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:20230831T095746Z
LOCATION:Flüela
DTSTART;TZID=Europe/Stockholm:20230627T120000
DTEND;TZID=Europe/Stockholm:20230627T123000
UID:submissions.pasc-conference.org_PASC23_sess157_msa227@linklings.com
SUMMARY:Experience From Ginkgo Porting to the SYCL Ecosystem
DESCRIPTION:Minisymposium\n\nYu-Hsiang Tsai, Terry Cojean, and Tobias Ribi
 zel (Karlsruhe Institute of Technology) and Hartwig Anzt (University of Te
 nnessee)\n\nIntel has introduced new GPU architectures into the High-Perfo
 rmance Computing markets and has chosen the SYCL ecosystem for its devices
 . Based on SYCL, they create several extensions to help the coding experie
 nce and improve usability. They also provide the tools to help port the co
 de from CUDA and measure the performance. Many applications rely on mathem
 atical libraries, so mathematical libraries need to be available on these 
 new devices. With the new Exascale machine Aurora using Intel GPU accelera
 tors, Ginkgo, which is a sparse linear algebra library, also faces the cha
 llenge of porting the code to the new Intel GPUs. Moreover, Ginkgo needs t
 o provide competitive performance and good portability. We show the ginkgo
  portability design such that we can add SYCL to our structure. We also sh
 are the challenges, concerns, and experiences from porting Ginkgo to SYCL.
  In the end, we summarize the supported functionality on different GPUs fr
 om different vendors.\n\nDomain: Computer Science, Machine Learning, and A
 pplied Mathematics 
\n\nSession Chair: Andrey Alekseenko (KTH Royal Instit
 ute of Technology, SciLifeLab)
END:VEVENT
END:VCALENDAR