4155

Posts

May, 19

GPU implementation of 3D object selection by conic volume techniques in virtual environments

In this paper we present a GPU implementation to accurately select 3D objects based on their silhouettes by a pointing device with six degrees of freedom (6DOF) in a virtual environment (VE). We adapt a 2D picking metaphor to 3D selection in VE’s by changing the projection and view matrices according to the position and […]
May, 19

Improved Poisson Matting for a Real Time Tele-presence System Using GPU

In this paper, an improved Poisson matting method is proposed to segment participants in real-time at a tele-presence session from their background. In order to improve the matting process, we introduce the concept of color distance and extend the standard Poisson matting using patch matching. The idea of patch based matching algorithm, which is widely […]
May, 19

GPU-PRISM: An Extension of PRISM for General Purpose Graphics Processing Units

We present an extension of the model checker PRISM for (general purpose) graphics processing units (GPUs). The extension is based on parallel algorithms for probabilistic model checking which are tuned for GPUs. In particular, we parallelize the parts of the algorithms that boil down to linear algebraic operations, like solving systems of linear equations and […]
May, 19

A GPU-based maximal frequent itemsets mining algorithm over stream

Maximal frequent itemsets are one of several condensed representations of frequent itemsets, which store most of the information contained in frequent itemsets using less space, thus being more suitable for stream mining. This paper considers a problem that to the best of our knowledge has not been addressed, namely, how to use GPU to mine […]
May, 19

An efficient out-of-core volume rendering method based on ray casting and GPU acceleration

Volume rendering techniques have been used widely for high quality visualization of 3D data sets, especially in the fields of biomedical image processing. However, when rendering very large (out-of-core) volume data sets, the conventional in-core volume rendering algorithms cannot run efficiently due to the impossibility of fitting the entire input data in the internal memory […]
May, 19

Practical considerations for GPU-accelerated CT

The introduction of programmability into commodity graphics hardware (GPUs) has enabled their use much beyond their native domain of computer graphics, in many areas of high performance computing. We have shown in previous work that many types of CT algorithms, both iterative and non-iterative, can also greatly benefit from the high degree of SIMD (same […]
May, 19

High-throughput stream categorization and intrusion detection on GPU

We present a design and implementation of a high-throughput deep packet inspection performing both stream categorization and intrusion detection on GPU platform using CUDA. This implementation is capable of matching 64 ethernet packet streams against 25 given regular expressions at 524 Mb/s rate on a computer system with GeForce GTX 295 graphic card.
May, 19

GPU acceleration of a fully 3D Iterative Reconstruction Software for PET using CUDA

A CUDA implementation of the existing software FIRST (Fast Iterative Reconstruction Software for (PET) Tomography) is presented. This implementation uses consumer graphics processing units (GPUs) to accelerate the compute-intensive parts of the reconstruction: forward and backward projection. FIRST was originally developed in FORTRAN, and it has been migrated to C language to be used with […]
May, 19

Astrophysical Particle Simulations with Custom GPU Clusters

We present our new parallel GPU clusters in Beijing and Heidelberg and demonstrate the nearly optimal speedup and performance for parallel direct astrophysical N-body simulations with up to six million bodies. We reach about 1/3 of the peak performance for a real application code. The clusters are used to simulate dense star clusters with many […]
May, 18

Ray Casting of Trimmed NURBS Surfaces on the GPU

We propose a conceptual extension of the standard triangle-based graphics pipeline by an additional intersection stage. The corresponding intersection program performs ray-object intersection tests for each fragment of an object’s bounding volume. The resulting hit fragments are transferred to the fragment shading stage for computing the illumination and performing further fragment operations. Our approach combines […]
May, 18

Graphics processor unit (GPU) acceleration of finite-difference time-domain (FDTD) algorithm

The finite-difference time-domain (FDTD) algorithm has become a tool of choice in many areas of RF and microwave engineering and optics. However, FDTD runs too slow for some simulations to be practical, even when carried out on supercomputers. The development of dedicated hardware to accelerate FDTD computations has been investigated. In this paper, we demonstrate […]
May, 18

Fast 2D-3D registration using GPU-based preprocessing

This paper describes the fast point-based 2-D/3-D registration that will increase the registration speed of intraoperative two-dimensional (2-D) fluoroscopy and preoperative three-dimensional (3-D) CT images using GPU (graphics processing unit)-based DRR’s preprocessing. Rigid 2-D/3-D registration of 2-D fluoroscopy images with 3-D CT images can be used for image-guided surgery or intraoperative navigation. X-ray fluoroscopy images […]
Page 574 of 793« First...102030...572573574575576...580590600...Last »

* * *

* * *

Like us on Facebook

HGPU group

230 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1425 peoples are following HGPU @twitter

* * *

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: