high performance computing on graphics processing units: hgpu.org

With the ever increasing demand for high quality 3D image processing on markets such as cinema and gaming, graphics processing units (GPUs) capabilities have shown tremendous advances. Although GPU-based cluster computing, which uses GPUs as the processing units, is one of the most promising high performance parallel computing platforms, currently there is no programming environment, […]

Using GPU for general computing has become an important research direction in high performance computing technology. However, this is not a lossless optimization method. Due to the impact of device initialization cost, data transmission delay, specific characteristics of programs, and other factors, the general computing on GPU may not always achieve the desired speedup, and […]

Most modern computers or game consoles are equipped with powerful yet cost-effective graphics processing units (GPUs) to accelerate graphics operations. Though the graphics engines in these GPUs are specially designed for graphics operations, can we harness their computing power for more general nongraphics operations? The answer is positive. In this paper, we present our study […]

The Graphics Processing Unit (GPU) is an asymmetric, heterogeneous multi-core architecture that can be used for high performance parallel computing applications. However, a significant level of interest has been focused on algorithms for solving regular problems, as these applications typically map well to the GPU. Irregular applications, which rely on pointer or graph-based data structures, […]

In order to solve the compute-intensive character of image processing, based on advantages of GPU parallel operation, parallel acceleration processing technique is proposed for image. First, efficient architecture of GPU is introduced that improves computational efficiency, comparing with CPU. Then, Sobel edge detector and homomorphic filtering, two representative image processing algorithms, are embedded into GPU […]

This paper reports on our experience with data structure design for systems having both multiple CPU cores and a programmable graphics card. We integrate our data structures into the game-like application OpenSteerDemo and compare our data structures on two pc-systems. One System has a relative fast single core CPU and slower GPU, whereas the other […]

Over the last decade, commodity graphics processors (GPUs) have evolved from fixed-function graphics units into powerful, programmable data-parallel processors. Today’s GPU is capable of sustaining computation rates substantially greater than today’s modern CPUs, with technology trends indicating a widening gap in the future. Researchers in the rapidly evolving field of GPU computing have demonstrated mappings […]

The architecture of the latest Graphic Processing Unit (GPU) consists of a number of uniform programmable units integrated on the same chip, which facilitate the general-purpose computing beyond the graphic processing. With the multiple programmable units executing in parallel, the latest GPU shows superior performance for many non-graphic applications. Furthermore, programmers can have a direct […]

One of the challenging advents in computer science in recent years was the fast evolution of parallel processors, specially the GPU – graphics processing unit. GPUs today play a major role in many computational environments, most notably those regarding real-time graphics applications, such as games. The digital game industry is one of the main driving […]

Benefit from the novel compute unified device architecture (CUDA) introduced by NVIDIA, graphics processing unit (GPU) turns out to be a promising solution for cryptography applications. In this paper we present an efficient implementation for MD5-RC4 encryption using NVIDIA GPU with novel CUDA programming framework. The MD5-RC4 encryption algorithm was implemented on NVIDIA GeForce 9800GTX […]

The massively parallel computing using graphical processing unit (GPU), which based on tens of thousands of parallel threats within hundreds of GPU’s streaming processors, has gained broad popularity and attracted researchers in a wide range of application areas from finance, computer aided engineering, computational fluid dynamics, game physics, numerics, science, medical imaging, life science, and […]

We discuss an implementation and optimization of GPU-accelerated Molecular Dynamics (MD) simulation of high-speed collision molecular model in NVIDIA CUDA language. A series of optimization methods are presented: spatial decomposition, use of shared memory and use of blockcell-link structure. These optimization methods effectively improve the performance by reducing data transfer time between CPU and GPU […]