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thisalmandula authored Jan 23, 2025

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# GPU_accelerated_LPT_CFD_code
This repository contains GPU accelerated version of the particle tracking model developed by Merel Kooi for biofouled microplastic particles ( available at: https://pubs.acs.org/doi/10.1021/acs.est.6b04702) written in CUDA Fortran and CUDA Python. This repository is intended as a learning tool for GPU programming and developed during the TRA220 GPU-accelerated Computational Methods using Python and CUDA offered at Chalmers University of Technology.
This repository contains GPU accelerated version of the particle tracking model developed by Merel Kooi for biofouled microplastic particles ( available at: https://pubs.acs.org/doi/10.1021/acs.est.6b04702) written in CUDA Fortran and CUDA Python. This repository is intended as a learning tool for GPU programming and developed during the TRA220 GPU-accelerated Computational Methods using Python and CUDA offered at Chalmers University of Technology (https://www.tfd.chalmers.se/~lada/CUDA-tracks.html).

The performance of an LPT code developed in Python and Fortran was evaluated on both CPU and GPU architectures. This study aimed to quantify the performance enhancements achieved by running LPT simulations on GPUs and to compare the efficiencies of CUDA implementations in Python versus Fortran. The number of particles was varied from 4 (2×2) to 16,384 (128×128) to assess scalability and computational efficiency. The following simulations were conducted on an NVIDIA GeForce RTX 3070 GPU. The results are illustrated in the figure below.

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