DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shin, Hyein | ko |
dc.contributor.author | Kang, Myeonggu | ko |
dc.contributor.author | Kim, Lee-Sup | ko |
dc.date.accessioned | 2020-11-30T09:50:17Z | - |
dc.date.available | 2020-11-30T09:50:17Z | - |
dc.date.created | 2020-11-30 | - |
dc.date.created | 2020-11-30 | - |
dc.date.issued | 2020-11 | - |
dc.identifier.citation | 39th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2020 | - |
dc.identifier.issn | 1933-7760 | - |
dc.identifier.uri | http://hdl.handle.net/10203/277768 | - |
dc.description.abstract | Resistive RAM (ReRAM) is widely regarded as a promising platform for deep neural network (DNN) acceleration. However, the ReRAM device suffers from severe thermal problems that degrade the lifetime and inference accuracy of the ReRAM-based DNN accelerator. To address the issues, we propose a thermal-aware optimization framework for accelerating DNN on ReRAM (TOPAR). TOPAR includes 3-stage offline thermal optimization and online thermal-aware error compensation. Offline thermal optimization consists of thermal-aware weight decomposition, thermal-aware column reordering, and fine-grained weight adjustment to reduce the temperature of the ReRAM-based DNN accelerator. For online thermal-aware error compensation, we compensate conductance change according to the temperature variation. With TOPAR, the endurance degradation due to temperature rise improves up to 2.39×, and inference accuracy is preserved without harming the performance of the ReRAM-based DNN accelerator. | - |
dc.language | English | - |
dc.publisher | IEEE/ACM | - |
dc.title | A Thermal-aware Optimization Framework for ReRAM-based Deep Neural Network Acceleration | - |
dc.type | Conference | - |
dc.identifier.wosid | 000671087100026 | - |
dc.identifier.scopusid | 2-s2.0-85097939639 | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | 39th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2020 | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Virtual | - |
dc.identifier.doi | 10.1145/3400302.3415665 | - |
dc.contributor.localauthor | Kim, Lee-Sup | - |
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