Interactive Refactoring for GPU Parallelization of Affine Loops

Kostadin Damevski, Madhan Muralimanohar
Virginia State University, Petersburg, VA 23806
Virginia State University, Technical report, 2012

   title={Interactive Refactoring for GPU Parallelization of Affine Loops},

   author={Damevski, K. and Muralimanohar, M.},



Download Download (PDF)   View View   Source Source   



Considerable recent attention has been given to the problem of porting existing code to heterogeneous computing architectures, such as GPUs. In this paper, we describe a novel, interactive refactoring tool that allows for quick and easy transformation of affine loops to execute on GPUs. Compared to previous approaches, our refactoring approach interactively combines the user’s knowledge with that of an automated parallelizer to produce parallel CUDA GPU code. The generated code retains the structure of the original loop in order to remain maintainable. The refactoring tool also computes and displays profitability metrics, intended to advise the user of the performance potential of the generated code.
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: