Accelerating a ray launching model using GPU with CUDA

Abstract

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.

Publication DOI: https://doi.org/10.1049/cp.2018.1197
Divisions: College of Engineering & Physical Sciences
Event Title: 12th European Conference on Antennas and Propagation
Event Type: Other
Event Dates: 2018-04-09 - 2018-04-13
Uncontrolled Keywords: GPU,propagation model,accelerated computing,Ray tracing
Last Modified: 29 Oct 2024 16:56
Date Deposited: 09 May 2023 11:48
Full Text Link:
Related URLs: https://ieeexpl ... ocument/8568875 (Publisher URL)
PURE Output Type: Conference contribution
Published Date: 2018-04-09
Authors: Dai, Zhuangzhuang (ORCID Profile 0000-0002-6098-115X)
Watson, Robert

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License: Creative Commons Attribution


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