UNPU: A 50.6TOPS/W Energy-Efficient Unified Deep Neural-Network Accelerator with 1-to-16b Fully Variable Bit Precision UNPU: A 50.6TOPS/W Energy-Efficient Unified Deep Neural-Network Accelerator with 1-to-16b Fully Variable Bit Precision
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Lee, Jinmook | ko |
| dc.contributor.author | Kim, Changhyeon | ko |
| dc.contributor.author | Kang, Sanghoon | ko |
| dc.contributor.author | Shin, Dongjoo | ko |
| dc.contributor.author | Kim, Sangyeob | ko |
| dc.contributor.author | Yoo, Hoi-Jun | ko |
| dc.date.accessioned | 2019-04-15T14:37:33Z | - |
| dc.date.available | 2019-04-15T14:37:33Z | - |
| dc.date.created | 2018-12-19 | - |
| dc.date.issued | 2018-02 | - |
| dc.identifier.citation | IEEE Internatioal Solid-State Circuits Conference | - |
| dc.identifier.uri | http://hdl.handle.net/10203/254232 | - |
| dc.language | English | - |
| dc.publisher | IEEE Internatioal Solid-State Circuits Conference | - |
| dc.title | UNPU: A 50.6TOPS/W Energy-Efficient Unified Deep Neural-Network Accelerator with 1-to-16b Fully Variable Bit Precision UNPU: A 50.6TOPS/W Energy-Efficient Unified Deep Neural-Network Accelerator with 1-to-16b Fully Variable Bit Precision | - |
| dc.type | Conference | - |
| dc.type.rims | CONF | - |
| dc.citation.publicationname | IEEE Internatioal Solid-State Circuits Conference | - |
| dc.identifier.conferencecountry | US | - |
| dc.identifier.conferencelocation | San Francisco, California | - |
| dc.contributor.localauthor | Yoo, Hoi-Jun | - |
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