Szczegóły publikacji
Opis bibliograficzny
Pruned simulation-based optimal sailboat path search using micro HPC systems / Roman DĘBSKI, Bartłomiej ŚNIEŻYŃSKI // W: Computational Science – ICCS 2021 : 21st international conference : Krakow, Poland, June 16–18, 2021 : proceedings, Pt. 4 / eds. Maciej Paszyński, [et al.]. — Cham : Springer Nature Switzerland, cop. 2021. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 12745. Theoretical Computer Science and General Issues ; ISSN 0302-9743). — ISBN: 978-3-030-77969-6; e-ISBN: 978-3-030-77970-2. — S. 158–172. — Bibliogr., Abstr. — Publikacja dostępna online od: 2021-06-09
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 134732 |
|---|---|
| Data dodania do BaDAP | 2021-07-19 |
| DOI | 10.1007/978-3-030-77970-2_13 |
| Rok publikacji | 2021 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Computational Science 2021 |
| Czasopisma/serie | Lecture Notes in Computer Science, Theoretical Computer Science and General Issues |
Abstract
Simulation-based optimal path search algorithms are often solved using dynamic programming, which is typically computationally expensive. This can be an issue in a number of cases including near-real-time autonomous robot or sailboat path planners. We show the solution to this problem which is both effective and (energy) efficient. Its three key elements – an accurate and efficient estimator of the performance measure, two-level pruning (which augments the estimator-based search space reduction with smart simulation and estimation techniques), and an OpenCL-based spmd-parallelisation of the algorithm – are presented in detail. The included numerical results show the high accuracy of the estimator (the medians of relative estimation errors smaller than 0.003), the high efficacy of the two-level pruning (search space and computing time reduction from seventeen to twenty times), and the high parallel speedup (its maximum observed value was almost 40). Combining these effects gives (up to) 782 times faster execution. The proposed approach can be applied to various domains. It can be considered as an optimal path planing framework parametrised by a problem specific performance measure heuristic/estimator.
