BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Events - ECPv6.17.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://events.ucsc.edu
X-WR-CALDESC:Events for Events
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20250309T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20251102T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20260308T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20261101T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20270314T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20271107T090000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260305T130000
DTEND;TZID=America/Los_Angeles:20260305T150000
DTSTAMP:20260217T182432Z
CREATED:20260217T182432Z
LAST-MODIFIED:20260217T182432Z
UID:10009238-1772715600-1772722800@events.ucsc.edu
SUMMARY:Xu\, Y. (CSE) - Right Place\, Right Time: Accelerating Edge Computation on Modern Heterogeneous SoCs
DESCRIPTION:Modern edge computing increasingly relies on heterogeneous System-on-Chip (SoC) architectures. These chips tightly integrate general-purpose CPUs with various specialized accelerators\, including GPUs\, FPGAs\, and AI accelerators\, all under a shared memory architecture. Although these shared-memory SoCs enable more efficient communication and data sharing between different processing units\, they are notoriously difficult to program and tune due to architectural diversity across vendors and asymmetric compute capabilities within each SoC. \nThis dissertation introduces Redwood and BetterTogether\, two frameworks that rethink CPU-accelerator collaboration on heterogeneous SoCs. Redwood targets a class of algorithms termed traverse–compute\, that combine irregular tree traversals with dense leaf-level computation\, e.g.\, Nearest-Neighbor Search and Barnes–Hut algorithm. \nIt addresses the efficient mapping of these algorithms onto heterogeneous systems by exploiting the architectural strengths of CPUs\, GPUs\, and FPGAs. BetterTogether extends this methodology to a different class of edge workloads\, specifically multi-stage pipelines and neural networks commonly used in computer vision tasks. Furthermore\, it introduces interference-aware analysis and scheduling techniques tailored for mobile SoCs. Finally\, to broaden the scope of heterogeneous acceleration\, we evaluated emerging domain-specific accelerators. We provide a preliminary analysis of Tensor Processing Units and Tensor Cores within the context of modern programming abstractions. \nEvent Host: Yanwen Xu\, Ph.D. Candidate\, Computer Science and Engineering \nAdvisor: Tyler Sorensen \nZoom- https://ucsc.zoom.us/j/5354629158?pwd=0CVhbwLuXDMX5fAGZd63tcfNqDWp0t.1 \nPasscode- 114514
URL:https://events.ucsc.edu/event/xu-y-cse-right-place-right-time-accelerating-edge-computation-on-modern-heterogeneous-socs/
LOCATION:Engineering 2\, Engineering 2 1156 High Street\, Santa Cruz\, CA\, 95064
CATEGORIES:Ph.D. Presentations
ATTACH;FMTTYPE=image/jpeg:https://events.ucsc.edu/wp-content/uploads/2026/02/ph.d.-presentation-graphic-option2.jpg
GEO:37.0009723;-122.0632371
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Engineering 2 Engineering 2 1156 High Street Santa Cruz CA 95064;X-APPLE-RADIUS=500;X-TITLE=Engineering 2 1156 High Street:geo:-122.0632371,37.0009723
END:VEVENT
END:VCALENDAR