high performance computing on graphics processing units: hgpu.org

As the traffic of the Internet increases and diversifies, the needs for a fast flexible router have made researchers to work on software routers. The existing software router systems may utilize the cluster structure of multiple machines or GPU systems. Especially, Packet Shader, which uses GPU to exploit GPU’s extensive parallelism, shows higher performance compared […]

In light of its powerful computing capacity and high energy efficiency, GPU (graphics processing unit) has become a focus in the research field of HPC (High Performance Computing). CPU-GPU heterogeneous parallel systems have become a new development trend of super-computer. However, the inherent unreliability of the GPU hardware deteriorates the reliability of super-computer. We have […]

For the virus signature matching time of traditional the eigenvalue is too long, which can’t meet the need of the information security, a method of fast virus signature matching on the GPU is compelled. The system uses the GPU as a fast filter to quickly identify possible virus signatures for thousands of data objects in […]

General purpose computing on graphics processing units (GPUs) has been previously shown to speed up computationally intensive data processing and image reconstruction algorithms for computed tomography (CT), magnetic resonance (MR), and ultrasound images. Although some algorithms in ultrasound have been converted to GPU processing, many investigative ultrasound research systems still use serial processing on a […]

In recent years, heterogeneous parallel system have become a focus research area in high performance computing field. Generally, in a heterogeneous parallel system, CPU provides the basic computing environment and special purpose accelerator (GPU in this paper) provides high computing performance. However, the overall performance of the system is prone to be limited by the […]

With fast development of transistor technology, Graphic Processing Unit(GPU) is increasingly used in the non-graphics applications, and major GPU hardware vendors have introduced software stacks for their own GPUs, such as Brook+ for AMD GPU. Compared with the traditional parallel systems, heterogeneous systems integerating stream-based multi-threaded GPUs provide higher parallel computing capabilities with lower cost. […]

Kernel methods such as kernel principal component analysis and support vector machines have become powerful tools for pattern recognition and computer vision. Unfortunately the high computational cost of kernel methods is a limiting factor for real-time classification tasks when running on the CPU of a standard PC. Over the last few years, commodity Graphics Processing […]

SAFT techniques are based on the sequential activation, in emission and reception, of the array elements and the post-processing of all the received signals to compose the image. Thus, the image generation can be divided into two stages: (1) the excitation and acquisition stage, where the signals received by each element or group of elements […]

Volume Rendering methods employing the GPU capabilities offer high performance on off-the-shelf hardware. In this article, we discuss the various bottlenecks found in the graphics hardware when performing GPU-based Volume Rendering. The specific properties of each bottleneck and the trade-offs between them are described. Further we present a novel strategy to balance the load on […]

In this paper we investigate the use of GPUs as digital beamformers. We specify a parallel implementation of a beamformer in time and frequency domain and measure its performance. We also give examples of the processing limits of NVIDIA Geforce 8800 GPU with respect to application parameters: number of sensors, sampling frequency, bandwidth, and number […]

By organizing the control mesh of subdivision in texture memory so that irregularities occur strictly inside independently refinable fragment meshes, all major features of subdivision algorithms can be realized in the framework of highly parallel stream processing. Our implementation of Catmull-Clark subdivision as a GPU kernel in programmable graphics hardware can model features like semi-smooth […]

This workshop will cover advances and innovations in graphic processor unit (GPU) capabilities and functionality into nontraditional, general-purpose computing as an adjunct vector/matrix processor. Examples include game physics, image processing, scientific computing, sorting and database query processing, to name a few.This workshop consists of invited speakers and poster presenters who provide insights into GP2 practice […]