11103

Parallel Firewalls on General-Purpose Graphics Processing Units

Kamal Chandra Reddy, Ankit Tharwani, Ch.Vamshi Krishna, Lakshminarayanan.V
Department of Computer Engineering, Malaviya National Institute of Technology, Jaipur, India
arXiv:1312.4188 [cs.DC], (15 Dec 2013)
@article{2013arXiv1312.4188R,

   author={Reddy}, K.~C. and {Tharwani}, A. and {Vamshi Krishna}, C. and {V}, L.},

   title={"{Parallel Firewalls on General-Purpose Graphics Processing Units}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1312.4188},

   primaryClass={"cs.DC"},

   keywords={Computer Science – Distributed, Parallel, and Cluster Computing},

   year={2013},

   month={dec},

   adsurl={http://adsabs.harvard.edu/abs/2013arXiv1312.4188R},

   adsnote={Provided by the SAO/NASA Astrophysics Data System}

}

Download Download (PDF)   View View   Source Source   

247

views

Firewalls use a rule database to decide which packets will be allowed from one network onto another thereby implementing a security policy. In high-speed networks as the inter-arrival rate of packets decreases, the latency incurred by a firewall increases. In such a scenario, a single firewall become a bottleneck and reduces the overall throughput of the network.A firewall with heavy load, which is supposed to be a first line of defense against attacks, becomes susceptible to Denial of Service (DoS) attacks. Many works are being done to optimize firewalls.This paper presents our implementation of different parallel firewall models on General-Purpose Graphics Processing Unit (GPGPU). We implemented the parallel firewall architecture proposed in and introduced a new model that can effectively exploit the massively parallel computing capabilities of GPGPU.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

122 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1179 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: