9003

Performance Analysis of a Symmetric Cryptographic Algorithm on Multicore Architectures

Adrian Pousa, Victoria Sanz, Armando de Giusti
Instituto de Investigacion en Informatica LIDI – School of Computer Science, National University of La Plata
Computer Science & Technology Series XVII Argentine Congress of Computer Science Selected Papers, 2012
@article{pousa2012performance,

   title={Performance Analysis of a Symmetric Cryptographic Algorithm on Multicore Architectures},

   author={POUSA, ADRI{‘A}N and SANZ, VICTORIA and DE GIUSTI, ARMANDO},

   year={2012}

}

Download Download (PDF)   View View   Source Source   

413

views

In this paper, a performance analysis of the symmetric encryption algorithm AES (Advanced Encryption Standard) on various multicore architectures is presented. To this end, three implementations based on C language that use the parallel programming tools OpenMP, MPI and CUDA to be run on multicore processors, multicore clusters and GPU, respectively, were carried out. The efficiency obtained by the CUDA implementation of the algorithm as input data size increases is shown.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

149 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1236 peoples are following HGPU @twitter

Featured events

* * *

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: