Degree Name: 

Master of Applied Science: 
M.App.Sc.

Thesis Degree Level: 

Master's

Thesis Degree Discipline: 

Engineering, Electrical and Computer

Parent Collection: 

Theses and Dissertations

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