high performance computing on graphics processing units: hgpu.org

General-purpose computation on graphics processing units (GPGPU) has become a popular field of study. Due to its high computing capacity and relatively low price, GPU has been an ideal processing unit for many scientific applications, among which is N-body simulation. According to the published papers, a simple O(N^2) algorithm of N-body simulation has achieved some […]

General-purpose computing on graphics processing units (GPGPU) is a fast developing method of high performance computing (HPC). In some cases even a low-end video card can be several to dozens times faster than a modem CPU core. Seismic wave filed modeling is one of the problems of this kind. But in some modern methods of […]

Ant colony algorithm is an efficient intelligent algorithm to solve NP hard problem. This paper presents a parallel computing solution based on General Purpose GPU (GPGPU) to solve traveling salesman problem (TSP) with max-min ant system (MMAS). The experimental result shows it is more efficient than pure CPU computing.

The HIE(Hybrid Implicit-Explicit)-FDTD method is very useful for the simulation of computational domain with thin cells. This paper describes the HIE-FDTD method with GPGPU(General Purpose computing on Graphic Processing Unit) for massively parallel electromagnetic field simulation. First, the properties of the HIE-FDTD method are explained. Next, 3D HIE-FDTD method with CUDA is implemented. Finally, it […]

General Purpose computing on Graphical Processing Units (GPGPU) is a paradigm shift in computing that promises a dramatic increase in performance. But GPGPU also brings an unprecedented level of complexity in algorithmic design and software development. In this paper, we present an efficient parallel fault simulator, FSimGP2, that exploits the high degree of parallelism supported […]

To be held in conjunction with CSE 2011. The goal of this workshop is to provide a forum for researchers and practitioners to discuss and share their research and development experiences and outputs on the massively parallel GPU platforms, software development tools, optimization techniques, parallel algorithm design, and all kinds of successful applications. We solicit […]

General-purpose computing on graphics processing units (GPGPU) is popular computing technology to utilize in various fields. In the paper, we parallelize cryptographical hash processing of a password cracking tool, John the Ripper, by utilizing CUDA on GPGPU. We also evaluate our work to compare the processing time of hash processing parallelized by GPU with that […]

Analysis of neural signals (such as EEG) has long been a hot topic in neuroscience community due to neural signals’ nonlinear and non-stationary features. Recent advances of experimental methods and neuroscience research have made neural signals constantly massive and analysis of these signals highly compute-intensive. Analysis of neural signals has been routinely performed upon CPU-based […]

Ensemble empirical-mode decomposition (EEMD) is a novel adaptive time-frequency analysis method, which is particularly suitable for extracting useful information from noisy nonlinear or nonstationary data. Unfortunately, since the EEMD is highly compute-intensive, the method does not apply in real-time applications on top of commercial-off-the-shelf computers. Aiming at this problem, a parallelized EEMD method has been […]

The GPUs (Graphics Processing Units) have evolved into extremely powerful and flexible processors, allowing its usage for processing different data. This advantage can be used in game development to optimize the game loop. Most GPGPU works deals only with some steps of the game loop, allowing to the CPU to process most of the game […]

A nonlinear filter bank named as an ∈-filter bank is implemented for real-time processing of video in order to make the skin in human faces look beautified. General-purpose computing on graphics processing units (GPGPU) is utilized for this real-time implementation. GPGPU has quite high computational power, and the facial beautification system using the ∈-filter bank […]

There is currently a strong push in the research community to develop biological scale implementations of neuron based vision models. Systems at this scale are computationally demanding and have generally utilized more accurate neuron models, such as the Izhikevich and Hodgkin- Huxley models, in favor of the integrate and fire model. This paper examines the […]