Multi-Layer Perceptron Hardware Accelerator on RISC-V Processor

Nazim Altar Koca, Berkay Yildiz, Yusuf Caner Demirkol, Berna Örs

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The need for domain-specific hardware architectures of neural network models is increasing with the rapid development of autonomous cars, robotics and IOT. For these data-driven systems, new fast and efficient hardware methodologies are introduced recently. In this study, a comparison between general purpose RISC-V processor and customized version of it will be presented. Customized version consists of local memory structure, special float computing unit and an interface to communicate with core. It is aimed to show by using the strong sides of these two hardware more efficient and fast architectures can be achieved.

Original languageEnglish
Title of host publication2021 13th International Conference on Electrical and Electronics Engineering, ELECO 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages465-469
Number of pages5
ISBN (Electronic)9786050114379
DOIs
Publication statusPublished - 2021
Event13th International Conference on Electrical and Electronics Engineering, ELECO 2021 - Virtual, Bursa, Turkey
Duration: 25 Nov 202127 Nov 2021

Publication series

Name2021 13th International Conference on Electrical and Electronics Engineering, ELECO 2021

Conference

Conference13th International Conference on Electrical and Electronics Engineering, ELECO 2021
Country/TerritoryTurkey
CityVirtual, Bursa
Period25/11/2127/11/21

Bibliographical note

Publisher Copyright:
© 2021 Chamber of Turkish Electrical Engineers.

Funding

This study is supported by TUBITAK within the scope of 2209-A projects.

FundersFunder number
TUBITAK

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