DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee,Juhyoung | ko |
dc.contributor.author | Kim,Changhyeon | ko |
dc.contributor.author | Han, Donghyeon | ko |
dc.contributor.author | Kim, Sangyeob | ko |
dc.contributor.author | Kim, Sangjin | ko |
dc.contributor.author | Yoo, Hoijun | ko |
dc.date.accessioned | 2021-11-04T06:43:25Z | - |
dc.date.available | 2021-11-04T06:43:25Z | - |
dc.date.created | 2021-10-26 | - |
dc.date.issued | 2021-06 | - |
dc.identifier.citation | 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2021 | - |
dc.identifier.uri | http://hdl.handle.net/10203/288775 | - |
dc.description.abstract | Deep reinforcement learning (DRL) is widely used for autonomous systems including autonomous driving, robots, and drones. DRL training is essential for human-level control and adaptation to rapidly changing environments in mobile autonomous systems. However, acceleration of DRL training has three challenges: 1) large memory access, 2) various data patterns, 3) complex data dependency due to utilization of multiple DNNs. Two CMOS DRL accelerators have been proposed to support high speed, high energy-efficiency DRL training in mobile autonomous systems. One accelerator handles different data patterns with transposable PE architecture and reduces large feature map memory access with top-3 experience compression. The other accelerator supports group-sparse training for weight compression and integrates the on-line DRL task scheduler to support multi-DNNs operations. | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Energy-Efficient Deep Reinforcement Learning Accelerator Designs for Mobile Autonomous Systems | - |
dc.type | Conference | - |
dc.identifier.scopusid | 2-s2.0-85113346297 | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2021 | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Washington DC | - |
dc.identifier.doi | 10.1109/AICAS51828.2021.9458435 | - |
dc.contributor.localauthor | Yoo, Hoijun | - |
dc.contributor.nonIdAuthor | Lee,Juhyoung | - |
dc.contributor.nonIdAuthor | Kim,Changhyeon | - |
dc.contributor.nonIdAuthor | Han, Donghyeon | - |
dc.contributor.nonIdAuthor | Kim, Sangyeob | - |
dc.contributor.nonIdAuthor | Kim, Sangjin | - |
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