Juan Andres Fraire, Pablo Ferreyra, Carlos Marques
The number of space objects such as satellites, spacecraft, and debris are increasing significantly, and so is the need for tracking them for security and collision avoidance purposes. In this context, as parallelism is becoming a new paradigm, the need of implementing high performance propagators remain unmet. For this, we implemented Simplified General Perturbations No. […]
View View   Download Download (PDF)   
Nicolo' Savioli
The aim of my thesis is to parallelize the Weighting Histogram Analysis Method (WHAM), which is a popular algorithm used to calculate the Free Energy of a molecular system in Molecular Dynamics simulations. WHAM works in post processing in cooperation with another algorithm called Umbrella Sampling. Umbrella Sampling has the purpose to add a biasing […]
View View   Download Download (PDF)   
Gary Macindoe
The use of linear algebra routines is fundamental to many areas of computational science, yet their implementation in software still forms the main computational bottleneck in many widely used algorithms. In machine learning and computational statistics, for example, the use of Gaussian distributions is ubiquitous, and routines for calculating the Cholesky decomposition, matrix inverse and […]
View View   Download Download (PDF)   
Mohamed Elhoseiny, Hossam Faheem, Taymour Nazmy, Eman Shaaban
Real time processing for teamwork action recognition is a challenge, due to complex computational models to achieve high system performance. Hence, this paper proposes a framework based on Graphical Processing Units (GPUs) to achieve a significant speed up in the performance of role based activity recognition of teamwork. The framework can be applied in various […]
View View   Download Download (PDF)   
Baha Sen, Nesrin Aydin Atasoy, Caner Ozcan
It is important to obtain the results of methods that are used in solving scientific and engineering problems rapidly for users and application developers. Parallel programming techniques have been developed alongside serial programming because the importance of performance has been increasing day by day while developing computer applications.Various methods such as Gauss Elimination (GE) Method, […]
View View   Download Download (PDF)   
Bogdan Oancea, Tudorel Andrei, Andreea Iluzia Iacob
Parallel computing can offer an enormous advantage regarding the performance for very large applications in almost any field: scientific computing, computer vision, databases, data mining, and economics. GPUs are high performance many-core processors that can obtain very high FLOP rates. Since the first idea of using GPU for general purpose computing, things have evolved and […]
View View   Download Download (PDF)   
O.S. Hilko, S.P. Kundas, I.A. Gishkeluk
In the paper the result of application of artificial neural networks (ANN) for radionuclides transport modelling with surface runoff is presented. ANN with supervised training based on back propagation algorithm was used to predict radionuclides transport in the soil and on its surface. Application of ANN for substances migration modelling is worth using, because it […]
View View   Download Download (PDF)   
Joseph Issa
The change in processor architectures and 3D benchmarks makes performance characterization important for every processor and 3D application generation. Recent 3D applications require large amount of data to be processed by the GPU and the CPU. This leads to the importance in analyzing processor performance for different architectures and benchmarks so that benchmarks and processors […]
View View   Download Download (PDF)   
Piotr Pawliczek, Witold Dzwinel, David A. Yuen
Multidimensional scaling (MDS) is a very popular and reliable method used in feature extraction and visualization of multidimensional data. The role of MDS is to reconstruct the topology of an original N-dimensional feature space consisting of M feature vectors in target 2-D (3-D) Euclidean space. It can be achieved by minimization of the error – […]
View View   Download Download (PDF)   
M.R. Lopez-Torres, J.L. Guisado, F. Jimenez-Morales, F. Diaz-del-Rio
We present a parallel implementation for Graphics Processing Units (GPUs) of a model based on cellular automata (CA) to simulate laser dynamics. A cellular automaton is an inherent parallel type of algorithm that is very suitable to simulate complex systems formed by many individual components which give rise to emergent behaviours. We exploit the parallel […]
View View   Download Download (PDF)   
Aleksandr Khasymski, M. Mustafa Rafique, Ali R. Butt, Sudharshan S. Vazhkudai, Dimitrios S. Nikolopoulos
The exponential growth in user and application data entails new means for providing fault tolerance and protection against data loss. High Performance Computing (HPC) storage systems, which are at the forefront of handling the data deluge, typically employ hardware RAID at the backend. However, such solutions are costly, do not ensure end-to-end data integrity, and […]
View View   Download Download (PDF)   
Fan Zhang, Zheng Li, Bingnan Wang, Maosheng Xiang, Wen Hong
In this paper, a new hybrid general-purpose computation on GPU (GPGPU) and computer graphics synthetic aperture radar (SAR) simulation method for complex scenes is proposed. Previous SAR simulations for complex scenes only use GPU’s graphics capabilities for scattering calculation in graphical electromagnetic computing (GRECO) algorithm. The new hybrid method use GPU’s graphics and parallel computing […]
View View   Download Download (PDF)   
Page 1 of 3123

* * *

* * *

Follow us on Twitter

HGPU group

1666 peoples are following HGPU @twitter

Like us on Facebook

HGPU group

339 people like HGPU on Facebook

* * *

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.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2015 hgpu.org

All rights belong to the respective authors

Contact us: