Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration
Name
genc2021-dac.pdf
Description
Accepted version
Size
1.23 MB
Format
Adobe PDF
Checksum (MD5)
eda593751ee21f583df5e6aa611bb0dc
Author(s)
Genc, Hasan
Kim, Seah
Amid, Alon
Haj-Ali, Ameer
Iyer, Vighnesh
Prakash, Pranav
Zhao, Jerry
Grubb, Daniel
Liew, Harrison
Mao, Howard
Date Issued
2021
Journal
2021 58th ACM/IEEE Design Automation Conference (DAC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Genc, Hasan, Kim, Seah, Amid, Alon, Haj-Ali, Ameer, Iyer, Vighnesh et al. 2021. "Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration." 2021 58th ACM/IEEE Design Automation Conference (DAC).
Version
Author's final manuscript
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/DAC18074.2021.9586216
