Yutong Qin, Jianbiao Lin, Xiang Huang
Ray tracing is a technique for generating an image by tracing the path of light through pixels in an image plane and simulating the effects of high-quality global illumination at a heavy computational cost. Because of the high computation complexity, it can’t reach the requirement of real-time rendering. The emergence of many-core architectures, makes it […]
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Joshua Penton
Deployment of parallel architectures in computing systems is increasing. In this paper we study the performance effects of a variety of programming techniques and technologies that utilize these parallel architectures as applied to example algorithms. We demonstrate that algorithms, which are highly parallel in nature, gain significant performance increases through proper application of both parallel […]
Sachitsing Dwarkan
Medical image registration is a computational task involving the spatial realignment of multiple sets of images of the same or different modalities. A novel method of using the Open Computing Language (OpenCL) framework to accelerate affine image registration across multiple processing architectures is presented. The use of this method on graphics processors results in a […]
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Jonathan Thompson, Kristofer Schlachter
This paper presents an overview of the OpenCL 1.1 standard [Khronos 2012]. We first motivate the need for GPGPU computing and then discuss the various concepts and technological background necessary to understand the programming model. We use concurrent matrix multiplication as a framework for explaining various performance characteristics of compiling and running OpenCL code, and […]
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Derek K. Gerstmann, Toby Potter, Michael Houston, Paul Bourke, Kwan-Liu Ma, Andreas Wicenec
Simulating the expansion of a Type II supernova using an adaptive computational fluid dynamics (CFD) engine yields a complex mixture of turbulent flow with dozens of physical properties. The dataset shown in this sketch was initially simulated on iVEC’s EPIC supercomputer (a 9600 core Linux cluster) using FLASH [Fryxell et al. 2000] to model the […]
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James Sweet
Due to the high demand for secure Internet usage, an improvement of the SSL performance is needed. This paper describes a technique to improve the performance of SSL by creating a CPU/GPU hybrid proxy to sit in front of a web server to only handle the SSL overheads. This will allow the utilization of high […]
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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

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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