Accelerating a ray launching model using GPU with CUDA

Zhuangzhuang Dai, Robert Watson

Research output: Chapter in Book/Published conference outputConference publication


The high computational cost of accurate deterministic wave propagation models often prevent them from being used in channel modelling. In this work, we present our experience of attempts to accelerate our 2.5D ray launching model using GPUs (Graphic Processing Units), which continue to grow in popularity due to their vast computation capability. At the heart of this trial is an implementation of a ray-surface intersection detection function, which was found to be the bottleneck of serial CPU computation, using NVIDIA's CUDA (Compute Unified Device Architecture). Various optimization efforts are made to obtain the best overall performance. The intersection detection function executes seven times faster on a large urban scenario after acceleration on a modest laptop GPU. This paper details the implementation of the CUDAbased intersection detection function and presents the acceleration results for different environments.
Original languageEnglish
Title of host publication2018 12th European Conference on Antennas and Propagation (EuCAP)
Number of pages3
Publication statusPublished - 9 Apr 2018
Event12th European Conference on Antennas and Propagation -
Duration: 9 Apr 201813 Apr 2018


Conference12th European Conference on Antennas and Propagation
Abbreviated titleEuCAP2018


  • GPU
  • propagation model
  • accelerated computing
  • Ray tracing


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