CUDA Implementation of a Lattice Boltzmann Method and Code Optimization

A. Jain
Tata Consultancy Services

   title={CUDA Implementation of a Lattice Boltzmann Method and Code Optimization},

   author={Jain, Anubhav}


Download Download (PDF)   View View   Source Source   



We study fluid flow in a 2D lid driven cavity for large Reynolds numbers using multirelaxation time – Lattice Boltzmann Method(LBM). LBM is an alternative to conventional CFD methods that solve Navier-Stokes equations to simulate incompressible fluid dynamics. In LBM, one solves the linearized Boltzmann equation on a discrete lattice to study spatio-temporal evolution of flow field. The data parallel implementation of the Lattice Boltzmann Method makes the GPGPU as a platform of choice for such computation. Several CUDA optimizations are implemented to achieve desired performance, these are discussed below.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Follow us on Twitter

HGPU group

1658 peoples are following HGPU @twitter

Like us on Facebook

HGPU group

335 people like HGPU on Facebook

* * *

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: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • 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: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

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 © 2010-2015 hgpu.org

All rights belong to the respective authors

Contact us: