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 language | English |
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Title of host publication | 2021 13th International Conference on Electrical and Electronics Engineering, ELECO 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 465-469 |
Number of pages | 5 |
ISBN (Electronic) | 9786050114379 |
DOIs | |
Publication status | Published - 2021 |
Event | 13th International Conference on Electrical and Electronics Engineering, ELECO 2021 - Virtual, Bursa, Turkey Duration: 25 Nov 2021 → 27 Nov 2021 |
Publication series
Name | 2021 13th International Conference on Electrical and Electronics Engineering, ELECO 2021 |
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Conference
Conference | 13th International Conference on Electrical and Electronics Engineering, ELECO 2021 |
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Country/Territory | Turkey |
City | Virtual, Bursa |
Period | 25/11/21 → 27/11/21 |
Bibliographical note
Publisher Copyright:© 2021 Chamber of Turkish Electrical Engineers.
Funding
This study is supported by TUBITAK within the scope of 2209-A projects.
Funders | Funder number |
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TUBITAK |