13126

Applications

Per Karlsson
This thesis tries to answer how to design a framework for image processing on the GPU, supporting the common environments OpenGL GLSL, OpenCL and CUDA. An generalized view of GPU image processing is presented. The framework is called gpuip and is implemented in C++ but also wrapped with Python-bindings. The framework is cross-platform and works […]
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Grzegorz Michalski, Norbert Sczygiol, Siergiei Leonov
This paper presents a simulation of the casting solidification process performed on graphics processors compatible with nVidia CUDA architecture. Indispensable for the parallel implementation of a computer simulation of the solidification process, it was necessary to modify the numerical model. The new approach shown in this paper allows the process of matrix building to be […]
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E. Bajrovic, S. Benkner
Heterogeneous parallel architectures combining conventional multicore CPUs with GPUs and other types of accelerators promise significant performance gains compared to homogeneous systems. However, exploiting the full potential of such systems is becoming more and more challenging often forcing programmers to combine different programming models and parallelization strategies. A promising approach to coping with the increased […]
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Owe Philipsen, Christopher Pinke, Alessandro Sciarra, Matthias Bach
We present the Lattice QCD application CL2QCD, which is based on OpenCL and can be utilized to run on Graphic Processing Units as well as on common CPUs. We focus on implementation details as well as performance results of selected features. CL2QCD has been successfully applied in LQCD studies at finite temperature and density and […]
Mario Spera
Graphics Processing Units (GPUs) can speed up the numerical solution of various problems in astrophysics including the dynamical evolution of stellar systems; the performance gain can be more than a factor 100 compared to using a Central Processing Unit only. In this work I describe some strategies to speed up the classical N-body problem using […]
Sparsh Mittal, Saket Gupta, Sudeb Dasgupta
Digital image processing(DIP) is an ever growing area with a variety of applications including medicine, video surveillance, and many more. To implement the upcoming sophisticated DIP algorithms and to process the large amount of data captured from sources such as satellites or medical instruments, intelligent high speed real-time systems have become imperative. Image processing algorithms […]
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O. Kaczmarek, C. Schmidt, P. Steinbrecher, M. Wagner
Lattice Quantum Chromodynamics simulations typically spend most of the runtime in inversions of the Fermion Matrix. This part is therefore frequently optimized for various HPC architectures. Here we compare the performance of the Intel Xeon Phi to current Kepler-based NVIDIA Tesla GPUs running a conjugate gradient solver. By exposing more parallelism to the accelerator through […]
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Fahad Khalid, Frank Feinbube, Andreas Polze
The pipeline pattern for parallel programs is utilized in a wide array of scientific applications designed for execution on hybrid CPU-GPU architectures. However, there is a dearth of tools and libraries to support implementation of pipeline parallelism for hybrid architectures. We present the Hybrid Pipeline Framework (HyPi) that is intended to fill this gap. HyPi […]
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Zachary Langbert, Mark C. Lewis
Physically accurate hard sphere collisions are inherently sequential as the order in which collisions occur can have a significant impact on the resulting system. This makes processing hard sphere collisions on parallel hardware challenging. We present an approach to solving this problem that can be implemented using OpenCL that runs on current hardware. This approach […]
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Bachir Bouhadef, Mauro Morganti, Giuseppe Terreni
Graphics Processing Units are high performance co-processors originally intended to improve the use and the acceleration of computer graphics applications. Because of their performance, researchers have extended their use beyond the computer graphics scope. We have investigate the possibility of implementing and speeding up online neutrino trigger algorithms in the KM3Net-It experiment using a CPU-GPU […]
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Ardalan Amiri Sani, Lin Zhong, Dan S. Wallach
Legacy device drivers implement both device resource management and isolation. This results in a large code base with a wide high-level interface making the driver vulnerable to security attacks. This is particularly problematic for increasingly popular accelerators like GPUs that have large, complex drivers. We solve this problem with library drivers, a new driver architecture. […]
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Simon Jones, Matthew Studley, Alan Winfield
It is desirable for a robot to be able to run on-board simulations of itself in a model of the world to evaluate action consequences and test new controller solutions, but simulation is computationally expensive. Modern mobile System-on-Chip devices have high performance at low power consumption levels and now incorporate powerful graphics processing units, making […]
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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: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • 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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