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Nico van Heijningen
Due to recent developments: leaks of large lists of user passwords (e.g. LinkedIn), new probabilistic password cracking techniques and the introduction of password cracking using GPUs. Passwords can now be cracked faster than ever before. The leaked password lists have been analyzed by hackers and common patterns found inside the passwords are being exploited to […]
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Gerhard Zumbusch
Several highly optimized implementations of Finite Difference schemes are discussed. The combination of vectorization and an interleaved data layout, spatial and temporal loop tiling algorithms, loop unrolling, and parameter tuning lead to efficient computational kernels in one to three spatial dimensions, truncation errors of order two to twelve, and isotropic and compact anisotropic stencils. The […]
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Anshul Rai, Ranjita Bhagwan, Saikat Guha
Resource allocation is an integral, evolving part of many data center management problems such as virtual machine placement in data centers, network virtualization, and multi-path network routing. Since the problems are inherently NP-Hard, most existing systems use custom-designed heuristics to find a suitable solution. However, such heuristics are often rigid, making it difficult to extend […]
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Allan Svejstrup Nielsen, Allan Peter Engsig-Karup, Bernd Dammann
This report is intended as a quick introduction to the OpenCL framework and the aim is to facilitate a smooth transfer into the use OpenCL C for developers with previous GPGPU experience. The purpose of OpenCL is to allow for developers to use all compute resources available on a heterogeneous hardware platform. As well as […]
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Andreas Falkenstrom Mieritz
In this report we’ve created a linear algebra API using OpenCL, for use with MATLAB. We’ve demonstrated that the individual linear algebra components can be faster when using the GPU as compared to the CPU. We found that the API is heavily memory bound, but still faster than MATLAB in our testcase. The API components […]
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Christian Conti, William Sawyer
The main objective of this work is to explore the capacity of modern GPUs to accelerate the ICON (ICOsahedral Non-hydrostatic) model [4] developed by the Max-Planck-Institut fur Meteorologie (MPI-M) in Hamburg in collaboration with the Deutscher Wetterdienst (DWD). The ICON model is an atmospheric general circulation model suited for both global and regional scale simulation.
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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
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  • 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

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