Egil Fykse
The objective of this thesis is to compare the suitability of FPGAs, GPUs and DSPs for digital image processing applications. Normalized cross-correlation is used as a benchmark, because this algorithm includes convolution, a common operation in image processing and elsewhere. Normalized cross-correlation is a template matching algorithm that is used to locate predefined objects in […]
Kristoffer Clausen Thyholdt
The lattice Boltzmann method has become a valuable tool in computational fluid dynamics, one of the reasons is due to the simplicity of its coding. In order to maximize the performance potential of today’s computers, code has to be optimized for parallel execution. In order to achieve parallel execution of the lattice Boltzmann method, the […]
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Jaime C. Acosta, Brenda G. Medina, Humberto Mendoza
It is well known that malware (worms, botnets, etc…) thrive on communication systems. The process of detecting and analyzing malware is very latent and not well-suited for real-time application, which is critical especially for propagating malware. For this reason, recent methods identify similarities among malware dynamic trace logs to extract malicious behavior snippets. These snippets […]
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Martin Clauss
In this paper we investigate a solution to the problem of simulating the spread of epidemics in real-world trading networks. We developed an application that uses parallel computing devices (e.g. GPUs – Graphical Processing Units) with OpenCL (Open Computing Language). Furthermore, we use the epidemiological SIRmodel to represent the nodes of the trading network. Initially, […]
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Free GPU computing nodes at

Registered users can now run their OpenCL application at 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.

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