BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/Chicago
X-LIC-LOCATION:America/Chicago
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
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TZNAME:CST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
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BEGIN:VEVENT
DTSTAMP:20230124T171520Z
LOCATION:C146
DTSTART;TZID=America/Chicago:20221114T133000
DTEND;TZID=America/Chicago:20221114T140000
UID:submissions.supercomputing.org_SC22_sess441_misc264@linklings.com
SUMMARY:PYNQ for HPC
DESCRIPTION:Workshop\n\nPYNQ for HPC\n\nSchelle\n\nPYNQ is an open-source 
 project from AMD that aims to help HPC applications achieve performance go
 als quicker by lowering software complexity. PYNQ with its runtime Python 
 APIs has its roots in Zynq SoCs (ARM processors plus programmable logic) a
 nd has expanded across both datacenter and RFSoC adaptive computing platfo
 rms. With that expansion, the PYNQ community now numbers in 1000s of activ
 e users across 10s of thousands shipped platforms. In this short talk, PYN
 Q will be revisited in the context of cloud and quantum computing as both 
 areas where adaptive computing is appearing in larger HPC frameworks. PYNQ
  has provided a scalable API for cloud deployments for some time and more 
 recently has been deployed within new quantum computing control systems. L
 astly, our newest project, PYNQ-Metadata, will be introduced as this work 
 gives users new levels of hardware introspection into existing (and new) h
 ardware designs, all from within Jupyter notebooks.\n\nSession Format: Rec
 orded\n\nRegistration Category: Workshop Reg Pass
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