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:20191206T142453Z
LOCATION:Substanz 1\, 2
DTSTART;TZID=Europe/Stockholm:20180626T083000
DTEND;TZID=Europe/Stockholm:20180626T100000
UID:isc_hpc_ISC High Performance 2018_sess113_post117@linklings.com
SUMMARY:(RP04) GPU-based Parallel PO-SWE Algorithm for the Design of Large
 -sized Dual-Reflector Antennas
DESCRIPTION:Research Poster\n\n(RP04) GPU-based Parallel PO-SWE Algorithm 
 for the Design of Large-sized Dual-Reflector Antennas\n\nMatsuo, Gocho, Oz
 aki, Katase, Ado\n\nLarge-sized dual-reflector antennas are analyzed to ev
 aluate their performance through long-time simulation using some accurate 
 EM (electromagnetic) methods based on PO (physical optics). To reduce the 
 time/term for the simulation/design, we focused on the parallelization of 
 the fast and accurate hybrid PO-SWE (spherical waveguide expansion) method
 , which relaxes the computational complexity while maintaining accuracy on
  a single-node CPU/GPU-embedded system, where each GPU has several thousan
 d cores on a discrete small-sized memory. To perform the hybrid PO-SWE on 
 such a small-sized memory, we developed the CPUs-GPUs distributed algorith
 m, through which the CPUs iteratively compute the new small-sized regions 
 of the main-reflector and the SWE coefficients of the sub-reflector behind
  the GPUs-based PO-SWE computation for the pre-computed them. We found tha
 t our implementation using 4 GPUs is up to 37 times faster than that using
  24-threaded 2 CPUs.\n\nPasses: Conference Pass, Parallel Algorithms, Perf
 ormance Analysis and Optimization\n\nTag: Conference Pass, Parallel Algori
 thms, Performance Analysis and Optimization
URL:https://2018.isc-program.com/presentation/?id=post117&sess=sess113
END:VEVENT
END:VCALENDAR

