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DTSTAMP:20250822T115807Z
LOCATION:Campussaal - Plenary Room
DTSTART;TZID=Europe/Stockholm:20250616T102000
DTEND;TZID=Europe/Stockholm:20250616T105000
UID:submissions.pasc-conference.org_PASC25_sess149_pos127@linklings.com
SUMMARY:P17 - GPU-Accelerated DEM Simulations for Complex Particle Shapes:
  Optimizing Spheropolyhedron Contact Detection
DESCRIPTION:Carlo Elia Doncecchi (CEA)\n\nThe Discrete Element Method (DEM
 ) is an N-body numerical method widely used to model granular materials wi
 th various particle shapes, including complex geometries like spheropolyhe
 dra. A major computational challenge in DEM lies in contact detection, par
 ticularly for such complex shapes, which involve multiple simultaneous con
 tact points and intricate geometry requiring costly intersection evaluatio
 ns. This work focuses on adapting existing methods to efficiently handle s
 pheropolyhedra geometries on GPUs. Two key developments are presented: ext
 ending the PCCP (Parallelized by Contact Candidate Pair) algorithm to thes
 e complex shapes, which redefines computational granularity by assigning G
 PU threads to contact pairs, and an optimized memory data layout (SOA) for
  efficient GPU memory access and data locality. These contributions speed 
 up the contact detection and force calculation phases. The effectiveness o
 f these GPU optimization methods is demonstrated through their implementat
 ion in the ExaDEM open-source HPC code, with performance evaluations on NV
 IDIA A100 and Grace Hopper GPUs. These optimizations enable large-scale si
 mulations, handling from a few hundred thousand to several million particl
 es, while maintaining reasonable simulation times. This work represents a 
 significant advancement in DEM by enabling efficient large-scale simulatio
 ns with complex particle geometries.\n\nSession Chair: Chris Cantwell (Imp
 erial College London)\n\n
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