BEGIN:VCALENDAR
VERSION:2.0
PRODID:-// - ECPv6.15.16//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.neuropac.info
X-WR-CALDESC:Events for 
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20230312T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20231105T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240504T110000
DTEND;TZID=America/New_York:20240504T121500
DTSTAMP:20260501T140517
CREATED:20240428T081014Z
LAST-MODIFIED:20240428T081014Z
UID:10000285-1714820400-1714824900@www.neuropac.info
SUMMARY:Sangyeob Kim @ ONM - C-DNN and C-Transformer: Mixing ANNs and SNNs for the Best of Both Worlds
DESCRIPTION:From the Open Neuromorphic website. \nSangyeob and his team have developed a C-DNN processor that effectively processes object recognition workloads\, achieving 51.3% higher energy efficiency compared to the previous state-of-the-art processor. Subsequently\, they have applied C-DNN not only to image classification but also to other applications\, and have developed the C-Transformer\, which applies this technique to a Large Language Model (LLM). As a result\, they demonstrate that the energy consumed in LLM can be reduced by 30% to 72% using the C-DNN technique\, compared to the previous state-of-the-art processor. In this talk\, we will introduce the processor developed for C-DNN and C-Transformer\, and discuss how neuromorphic computing can be used in actual applications in the future. \n\n\nAbout the Speaker\nSangyeob Kim (Student Member\, IEEE) received the B.S.\, M.S. and Ph.D. degrees from the School of Electrical Engineering\, Korea Advanced Institute of Science and Technology (KAIST)\, Daejeon\, South Korea\, in 2018\, 2020 and 2023\, respectively. He is currently a Post-Doctoral Associate with the KAIST. His current research interests include energy-efficient system-on-chip design\, especially focused on deep neural network accelerators\, neuromorphic hardware\, and computing-in-memory accelerators.
URL:https://www.neuropac.info/event/sangyeob-kim-onm-c-dnn-and-c-transformer-mixing-anns-and-snns-for-the-best-of-both-worlds/
LOCATION:Online
CATEGORIES:Talk,Workshop
END:VEVENT
END:VCALENDAR