11100

A Cloud Computing Service Architecture of a Parallel Algorithm Oriented to Scientific Computing with CUDA and Monte Carlo

Ji Yimu, Kuang Zizhuo, Pan Qiao Yu, Sun Yanpeng, Kang Jiangbang, Huang Wei
College of Computer, Nanjing University of Posts and Telecommunication, Jiangsu, China
Cybernetics and Information Technologies, Volume 13, Special Issue, 2013
@article{yimu2013cloud,

   title={A Cloud Computing Service Architecture of a Parallel Algorithm Oriented to Scientific Computing with CUDA and Monte Carlo},

   author={Yimu, Ji and Zizhuo, Kuang and Yu, Pan Qiao and Yanpeng, Sun and Jiangbang, Kang and Wei, Huang},

   year={2013}

}

Download Download (PDF)   View View   Source Source   

403

views

The GPGPU (General Purpose Graphics Processing Units) have become a whole new area for research due to the fast development of GPU hardware and programming tools, such as CUDA (Compute Unified Device Architecture). Here we have made a research on CUDA and its applications in the field of scientific computation, as organ electronics. We propose one solution of the parallel computation in global optimization of the physical characteristics in organ electronics with Monte Carlo, and one cloud service architecture for parallel computation of organ electronics was designed. Finally, one case of computing the organ molecule moving orbit was implemented based on the above solution and architecture, and has got a good display by the cloud service.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

167 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1273 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: