BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Chicago BEGIN:DAYLIGHT DTSTART:20250309T030000 TZOFFSETFROM:-0600 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:CDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20251102T010000 TZOFFSETFROM:-0500 TZOFFSETTO:-0600 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:CST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20251010T130605Z UID:87665325-FB42-434A-8B77-F40E8B7429AD DTSTART;TZID=America/Chicago:20251007T090000 DTEND;TZID=America/Chicago:20251007T100000 DESCRIPTION:In this talk\, the speaker will first discuss how new mapping s olutions\, i.e.\, composing heterogeneous accelerators within a system-on- chip with both FPGAs and AI tensor cores\, achieve orders of magnitude ene rgy efficiency gains when compared to monolithic accelerator mapping desig ns for deep learning applications. Then\, the speaker will apply such nove l mapping solutions to show how design space explorations are performed to achieve low-latency AI inference. The speaker will further discuss how we applied these techniques to different application domains\, including aut onomous vehicles\, additive manufacturing\, etc.\n\nSpeaker(s): Dr. Peipei Zhou\, \n\nAgenda: \nIntroduction\n\nTalk/Presentation\n\nQ&A\n\nVirtual: https://events.vtools.ieee.org/m/499929 LOCATION:Virtual: https://events.vtools.ieee.org/m/499929 ORGANIZER:ashok.polavarapu1@louisiana.edu SEQUENCE:38 SUMMARY: IEEE Lafayette Section Young Professionals Affinity Group - IEEE D ay Tech Chat URL;VALUE=URI:https://events.vtools.ieee.org/m/499929 X-ALT-DESC:Description: <br /><p>In this talk\, the speaker will first disc uss how new mapping solutions\, i.e.\, composing heterogeneous accelerator s within a system-on-chip with both FPGAs and AI tensor cores\, achieve or ders of magnitude energy efficiency gains when compared to monolithic acce lerator mapping designs for deep learning applications. Then\, the speaker will apply such novel mapping solutions to show how design space explorat ions are performed to achieve low-latency AI inference. The speaker will f urther discuss how we applied these techniques to different application do mains\, including autonomous vehicles\, additive manufacturing\, etc.</p>< br /><br />Agenda: <br /><p>Introduction</p>\n<p>Talk/Presentation</p>\n<p >Q&amp\;A</p> END:VEVENT END:VCALENDAR