Posts

Dec, 15

Hybrid of genetic algorithm and local search to solve MAX-SAT problem using nVidia CUDA framework

General Purpose computing over Graphical Processing Units (GPGPUs) is a huge shift of paradigm in parallel computing that promises a dramatic increase in performance. But GPGPUs also bring an unprecedented level of complexity in algorithmic design and software development. In this paper we describe the challenges and design choices involved in parallelizing a hybrid of […]
Dec, 15

Genetic programming on graphics processing units

The availability of low cost powerful parallel graphics cards has stimulated the port of Genetic Programming (GP) on Graphics Processing Units (GPUs). Our work focuses on the possibilities offered by Nvidia G80 GPUs when programmed in the CUDA language. In a first work we have showed that this setup allows to develop fine grain parallelization […]
Dec, 15

Real-time saliency-aware video abstraction

Existing real-time automatic video abstraction systems rely on local contrast only for identifying perceptually important information and abstract imagery by reducing contrast in low-contrast regions while artificially increasing contrast in higher contrast regions. These methods, however, may fail to accentuate an object against its background for the images with objects of low contrast over background […]
Dec, 15

In vivo interactive visualization of four-dimensional blood flow patterns

In this paper we give an overview over a series of experiments to visualize and measure flow fields in the human vascular system with respect to their diagnostic capabilities. The experiments utilize a selection of GPU-based sparse and dense flow visualization algorithms to show the diagnostic opportunities for volumetric cardiovascular phase contrast magnetic resonance imaging […]
Dec, 15

Creation and control of rain in virtual environments

Realistic outdoor scenarios often include rain and other atmospheric phenomena, which are difficult to simulate in real time. In the field of real-time applications, a number of solutions have been proposed which offer realistic but costly rain systems. Our proposal consists in developing a solution to facilitate the creation and control of rain scenes and […]
Dec, 15

Filtered Blending: A new, minimal Reconstruction Filter for Ghosting-Free Projective Texturing with Multiple Images

Whenever approximate 3D geometry is projectively texture-mapped from different directions simultaneously, annoyingly visible aliasing artifacts are the result. To prevent such ghosting in projective texturing and image-based rendering, we propose a new GPU-based rendering strategy and a new, viewdependent definition of ghosting. The algorithm is applicable to any kind of image-based rendering method, or general […]
Dec, 15

Real-time multi-band synthesis of ocean water with new iterative up-sampling technique

Adapting natural phenomena rendering for real-time applications has become a common practice in computer graphics. We propose a GPU-based multi-band method for optimized synthesis of “far from coast” ocean waves using an empirical Fourier domain model. Instead of performing two independent syntheses for low- and high-band frequencies of ocean waves, we perform only low-band synthesis […]
Dec, 15

Acceleration of cardiac tissue simulation with graphic processing units

In this technical note we show the promise of using graphic processing units (GPUs) to accelerate simulations of electrical wave propagation in cardiac tissue, one of the more demanding computational problems in cardiology. We have found that the computational speed of two-dimensional (2D) tissue simulations with a single commercially available GPU is about 30 times […]
Dec, 15

Optimizing Monte Carlo radiosity on graphics hardware

The radiosity method is usually employed for the rendering of highly realistic synthetic images. In this paper we present an implementation of the Monte Carlo radiosity algorithm on the GPU using CUDA. Our proposal is based on the partition of the scene into sub-scenes to be processed in parallel to exploit the graphics card structure. […]
Dec, 15

Scalable and highly parallel implementation of Smith-Waterman on graphics processing unit using CUDA

Program development environments have enabled graphics processing units (GPUs) to become an attractive high performance computing platform for the scientific community. A commonly posed problem in computational biology is protein database searching for functional similarities. The most accurate algorithm for sequence alignments is Smith-Waterman (SW). However, due to its computational complexity and rapidly increasing database […]
Dec, 15

OpenMP to GPGPU: a compiler framework for automatic translation and optimization

GPGPUs have recently emerged as powerful vehicles for general-purpose high-performance computing. Although a new Compute Unified Device Architecture (CUDA) programming model from NVIDIA offers improved programmability for general computing, programming GPGPUs is still complex and error-prone. This paper presents a compiler framework for automatic source-to-source translation of standard OpenMP applications into CUDA-based GPGPU applications. The […]
Dec, 15

Compiler support for general-purpose computation on GPUs

In recent years, the GPU (graphics processing unit) has evolved into an extremely powerful and flexible processor, with it now representing an attractive platform for general-purpose computation. Moreover, changes to the design and programmability of GPUs provide the opportunity to perform general-purpose computation on a GPU (GPGPU). Even though many programming languages, software tools, and […]
Page 619 of 705« First...102030...617618619620621...630640650...Last »

* * *

* * *

* * *

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 11.4
  • SDK: AMD APP SDK 2.8
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 5.0.35, AMD APP SDK 2.8

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 © 2010-2014 hgpu.org

All rights belong to the respective authors

Contact us:

contact@hgpu.org