Wanglong Yan, Xiaohua Shi, Xin Yan, Lina Wang
Speeded-Up Robust Feature (SURF) algorithm is widely used for image feature detecting and matching in computer vision area. Open Computing Language (OpenCL) is a framework for writing programs that execute across heterogeneous platforms consisting of CPUs, GPUs, and other processors. This paper introduces how to implement an open-sourced SURF program, namely OpenSURF, on general purpose […]
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Leonardo Jero
In recent years the need to solve complex problems that require large computing resources in shorter time has especially arisen. Some of these in the scientific field are: weather forecast, seismic simulations, chemical reactions simulation and studies on the human genoma [1]. All of them belong to the "Grand Challenge Problems" set. As can be […]
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Manish Pandey, Himanshu Pandey, Sanjay Sharma
The all-pairs shortest paths (APSP) problem finds the shortest path distances between all pairs of vertices,and is one of the most fundamental graph problems. In this paper, a parallel recursive partitioning approach to APSP problem using Open Computing Language (OpenCL) for directed and dense graphs with no negative cyclesbased on R-Kleene algorithm, is presented, which […]
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Jan Krekan, Lubomir Dobos, Matus Pleva
The main goal of this paper is to discuss new & faster methods for testing the strength of security used in today’s wireless networks. This paper discusses probabilistic password generation methodsfor testing the real security of networks protected by WPA/WPA2 PSK (Pre-shared key) standard (also known as Personal mode). The main advantage of using those […]
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Orion Lawlor
We present a high performance GPU programming language, based on OpenCL, that is embedded in C++. Our embedding provides shared data structures, typesafe kernel invocation, and the ability to more naturally interleave CPU and GPU functions, similar to CUDA but with the portability of OpenCL. For expressivity, our language provides an abstraction that releases control […]

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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 11.4
  • SDK: AMD APP SDK 2.8
Node 2
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  • 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

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