BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//EcoCloud - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://ecocloud.epfl.ch
X-WR-CALDESC:Events for EcoCloud
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Paris
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20220327T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20221030T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20230326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20231029T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20240331T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20241027T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20230601T120000
DTEND;TZID=Europe/Paris:20230601T140000
DTSTAMP:20260421T154810
CREATED:20230601T105107Z
LAST-MODIFIED:20230602T131702Z
UID:9258-1685620800-1685628000@ecocloud.epfl.ch
SUMMARY:Innovation for Energy-Efficient Deep Learning
DESCRIPTION:Dr. Gourav Datta of University of Southern California Viterbi\, Electrical Engineering\, gave a presentation on \nIn-Sensor & Neuromorphic Computing are all you need for Energy-Efficient Deep Learning\nThis talk will focus on two research thrusts in energy and latency-efficient edge intelligence. \nThe first thrust is inspired by the fact that spiking neural networks (SNNs) are a promising low-power alternative to compute and memory-expensive DNNs\, due to their high activation sparsity and use of accumulates (AC) instead of expensive multiply-and-accumulates (MAC). However\, most existing SNNs require multiple time steps for acceptable inference accuracy\, hindering real-time deployment and increasing energy consumption. This motivates the need for novel training frameworks to optimize source DL models\, their conversion to target SNNs\, and subsequent SNN fine-tuning\, which I will discuss in this talk. \nThe second thrust is inspired by the fact that modern image sensors generate huge amounts of high-resolution visual data that typically must be transferred to downstream CPUs/accelerators for computer vision (CV) processing. This data transfer requires significant bandwidth and can dominate the total energy consumption\, particularly when the CV processing is heavily optimized using SNNs. \nI will discuss a novel in-sensor computing paradigm based on CNNs\, coupled with intelligent algorithm-hardware co-design that can mitigate this concern. This paradigm is the first to demonstrate the feasibility of enabling all the computational aspects of modern CNN layers inside image sensors. Coupled with the optimized SNNs\, this paradigm can reduce the total system energy-delay product (EDP) of several on-device CV workloads by two orders of magnitude compared to existing approaches without significantly affecting the performance. \nGourav Datta\n\nDr. Gourav Datta (Graduate Student Member\, IEEE) received the B.Tech. Degree in instrumentation engineering with a minor in electronics and electrical communication engineering from the Indian Institute of Technology\, Kharagpur\, in 2018. He has recently completed a PhD at the University of Southern California\, USA. His research interests include energy and latency-efficient algorithm-hardware co-design for machine learning at the edge. He is a finalist of the Qualcomm Innovation fellowship 2022 (North America)\, a recipient of the IEEE Graduate Fellowship on Applied Superconductivity\, and a Ming Hsieh Ph.D. scholar. During his PhD tenure he has published 20 peer-reviewed papers in top-tier venues such as Scientific Reports\, Frontiers in Neuroscience\, TCAS-I\, DATE\, and WACV\, among others.
URL:https://ecocloud.epfl.ch/event/innovation-for-energy-efficient-deep-learning/
LOCATION:BC420 – Computing Building of EPFL\, EPFL\, Ecublens\, Switzerland
CATEGORIES:EcoCloud Official Event
ATTACH;FMTTYPE=image/png:https://ecocloud.epfl.ch/wp-content/uploads/2023/06/IMG_3218.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20230612T100000
DTEND;TZID=Europe/Paris:20230612T110000
DTSTAMP:20260421T154810
CREATED:20230605T080043Z
LAST-MODIFIED:20230605T081219Z
UID:9411-1686564000-1686567600@ecocloud.epfl.ch
SUMMARY:Computing Near Storage
DESCRIPTION:Prof. Paolo Ienne is delighted to invite Arvind of MIT to give the following talk: \nWe live in an age where an enormous amount of data is being collected constantly because of smart phones\, the ubiquitous presence of sensors and the wide-spread use of social media. Useful and cost-effective analysis of this data is the biggest economic driver for the IT industry. Such analyses are often done in data centers or on a cluster of machines because they involve applying sophisticated algorithms to terabyte-size graphs\, which are extremely irregular and sparse. We will show how low-power appliances for such analyses can be built using flash storage and hardware accelerators. Such appliances are likely to be 10X cheaper than 16-32 node server clusters and will come in the form of an SSD to be plugged into your laptop. \nArvind is the Head of the Computer Science Faculty and the Charles and Jennifer Johnson Professor of Computer Science and Engineering at MIT. Arvind’s group\, in collaboration with Motorola\, built the Monsoon dataflow machines and its associated software in the late eighties. In 2000\, Arvind started Sandburst which was sold to Broadcom in 2006. In 2003\, Arvind co-founded Bluespec Inc.\, an EDA company to produce a set of tools for high-level synthesis. Arvind’s current research focus is to enable the rapid development of embedded systems and designing complex digital chips with associated correctness proofs. Arvind is a Fellow of IEEE and ACM\, and a member of the National Academy of Engineering and the American Academy of Arts and Sciences.
URL:https://ecocloud.epfl.ch/event/computing-near-storage/
LOCATION:BC420 – Computing Building of EPFL\, EPFL\, Ecublens\, Switzerland
CATEGORIES:EcoCloud Connected Event
ATTACH;FMTTYPE=image/jpeg:https://ecocloud.epfl.ch/wp-content/uploads/2023/06/arvind-e1685952141331.jpeg
END:VEVENT
END:VCALENDAR