Brian Guenter, Diego Nehab
Neon is a high-level domain-specific programming language for writing efficient image processing programs which can run on either the CPU or the GPU. End users write Neon programs in a C# programming environment. When the Neon program is executed, our optimizing code generator outputs human-readable source files for either the CPU or GPU. These source […]
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Jiawen Chen, Ilya Baran, Fredo Durand, Wojciech Jarosz
Light scattering in a participating medium is responsible for several important effects we see in the natural world. In the presence of occluders, computing single scattering requires integrating the illumination scattered towards the eye along the camera ray, modulated by the visibility towards the light at each point. Unfortunately, incorporating volumetric shadows into this integral, […]
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Alan Brunton, Jiying Zhao
In this paper, we propose a real-time video watermarking system on programmable graphics hardware. Real-time video watermarking is important to the use of digital video in legal proceedings, security surveillance, new reportage and commercial video transactions. The watermarking scheme implemented here is based on Wong’s scheme for image watermarking, and is designed to detect and […]
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Wesley De Neve, Dieter Van Rijsselbergen, Charles Hollemeersch, Jan De Cock, Stijn Notebaert, Rik Van de Walle
Although pixel shaders were designed for the creation of programmable rendering effects, they can also be used as generic processing units for vector data. In this paper, attention is paid to an implementation of the YCoCg-R to RGB color space transform, as defined in the H.264/AVC Fidelity Range Extensions, by making use of pixel shaders. […]
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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
  • GPU device 0: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • 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: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

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