Feifei Shen, Zhenjian Song, Congrui Wu, Jiaqi Geng, Qingyun Wang
Study of general purpose computation by GPU (Graphics Processing Unit) can improve the image processing capability of micro-computer system. This paper studies the parallelism of the different stages of decimation in time radix 2 FFT algorithm, designs the butterfly and scramble kernels and implements 2D FFT on GPU. The experiment result demonstrates the validity and […]
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Marcus Hinders
This thesis describes how the performance of job management systems on heterogeneous computing grids can be increased with Graphics Processing Units (GPU). The focus lies on describing what is required to extend the grid to support the Open Computing Language (OpenCL) and how an OpenCL application can be implemented for the heterogeneous grid. Additionally, already […]
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Xinpan Yuan, Jun Long, Hao Zhang, Zuping Zhang, Weihua Gui
Although considerable effort has been devoted to duplicate document detection (DDD) and its applications, there is very limited study on the optimization of its time-consuming functions. An experimental analysis which is conducted on a million Grant Proposal documents from the nsfc.gov.cn shows that even by using the clustering and the sampling methods, the speed of […]
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Alejandro Segovia
Using hardware acceleration via General Programming on stock GPUs (GPGPU), I’ve sped up my algorithms by more than tenfold. This article shows how you can achieve these results too! Programmers have been interested in leveraging the highly parallel processing power of video cards to speed up applications that are not graphic in nature for a […]
Qiwei Jin, David B. Thomas, Wayne Luk
This paper explores the application of reconfigurable hardware and graphics processing units (GPUs) to the acceleration of financial computation using the finite difference (FD) method. A parallel pipelined architecture has been developed to support concurrent valuation of independent options with high pricing throughput. Our FPGA implementation running at 106 MHz on an xc4vlx160 device demonstrates […]
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Zachary Pezzementi, Sandrine Voros, Gregory D. Hager
We describe a general methodology for tracking 3-dimensional objects in monocular and stereo video that makes use of GPU-accelerated filtering and rendering in combination with machine learning techniques. The method operates on targets consisting of kinematic chains with known geometry. The tracked target is divided into one or more areas of consistent appearance. The appearance […]
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Xiangkun Zhao, Fengxia Li, Yufeng Chen, Shouyi Zhan
A new real-time point-based rendering method of large outdoor scenes is presented. Based on our interactive subdivide method, polygonal trees and other vegetation were converted to point-based models, and then different level of details of trees and other vegetation were created using hierarchical clustering. Different level of details of terrain were created using diamond tree […]
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Bernardete Ribeiro, Noel Lopes, Catarina Silva
In recent years the the potential and programmability of Graphics Processing Units (GPU) has raised a note-worthy interest in the research community for applications that demand high-computational power. In particular, in financial applications containing thousands of high-dimensional samples, machine learning techniques such as neural networks are often used. One of their main limitations is that […]
Anson H.T. Tse, David B. Thomas, Wayne Luk
Quadrature based methods for numerical integration provide a means of quickly and accurately pricing financial products such as options. These methods can be applied to multi-dimensional products, such as options on multiple underlying assets, but suffer from an exponential increase in computational complexity as the dimension increases. This paper examines the theoretical complexity of quadrature […]
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Anson H. T. Tse, David Thomas, Wayne Luk
This paper presents a novel parallel architecture for accelerating quadrature methods used for pricing complex multi-dimensional options, such as discrete barrier, Bermudan and American options. We explore different designs of the quadrature evaluation core including optimized pipelined hardware designs in reconfigurable logic and a compute unified device architecture (CUDA)-based graphics processing unit (GPU) design. A […]
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Evdokimos I. Konstantinidis, Christos A. Frantzidis, Lazaros Tzimkas, Costas Pappas, Panagiotis D. Bamidis
This paper investigates the benefits derived by adopting the use of Graphics Processing Unit (GPU) parallel programming in the field of biomedical signal processing. The differences in execution time when computing the Correlation Dimension (CD) of multivariate neurophysiological recordings and the Skin Conductance Level (SCL) are reported by comparing several common programming environments. Moreover, as […]
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Andreas Klockner, Nicolas Pinto, Yunsup Lee, Bryan Catanzaro, Paul Ivanov, Ahmed Fasih
High-performance computing has recently seen a surge of interest in heterogeneous systems, with an emphasis on modern Graphics Processing Units (GPUs). These devices offer tremendous potential for performance and efficiency in important large-scale applications of computational science. However, exploiting this potential can be challenging, as one must adapt to the specialized and rapidly evolving computing […]
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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
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  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
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  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
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  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

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