DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jung, Youngbeom | ko |
dc.contributor.author | Choi, Yeongjae | ko |
dc.contributor.author | Sim, Jaehyeong | ko |
dc.contributor.author | Kim, Lee-Sup | ko |
dc.date.accessioned | 2019-11-21T08:20:25Z | - |
dc.date.available | 2019-11-21T08:20:25Z | - |
dc.date.created | 2019-08-19 | - |
dc.date.created | 2019-08-19 | - |
dc.date.issued | 2019-11-04 | - |
dc.identifier.citation | 38th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2019 | - |
dc.identifier.issn | 1933-7760 | - |
dc.identifier.uri | http://hdl.handle.net/10203/268512 | - |
dc.description.abstract | CNN-based Super-Resolution (SR), the most representative of low-level vision task, is a promising solution to improve users’ QoS on IoT devices that suffer from limited network bandwidth and storage capacity by effectively enhancing image/video resolution. Although prior accelerators to embed CNN show tremendous performance and energy efficiency, they are not suitable for SR tasks regarding off-chip memory accesses. In this work, we present eSRCNN, a framework that enables performing energy-efficient SR tasks on diverse embedded CNN accelerators by decreasing off-chip memory accesses. To reduce off-chip memory accesses, our framework consists of three steps: a network reformation using a cross-layer weight scaling, a precision minimization with priority-based quantization, and an activation map compression exploiting a data locality. As a result, the energy consumption of off-chip memory accesses is reduced up to 71.89% with less than 3.52% area overhead. | - |
dc.language | English | - |
dc.publisher | IEEE/ACM | - |
dc.title | eSRCNN: A Framework for Optimizing Super-Resolution Tasks on Diverse Embedded CNN Accelerators | - |
dc.type | Conference | - |
dc.identifier.wosid | 000524676400045 | - |
dc.identifier.scopusid | 2-s2.0-85077790066 | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | 38th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2019 | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | The Westin Westminster | - |
dc.identifier.doi | 10.1109/ICCAD45719.2019.8942086 | - |
dc.contributor.localauthor | Kim, Lee-Sup | - |
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