Strippgen, DavidNagel, Kai2018-11-272018-11-272009978-1-4244-4906-4https://depositonce.tu-berlin.de/handle/11303/8605http://dx.doi.org/10.14279/depositonce-7739Today's graphics processing units (GPU) have tremendous resources when it comes to raw computing power. The simulation of large groups of agents in transport simulation has a huge demand of computation time. Therefore it seems reasonable to try to harvest this computing power for traffic simulation. Unfortunately simulating a network of traffic is inherently connected with random memory access. This is not a domain that the SIMD (single instruction, multiple data) architecture of GPUs is known to work well with. In this paper the authors will try to achieve a speedup by computing multi-agent traffic simulations on the graphics device using NVIDIA's CUDA framework.en380 Handel, Kommunikation, Verkehrmulti agent simulationlarge-scale simulationGPGPUGPUmulti-coreCUDAConference Object