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A Network on Chip For Concurrent Transmission Of Accurate and Approximate Data

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A Network on Chip For Concurrent Transmission Of Accurate and Approximate Data

Fenster, Richard (2022) A Network on Chip For Concurrent Transmission Of Accurate and Approximate Data. Masters thesis, Concordia University.

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Abstract

As time passes by, there is an increase in desired computational ability. Networks on chip have been seen to facilitate communication between tightly coupled processing elements located on the same die. With said increasing computational demand, comes an increase in power consumption. As a result, approximate computing techniques are used in conjunction with networks on chip to reduce power consumption and latency. When implementing these approximate networks on chip, additional resources are required and may not have maximal use during runtime. In this work, we propose a network on chip design that maximizes resource usage irrespective of data type. This is achieved by using virtual channels that are configured depending on one of two operating modes. An accurate only mode allocates all bandwidth such that a single accurate link is active. The other operating mode is a mixed mode where the bandwidth is halved for approximate and accurate data types. If operating in this mixed Mode, a latency reduction of up to 4.2% from baseline can be realized when approximate traffic accounts for sixty-seven percent of all network traffic. The additional power requirement for this improvement is 22.6% when wide flits are used.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Fenster, Richard
Institution:Concordia University
Degree Name:M. Sc.
Program:Electrical and Computer Engineering
Date:July 2022
Thesis Supervisor(s):Le Beux, Sébastien
Keywords:noc, network-on-chip, approximate, approximate computing, computer, computer architecture
ID Code:990833
Deposited By: RICHARD FENSTER
Deposited On:27 Oct 2022 14:27
Last Modified:27 Oct 2022 14:27
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