Hauptseite > Publikationsdatenbank > A New Spin on the Fast Multipole Method for GPUS: Rethinking the Far-Field Operators > print

001     1049541
005     20251213202221.0
037 _ _ |a FZJ-2025-05345
100 1 _ |a Lengvenis, Arijus
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111 2 _ |a 2025 IEEE International Parallel and Distributed Processing Symposium
|g IPDPS
|c Milano
|d 2025-06-03 - 2025-06-07
|w Italy
245 _ _ |a A New Spin on the Fast Multipole Method for GPUS: Rethinking the Far-Field Operators
260 _ _ |c 2025
336 7 _ |a Conference Paper
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520 _ _ |a The Fast Multipole Method (FMM) is an optimally efficient algorithm for solving N -body problems: a fundamental challenge in fields like astrophysics, plasma physics and molecular dynamics. It is particularly suited for computing 1/r potentials present in Coulomb and gravitational particle systems. Despite the near-field phase being trivially parallelisable, the far-field phase of the 1/r FMM currently lacks an efficient, massively parallel GPU algorithm fitting for the era of Exascale computing. Current state-of-the-art approaches either favor highly parallel but inefficient expansion shift operators or asymptotically efficient but poorly parallelisable rotation-based ones. Recently, a breakthrough was made with the re-evaluation of a rotation operator variant called fast rotation, which dramatically increases caching effectiveness and marries the advantages of both methods. Thus, this paper incorporates this approach to create fast rotation-based operators that facilitate an efficient far-field algorithm for the FMM on GPUs. Additionally, a warpcentric data access scheme is co-developed alongside a matching octree design, which yields coalesced memory access patterns for the bottleneck operators of the far-field phase. The fast rotation algorithm is enhanced with a cache-tiling mechanism, maximising GPU cache utilisation. Compared to the state-of-theart GPU FMM far-field implementation, our algorithm achieves lower running times across the board and a 2.47 x speedup for an increased precision simulation, with the performance improvement growing as precision increases, providing concrete proof of efficacy for dense particle systems.
536 _ _ |a 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)
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700 1 _ |a Dachsel, Holger
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700 1 _ |a Morgenstern, Laura
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700 1 _ |a Kabadshow, Ivo
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