8835

Hybrid Single/Double Precision Floating-Point Computation on GPU Accelerators for 2-D FDTD

Hasitha Muthumala Waidyasooriya, Yasuhiro Takei, Masanori Hariyama, Michitaka Kameyama
Graduate School of Information Sciences, Tohoku University, Japan
International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA), pp.1001-1002, 2012
@article{waidyasooriya2012hybrid,

   title={Hybrid Single/Double Precision Floating-Point Computation on GPU Accelerators for 2-D FDTD},

   author={Waidyasooriya, H.M. and Takei, Y. and Hariyama, M. and Kameyama, M.},

   year={2012}

}

Download Download (PDF)   View View   Source Source   

382

views

Acceleration of FDTD (Finite-Difference TimeDomain) is very important in computational electromagnetic. We propose a hybrid single/double precision floating-point computation to accelerate FDTD on GPUs. We apply single-precision when the dynamic range of the electromagnetic field is low and double-precision when the dynamic range is high. According to the experimental results, we achieved over 35 times of speed-up compared to the CPU implementation and over 1.79 times speed-up compared to the conventional GPU acceleration.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

168 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1275 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: