Comparison of Road Traffic Simulation Speed on CPU and GPU

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43956278" target="_blank" >RIV/49777513:23520/19:43956278 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/DS-RT47707.2019.8958702" target="_blank" >http://dx.doi.org/10.1109/DS-RT47707.2019.8958702</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/DS-RT47707.2019.8958702" target="_blank" >10.1109/DS-RT47707.2019.8958702</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Comparison of Road Traffic Simulation Speed on CPU and GPU

Popis výsledku v původním jazyce

In this paper, we describe a fair comparison of the performance of a microscopic road traffic simulation performed on a GPU and on a CPU. The aim of our work is to determine the speedup, which can be achieved if the GPU is used for the same simulation instead of the (multi-core) CPU. A microscopic road traffic simulator capable of running on both platforms was created for this purpose with the aim to make the GPU-based and the CPU-based simulations as similar as possible. The performances of both the GPU-based and the CPU-based simulations were tested using two different road traffic models (a car-following model and a cellular automaton model), four road traffic networks (regular square grids of crossroads) of different sizes, and three different hardware configurations. The maximal achieved speedup using the GPU instead of the multi-core CPU for the cellular automaton model was 12.4. For the car-following model, the maximal achieved speedup was 10.7.

Název v anglickém jazyce

Comparison of Road Traffic Simulation Speed on CPU and GPU

Popis výsledku anglicky

In this paper, we describe a fair comparison of the performance of a microscopic road traffic simulation performed on a GPU and on a CPU. The aim of our work is to determine the speedup, which can be achieved if the GPU is used for the same simulation instead of the (multi-core) CPU. A microscopic road traffic simulator capable of running on both platforms was created for this purpose with the aim to make the GPU-based and the CPU-based simulations as similar as possible. The performances of both the GPU-based and the CPU-based simulations were tested using two different road traffic models (a car-following model and a cellular automaton model), four road traffic networks (regular square grids of crossroads) of different sizes, and three different hardware configurations. The maximal achieved speedup using the GPU instead of the multi-core CPU for the cellular automaton model was 12.4. For the car-following model, the maximal achieved speedup was 10.7.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT)

ISBN

978-1-72812-923-5

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

9-16

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Cosenza, Itálie

Datum konání akce

7. 10. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—