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Posts

Jun, 7

Implementation and Experimental Evaluation of a CUDA Core under Single Event Effects

Graphic Processing Units have become popular in a broad range of applications due to their high computational power and low prices. Among the applications are the safety critical ones, where fault tolerance is mandatory. This paper presents the implementation of a CUDA core, the main processing core of a GPU and its evaluation under Single […]
Jun, 7

Parallelization of Synthetic Aperture Radar (SAR) Imaging Algorithms on GPU

The increased demand for higher resolution and detailed SAR imaging builds up a pressure on the processing power of the existing systems for real time or near real time processing. Exploitation of GPU processing power could suffice the increasing demands in processing. The processing of initial SAR systems was based on the principles of Fourier […]
Jun, 7

Performance Evaluation of Discrete Wavelet Transform Based on Image Compression Technique on Both CPU and GPU

This paper investigates the use of the Compute Unified Device Architecture (CUDA) programming model to implement Discrete Wavelet Transform (DWT) based algorithm for efficient image compression. The PSNR (Peak Signal to Noise Ratio) is used to evaluate image reconstruction quality in this paper. The results are presented and discussed.
Jun, 7

Brain perfusion imaging: performance and accuracy

Brain perfusion weighted images acquired using dynamic contrast studies have an important clinical role in acute stroke diagnosis and treatment decisions. The purpose of my PhD research is to develop novel methodologies for improving the efficiency and quality of brain perfusion-imaging analysis so that clinical decisions can be made more accurately and in a shorter […]
Jun, 6

Software-Based Hardening Strategies for Neutron Sensitive FFT Algorithms on GPUs

In this paper we assess the neutron sensitivity of Graphics Processing Units (GPUs) when executing a Fast Fourier Transform (FFT) algorithm, and propose specific software-based hardening strategies to reduce its failure rate. Our research is motivated by experimental results with an unhardened FFT that demonstrate a majority of multiple errors in the output in the […]
Jun, 6

An Improved Parallel Algorithm using GPU for Siting Observers on Terrain

This paper presents an efficient method to determine a set of observers (that is, where to site them) such that a given percentage of a terrain is visually covered. Our method extends the method proposed in (Franklin, 2002) including a local search heuristic efficiently implemented using dynamic programming and GPU parallel programming. This local search […]
Jun, 6

Parallel centerline extraction on the GPU

Centerline extraction is important in a variety of visualization applications including shape analysis, geometry processing, and virtual endoscopy. Centerlines allow accurate measurements of length along winding tubular structures, assist automatic virtual navigation, and provide a path-planning system to control the movement and orientation of a virtual camera. However, efficiently computing centerlines with the desired accuracy […]
Jun, 6

High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System

We have developed a graphics processor unit (GPU-) based high-speed fully 3D system for diffuse optical tomography (DOT). The reduction in execution time of 3D DOT algorithm, a severely ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden approach for updating the Jacobian matrix and thereby updating the […]
Jun, 6

GPGPU opportunities for the LHCb trigger

This note describes arguments to study the use general purpose graphic processing units to improve the performance of the LHCb trigger, presents the current developments in the integration into the Gaudi framework and the implementation of algorithms and points towards possible R and D directions.
Jun, 5

Performance models for CPU-GPU data transfers

Many GPU applications perform data transfers to and from GPU memory at regular intervals. For example because the data does not fit into GPU memory or because of inter- node communication at the end of each time step. Overlapping GPU computation with CPU-GPU communication can reduce the costs of moving data. Several different techniques exist […]
Jun, 5

Real-time Model-based Articulated Object Pose Detection and Tracking with Variable Rigidity Constraints

We introduce a real-time system for recognizing and tracking the position and orientation of a large number of complex real-world objects, together with an articulated robotic manipulator operating upon them. The proposed system is fast, accurate and reliable and yet does not require precise camera calibration. The key to this high level of performance is […]
Jun, 5

GPU Accelerated Nature Inspired Methods for Modelling Large Scale Bi-Directional Pedestrian Movement

Pedestrian movement, although ubiquitous and well-studied, is still not that well under-stood due to the complicating nature of the embedded social dynamics. Interest among researchers in simulating the nature of pedestrian movement and interactions has grown significantly in part due to increased computational and visualization capabilities afforded by high power computing. Different approaches have been […]
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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

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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