Application of GPU Computing to Some Urban Traffic Problems
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2016-11-30
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Universidade Federal de Goiás
Resumo
The present work studies and proposes GPU-based parallel algorithms and implementations
for the problem of macroscopic assignment of urban traffic on large-scale networks,
promoting an in-depth investigation on each sub-problem that must be efficiently solved
during the traffic assignment process. Among the main contributions of this work, there are:
1) the first GPU-based algorithm for the enumeration of chordless cycles; 2) a new parallel
GPU-based shortest path algorithm that takes advantage of some common properties of urban
traffic networks; a refinement in the parallel reduction implementation proposed by one of the
leaders in the GPU market, which resulted in a 2.8x speedup relative to its original version;
and finally, 3) a parallel algorithm for the macroscopic traffic assignment problem, 39x faster
than the equivalent sequential approach when applied to large scale networks.
The main goal of this thesis is to contribute to the extension of the PET-Gyn software,
proposing efficient GPU data structures and parallel algorithms for a faster resolution of two
well known problems in the literature: The Traffic Assignment Problem (TAP) and the
Enumeration of Chordless Cycles. When applied to difficult input sets, the performed
experiments showed a clear advantage of the parallel algorithms over their sequential
versions.
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JRADI, Walid Abdala Rfaei. Application of GPU Computing to Some Urban Traffic Problems. 2016. 195 f. Tese (Doutorado em Ciência da Computação em Rede) - Universidade Federal de Goiás, Goiânia, 2016.