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BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Penn Engineering Events - ECPv6.18.0//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Penn Engineering Events X-ORIGINAL-URL:https://seasevents.nmsdev7.com X-WR-CALDESC:Events for Penn Engineering Events 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:20190310T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20191103T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20200308T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20201101T060000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:EDT DTSTART:20210314T070000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:EST DTSTART:20211107T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/New_York:20200305T150000 DTEND;TZID=America/New_York:20200305T160000 DTSTAMP:20200220T190835Z CREATED:20200220T190835Z LAST-MODIFIED:20200220T190835Z UID:2705-1583420400-1583424000@seasevents.nmsdev7.com SUMMARY:CIS Seminar: "Building Data-Driven Computers: Reimagining Systems to Reduce the High Costs of Large-Scale Data Processing" DESCRIPTION:Abstract: \nA wide range of application domains are emerging as computing platforms of all types become more ubiquitous in society.  Many of these applications are data centric\, and spend a significant fraction of their time on accessing and processing very large datasets.  Examples of these applications include graph frameworks\, precision medicine\, computer vision\, deep learning\, and mobile device workloads.  Unfortunately\, the hardware platforms executing these applications remain compute centric\, and are rooted in decades-old design principles for computer architectures.  Running modern data-centric applications on compute-centric platforms results in high inefficiencies\, with significant energy waste and program stalls.  Data-centric platforms can eliminate these inefficiencies\, but require the community to fundamentally rethink our approach to computer design. \nIn this talk\, I will present a holistic approach for developing practical data-centric architectures and systems.  I will begin by using experimental characterization to identify the sources of poor energy efficiency and poor performance in existing architectures as they run modern applications\, focusing on the impact of current memory systems.  Next\, I will show how near-data computing can mitigate these inefficiencies.  Recent breakthroughs in memory technologies have made near-data computing a practical and viable alternative to compute-centric platforms\, but several system-level challenges remain.  I will present a few of my representative efforts towards developing practical programmer and architectural support for near-data computing\, including efficient data coherence and domain-specific system design.  I will conclude the talk with my future research vision\, on developing and building full-system data-driven architectures that are optimized for energy efficiency.  This includes microarchitectural and circuit-level support for in-memory computing using emerging non-volatile memories\, cooperative hardware–software memory management\, and compiler and data optimizations that allow programmers to effortlessly target these data-driven architectures. \n  URL:https://seasevents.nmsdev7.com/event/cis-seminar-building-data-driven-computers-reimagining-systems-to-reduce-the-high-costs-of-large-scale-data-processing/ LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States CATEGORIES:Colloquium ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu END:VEVENT END:VCALENDAR