Parallel Algorithm for Generation of Test Recommended Path using CUDA

Zhao Yu, Jae-Han Cho, Byoung-Woo Oh, Lee-Sub Lee
Department of Computer Engineering, Kumoh National Institute of Technology, Korea
International Journal of Engineering and Technology, Vol. 5, No.1, 2013
@article{yu2013parallel,

   title={Parallel Algorithm for Generation of Test Recommended Path using CUDA},

   author={Yu, Zhao and Cho, Jae-Han and Oh, Byoung-Woo and Lee, Lee-Sub},

   journal={International Journal of Engineering and Technology},

   volume={5},

   year={2013}

}

Download Download (PDF)   View View   Source Source   
Software testing of an application makes the user to find defect. The users, called testers, should test the various situations with test cases. In order to make test cases, many states and events have to be considered. It takes much time to create test cases with many states and events. Instead of using the common sequential algorithm, this paper proposes a parallel algorithm for generation of test cases. The proposed method achieves efficient performance using General-Purpose GPU (GPGPU), especially CUDA.
VN:F [1.9.22_1171]
Rating: 4.5/5 (2 votes cast)
Parallel Algorithm for Generation of Test Recommended Path using CUDA, 4.5 out of 5 based on 2 ratings

You must be logged in to post a comment.

* * *

* * *

* * *

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 11.4
  • SDK: AMD APP SDK 2.8
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 5.0.35, AMD APP SDK 2.8

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:

contact@hgpu.org