11854

The GENGA Code: Gravitational Encounters in N-body simulations with GPU Acceleration

Simon L. Grimm, Joachim G. Stadel
Institute for Computational Science, University of Zurich, Winterthurerstrasse 190, CH-8057, Zurich, Switzerland
arXiv:1404.2324 [astro-ph.EP], (8 Apr 2014)
@article{2014arXiv1404.2324G,

   author={Grimm}, S.~L. and {Stadel}, J.~G.},

   title={"{The GENGA Code: Gravitational Encounters in N-body simulations with GPU Acceleration}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1404.2324},

   primaryClass={"astro-ph.EP"},

   keywords={Astrophysics – Earth and Planetary Astrophysics},

   year={2014},

   month={apr},

   adsurl={http://adsabs.harvard.edu/abs/2014arXiv1404.2324G},

   adsnote={Provided by the SAO/NASA Astrophysics Data System}

}

Download Download (PDF)   View View   Source Source   Source codes Source codes

Package:

661

views

We describe a GPU implementation of a hybrid symplectic N-body integrator, GENGA (Gravitational ENcounters with Gpu Acceleration), designed to integrate planet and planetesimal dynamics in the late stage of planet formation and stability analysis of planetary systems. GENGA is based on the integration scheme of the Mercury code (Chambers 1999), which handles close encounters with very good energy conservation. It uses mixed variable integration (Wisdom & Holman 1991) when the motion is a perturbed Kepler orbit and combines this with a direct N-body Bulirsch-Stoer method during close encounters. The GENGA code supports three simulation modes: Integration of up to 2048 massive bodies, integration with up to a million test particles, or parallel integration of a large number of individual planetary systems. GENGA is written in CUDA C and runs on all Nvidia GPUs with compute capability of at least 2.0. All operations are performed in parallel, including the close encounter detection and the grouping of independent close encounter pairs. Compared to Mercury, GENGA runs up to 30 times faster. GENGA is available as open source code from https://bitbucket.org/sigrimm/genga.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

169 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1280 peoples are following HGPU @twitter

* * *

Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: AMD APP SDK 2.9
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 6.0.1, AMD APP SDK 2.9

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2014 hgpu.org

All rights belong to the respective authors

Contact us: