BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:Asia/Seoul
X-LIC-LOCATION:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:18871231T000000
DTSTART:19881009T020000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20230103T035311Z
LOCATION:Room 325-AB\, Level 3\, West Wing
DTSTART;TZID=Asia/Seoul:20221208T153000
DTEND;TZID=Asia/Seoul:20221208T170000
UID:siggraphasia_SIGGRAPH Asia 2022_sess170_papers_570@linklings.com
SUMMARY:Fast Octree Neighborhood Search for SPH Simulations
DESCRIPTION:Technical Papers\n\nFast Octree Neighborhood Search for SPH Si
 mulations\n\nFernández-Fernández, Westhofen, Löschner, Jeske, Longva...\n\
 nWe present a new octree-based neighborhood search method for SPH simulati
 on. A speedup of up to 1.9x is observed in comparison to state-of-the-art 
 methods which rely on uniform grids. While our method focuses on maximizin
 g performance in fixed-radius SPH simulations, we show that it can also be
  used in scenarios where the particle support radius is not constant thank
 s to the adaptive nature of the octree acceleration structure.\n\nNeighbor
 hood search methods typically consist of an acceleration structure that pr
 unes the space of possible particle neighbor pairs, followed by direct dis
 tance comparisons between the remaining particle pairs. Previous works hav
 e focused on minimizing the number of comparisons. However, in an effort t
 o minimize the actual computation time, we find that distance comparisons 
 exhibit very high throughput on modern CPUs. By permitting more comparison
 s than strictly necessary, the time spent on preparing and searching the a
 cceleration structure can be reduced, yielding a net positive speedup. The
  choice of an octree acceleration structure, instead of the uniform grid t
 ypically used in fixed-radius methods, ensures balanced computational task
 s. This benefits both parallelism and provides consistently high computati
 onal intensity for the distance comparisons. We present a detailed account
  of high-level considerations that, together with low-level decisions, ena
 ble high throughput for performance-critical parts of the algorithm.\n\nFi
 nally, we demonstrate the high performance of our algorithm on a number of
  large-scale fixed-radius SPH benchmarks and show in experiments with a su
 pport radius ratio up to 3 that our method is also effective in multi-reso
 lution SPH simulations.\n\nRegistration Category: FULL ACCESS, ON-DEMAND A
 CCESS\n\nLanguage: ENGLISH\n\nFormat: IN-PERSON, ON-DEMAND
URL:https://sa2022.siggraph.org/en/full-program/?id=papers_570&sess=sess17
 0
END:VEVENT
END:VCALENDAR