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Simulation of Brownian Motion for Molecular Communications on a Graphics Processing Unit

  • Yun Tian(corresponding author)
    ,
  • Uri Rogers
    ,
  • Tobias Cain
    ,
  • ,
  • Fangyang Shen
*Corresponding author for this work
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution

Abstract

This work applies a graphics processing unit (GPU) to the study of molecular communication (MC) systems where molecules are used to exchange information. Most MC is based on Brownian motion and modeled via a stochastic differential equation that admits analytical solutions under certain rather restrictive assumptions. As such, emphasis is placed on Monte Carlo simulation methods to study MC. This paper explores the application of a GPU to reduce this simulation time using two different approaches. This work will show that the GPU can offer significant speedup relative to the CPU, providing avenues to deeper MC research unavailable using a CPU based simulator. With that, it will also show that some avenues towards deeper MC research remain infeasible due to excessively long simulation times, even when using a GPU.

Bibliographic Information

Output type

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution

Original language

English

Pages from-to (Number of pages)

Pages 267-270 (4 pages)

Publication milestones

  • Published - 2020

Publication status

Published - 2020

Publisher

Springer Verlag

Publication series

  • Publication series name: Advances in Intelligent Systems and Computing
    ISSN (Print): 2194-5357
    ISSN (Electronic): 2194-5365
    Volume: 1134
9783030430191

Publication IDs

  • Scopus: 85085732816

Host publication title

17th International Conference on Information Technology–New Generations, ITNG 2020

Host publication editors

  • Shahram Latifi