BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:Europe/Stockholm
X-LIC-LOCATION:Europe/Stockholm
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20191206T142523Z
LOCATION:Panorama 3
DTSTART;TZID=Europe/Stockholm:20180627T134500
DTEND;TZID=Europe/Stockholm:20180627T151500
UID:isc_hpc_ISC High Performance 2018_sess167@linklings.com
SUMMARY:Data Centric Computing
DESCRIPTION:Focus Session\n\nData Centric Programming Abstractions Suitabl
 e from a Multiphysics Application Perspective\n\nDubey\n\nOrchestrating lo
 cality in data management has always been an important concern in high per
 formance computing (HPC) systems. In distributed memory architectures the 
 cost variation in data access had a few layers; cache hierarchy and DRAM a
 ccess versus off node. In forthcoming architectures there are ...\n\n-----
 ----------------\nSpatial Computing:  A Synthesis of Data-Centric Computin
 g and Extreme Hardware Specialization\n\nShalf\n\nThe conventional wisdom 
 of the last two decades is built on the premise that computing is the most
  expensive component of computing systems. However, we are entering an era
  where computing is cheap and ubiquitous, and where data movement dominate
 s energy costs and computational performance. These ch...\n\n-------------
 --------\nEmpirical Performance Modeling of HPC Workloads\n\nWolf\n\nMany 
 parallel applications suffer from latent performance limitations that may 
 prevent them from scaling to larger problem or machine sizes. Performance 
 models allow such issues to be predicted before they become relevant. A pe
 rformance model is a formula that expresses a performance metric of inter.
 ..\n\n---------------------\nParallel Program = Operator + Schedule + Para
 llel Data Structures\n\nPingali\n\nMulticore and manycore processors are n
 ow ubiquitous, but\nparallel programming remains as difficult as it was 30
 -40 \nyears ago. During this time, our community has explored\nmany promis
 ing approaches including functional and dataflow \nlanguages, logic progra
 mming, and automatic parallelization \nusing...\n\n\nPasses: Conference Pa
 ss
END:VEVENT
END:VCALENDAR