high performance computing on graphics processing units: hgpu.org

We present a real-time 3D face identification system using a consumer level depth camera (PrimeSensor). Our system takes a noisy sequence as input and produces reliable identification. Instead of registering a probe to all instances in the database, we propose to only register it with several intermediate references, which considerably reduces processing, while preserving the […]

High performance of modern Graphics Processing Units may be utilized not only for graphics related application but also for general computing. This computing power has been utilized in new variants of many algorithms from almost every computer science domain. Unfortunately, while other application domains strongly benefit from utilizing the GPUs, databases related applications seem not […]

Weather forecasts for long periods of time has emerged as increasingly important. The global concern with the consequences of climate changes has stimulated researches to determine the climate in coming decades. At the same time the steps needed to better defining the modeling and the simulation of climate/weather is far of the desired accuracy. Upscaling […]

In order to study how to use GPU in real-time signal processing system, we implement common beam forming arithmetic using it. In a GTX285 GPU, computing speed is 170-450 times faster than AD TigerSharc201. This shows good prospects of GPU.

In networked signal processing systems, dataflow graphs can be used to describe the processing on individual network nodes. However, to analyze the correctness and performance of these systems, designers must understand the interactions across these individual "node-level" dataflow graphs — as they communicate across the network – in addition to the characteristics of the individual […]

The representation of an image as a flow network has gained an increased interest in research for the 2D and 3D segmentation field. One of these segmentation approaches consists in applying a minimum cut algorithm to separate the image in background and foreground. The most remarkable algorithm to segment a 2D image using this approach […]

We design and implement a parallel algebraic multigrid method for isotropic graph Laplacian problems on multicore Graphical Processing Units (GPUs). The proposed AMG method is based on the aggregation framework. The setup phase of the algorithm uses a parallel maximal independent set algorithm in forming aggregates and the resulting coarse level hierarchy is then used […]

Deep Neural Networks now excel at image classification, detection and segmentation. When used to scan images by means of a sliding window, however, their high computational complexity can bring even the most powerful hardware to its knees. We show how dynamic programming can speedup the process by orders of magnitude, even when max-pooling layers are […]

In oil and gas exploration, the seismic data can provide the information of the earth’s subsurface structure and detect where oil can be found and recovered. To get a geological model of the earth, the complex iterative processing is being done. So, the need for computing power increases with the oil and gas exploration and […]

Network traffic processing is necessary in order to develop active components in the infrastructure of the network, such as routers, or passive applications, such as network intrusion detection systems. However, in today’s high-speed network links this has become a very challenging task in terms of computational resources. Custom hardware appliances that can handle high packet […]

Wide baseline matching is the state of the art for object recognition and image registration problems in computer vision. Robust feature descriptors can give vast improvements in the quality and speed of subsequent steps, but intensive computation is still required. With the release of general purpose parallel computing interfaces, opportunities for increases in performance arise. […]

There is a huge computational potential in unconventional computing paradigms such as reaction-diffusion chemistry. The main problem with unconventional systems is the inherent difficulty in programming them. By extending the computational application of reaction-diffusion systems, this problem may be alleviated, as every new application allows for another method of approaching problems. With the central nervous […]