Sangho Lee, Youngsok Kim, Jangwoo Kim, Jong Kim
Graphics processing units (GPUs) are important components of modern computing devices for not only graphics rendering, but also efficient parallel computations. However, their security problems are ignored despite their importance and popularity. In this paper, we first perform an in-depth security analysis on GPUs to detect security vulnerabilities. We observe that contemporary, widely-used GPUs, both […]
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Roman V. Baluev
This is a parallelized algorithm performing a decomposition of a noisy time series into a number of frequency components. The algorithm analyses all suspicious periodicities that can be revealed, including the ones that look like an alias or noise at a glance, but later may prove to be a real variation. After selection of the […]
Mohammad Motamedi, Sima Sobhieh, S. Ahmad Motamedi, Amir Hossein Rezaie
The Curvelet transform is among one of the most powerful time-frequency representations of an image. However, since it is not a fast algorithm it cannot be employed in most real-time and/or large scale applications. This paper proposes a novel algorithm to speed up the Curvelet transform by both optimizing it for repetitive Curvelet usage and […]
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Jason Clemons, Andrew Jones, Robert Perricone, Silvio Savarese, Todd Austin
The deployment of computer vision algorithms in mobile applications is growing at a rapid pace. A primary component of the computer vision software pipeline is feature extraction, which identifies and encodes relevant image features. We present an embedded heterogeneous multicore design named EFFEX that incorporates novel functional units and memory architecture support, making it capable […]
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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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