Efficiently Mapping the AES Encryption Algorithm on GPUs

Wagner M. Nunan Zola, Luis C. Erpen De Bona
Federal University of Parana, Department of Informatics, Brazil
CSBS, 2012

   title={Efficiently Mapping the AES Encryption Algorithm on GPUs},

   author={Zola, Wagner M Nunan and De Bona, Luis C Erpen},



Download Download (PDF)   View View   Source Source   



Warped AES is a high performance heterogeneous GPU/CPU-SSE parallel method for encryption using GPUs. Considering the performance of encryption in GPU memory alone, our algorithm outperforms current published implementations on comparable hardware. In our ongoing research, we have also devised a speculative method for high throughput encryption on GPUs, while preserving low latency to client CPU applications. In this work we emphasize on techniques used to efficiently map the AES CTR encryption tasks for parallel execution on GPUs.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Follow us on Twitter

HGPU group

1660 peoples are following HGPU @twitter

Like us on Facebook

HGPU group

334 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: