Accelerated Pressure Projection using OpenCL on GPUs

Davoud Saffar Shamshirgar
Department of Mechanics, KTH Stockhom
KTH, 2012

   title={Accelerated Pressure Projection using OpenCL on GPUs},

   author={Saffar Shamshirgar, D.},




Download Download (PDF)   View View   Source Source   



A GPU version of the pressure projection solver using OpenCL is implemented. Then it has been compared with CPU version which is accelerated with OpenMP. The GPU version shows a sensible reduction in time despite using a simple algorithm in the kernel. The nal code is plugged into a commercial uid simulator software. Dierent kinds of algorithms and data transfer methods have been investigated. Overlapping the computation and communication showed a more than 3 times speed-up versus the serial communication-computation pattern. Finally we exploit methods for partitioning data and writing kernels to use many of the bene ts of computation on a heterogeneous system. We ran all the simulations on a machine with an Intel core i7-2600 cpu and 16 GB main memory coupled with a GeForce GTX 560 Ti graphic processing unit on a windows OS.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Follow us on Twitter

HGPU group

1662 peoples are following HGPU @twitter

Like us on Facebook

HGPU group

337 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: