Cargando…

GPU in Physics Computation: Case Geant4 Navigation

General purpose computing on graphic processing units (GPU) is a potential method of speeding up scientific computation with low cost and high energy efficiency. We experimented with the particle physics simulation toolkit Geant4 used at CERN to benchmark its geometry navigation functionality on a G...

Descripción completa

Detalles Bibliográficos
Autores principales: Seiskari, Otto, Kommeri, Jukka, Niemi, Tapio
Lenguaje:eng
Publicado: 2012
Materias:
Acceso en línea:http://cds.cern.ch/record/1481237
_version_ 1780925947527036928
author Seiskari, Otto
Kommeri, Jukka
Niemi, Tapio
author_facet Seiskari, Otto
Kommeri, Jukka
Niemi, Tapio
author_sort Seiskari, Otto
collection CERN
description General purpose computing on graphic processing units (GPU) is a potential method of speeding up scientific computation with low cost and high energy efficiency. We experimented with the particle physics simulation toolkit Geant4 used at CERN to benchmark its geometry navigation functionality on a GPU. The goal was to find out whether Geant4 physics simulations could benefit from GPU acceleration and how difficult it is to modify Geant4 code to run in a GPU. We ported selected parts of Geant4 code to C99 & CUDA and implemented a simple gamma physics simulation utilizing this code to measure efficiency. The performance of the program was tested by running it on two different platforms: NVIDIA GeForce 470 GTX GPU and a 12-core AMD CPU system. Our conclusion was that GPUs can be a competitive alternate for multi-core computers but porting existing software in an efficient way is challenging.
id cern-1481237
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2012
record_format invenio
spelling cern-14812372019-09-30T06:29:59Zhttp://cds.cern.ch/record/1481237engSeiskari, OttoKommeri, JukkaNiemi, TapioGPU in Physics Computation: Case Geant4 NavigationOther Fields of PhysicsGeneral purpose computing on graphic processing units (GPU) is a potential method of speeding up scientific computation with low cost and high energy efficiency. We experimented with the particle physics simulation toolkit Geant4 used at CERN to benchmark its geometry navigation functionality on a GPU. The goal was to find out whether Geant4 physics simulations could benefit from GPU acceleration and how difficult it is to modify Geant4 code to run in a GPU. We ported selected parts of Geant4 code to C99 & CUDA and implemented a simple gamma physics simulation utilizing this code to measure efficiency. The performance of the program was tested by running it on two different platforms: NVIDIA GeForce 470 GTX GPU and a 12-core AMD CPU system. Our conclusion was that GPUs can be a competitive alternate for multi-core computers but porting existing software in an efficient way is challenging.arXiv:1209.5235oai:cds.cern.ch:14812372012-09-25
spellingShingle Other Fields of Physics
Seiskari, Otto
Kommeri, Jukka
Niemi, Tapio
GPU in Physics Computation: Case Geant4 Navigation
title GPU in Physics Computation: Case Geant4 Navigation
title_full GPU in Physics Computation: Case Geant4 Navigation
title_fullStr GPU in Physics Computation: Case Geant4 Navigation
title_full_unstemmed GPU in Physics Computation: Case Geant4 Navigation
title_short GPU in Physics Computation: Case Geant4 Navigation
title_sort gpu in physics computation: case geant4 navigation
topic Other Fields of Physics
url http://cds.cern.ch/record/1481237
work_keys_str_mv AT seiskariotto gpuinphysicscomputationcasegeant4navigation
AT kommerijukka gpuinphysicscomputationcasegeant4navigation
AT niemitapio gpuinphysicscomputationcasegeant4navigation