  BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//ISISLab - ECPv6.3.3//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:ISISLab
X-ORIGINAL-URL:https://www.isislab.it
X-WR-CALDESC:Eventi per ISISLab
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Rome
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20230326T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20231029T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Rome:20230616T160000
DTEND;TZID=Europe/Rome:20230616T170000
DTSTAMP:20260915T164142
CREATED:20230614T145706Z
LAST-MODIFIED:20230614T145707Z
UID:13292-1686931200-1686934800@www.isislab.it
SUMMARY:Seminario:"Towards a SYCL API for Approximate Computing" di Lorenzo Carpentieri
DESCRIPTION:Abstract:Approximate computing exploits the gap between the accuracy provided by a system and the accuracy required by an application. Many applications such as image processing and neural networks\, are tolerant of a certain amount of error\, and have the potential for significant improvements in terms of execution time and energy consumption if a small amount of error can be accepted. The most advanced software approximation techniques are mixed precision\, which uses a lower precision data representation for both integer and floating point variables; perforation\, which exploits data locality by skipping some iterations and assuming that nearby data have similar values; and relaxed synchronization.In this talk\, we present SYprox\, a SYCL-based API supporting a broad set of approximation techniques in modern C++.SYprox introduces a set of semantics that extend SYCL’s buffers and accessors to provide a high-level easy-to-use programming API.SYprox’s approximation framework seamlessly adds three additional stages to standard computational processing implementing perforation\, input reconstruction and output reconstruction. It supports data perforation and elision patterns for efficient approximation\, as well as signal reconstruction algorithms for error mitigation.Finally\, we present our preliminary results\, showing improvements in terms of performance and accuracy over to state-of-the-art approaches\, while maintaining at the same time a high-level programming approach.
URL:https://www.isislab.it/event/seminariotowards-a-sycl-api-for-approximate-computing-di-lorenzo-carpentieri/
ATTACH;FMTTYPE=image/png:https://www.isislab.it/wp-content/uploads/2023/06/SeminarioISISLab-16-06-2023.png
END:VEVENT
END:VCALENDAR