high performance computing on graphics processing units: hgpu.org

Motion blur and rolling shutter deformations both inhibit visual motion registration, whether it be due to a moving sensor or a moving target. Whilst both deformations exist simultaneously, no models have been proposed to handle them together. Furthermore, neither deformation has been considered previously in the context of monocular full-image 6 degrees of freedom registration […]

The analysis of complex nonlinear systems is often carried out using simpler piecewise linear representations of them. We propose a principled and practical technique to linearize and evaluate arbitrary continuous nonlinear functions using polygonal (continuous piecewise linear) models under the L1 norm. A thorough error analysis is developed to guide an optimal design of two […]

In this paper, we describe a novel technique to optimize longest common subsequence (LCS) algorithm for one-to-many matching problem on GPUs by transforming the computation into bit-wise operations and a post-processing step. The former can be highly optimized and achieves more than a trillion operations (cell updates) per second (CUPS)-a first for LCS algorithms. The […]

Ultra-High definition video streaming has been explored in recent years. Most recently the possibility of 4kUHD video streaming over wireless 802.11n was presented, using pre-encoded video. Live encoding for streaming using x264 has proven to be very slow. The use of parallel encoding has been explored to speed up the process using CUDA. However there […]

High data rate waveforms for software defined radios (SDR) have to cope with frequency selective fading due to the mobile use in different harsh transmission environments. The received signal needs to be equalized in order to restore the transmitted information. Turbo equalization is a promising approach to deal with the inter-symbol interference occurring at the […]

The paper addresses the problem of pose-invariant recognition of faces via an MRF matching model. Unlike previous costly matching approaches, the proposed algorithm employs effective techniques to reduce the MRF inference time. To this end, processing is done in a parallel fashion on a GPU employing a dual decomposition framework. The optimisation is further accelerated […]

The exponential growth of the world’s technological industry has an important impact on our lives; we are witnessing an expansion in computer power combined with a noticeable development of digital camera capabilities. To keep up with the requirements of the digitalized world, the focus has been set on the computer vision field. One of the […]

Although trivial Background Subtraction algorithms which are median- based, Gaussian-based and Kernel density-based approaches can perform quite fast, but they are not roust enough to be used in various computer vision problems. Some complex algorithms usually give better results, but are too slow to be applied to real-time systems. Here, we examine the GPU architecture […]

Nowadays, the paradigm of parallel computing is changing. CUDA is now a popular programming model for general purpose computations on GPUs and a great number of applications were ported to CUDA obtaining speedups of orders of magnitude comparing to optimized CPU implementations. Hybrid approaches that combine the message passing model with the shared memory model […]

In this paper, we present an algorithm and provide design improvements needed to port the serial Lempel-Ziv-Storer-Szymanski (LZSS), lossless data compression algorithm, to a parallelized version suitable for general purpose graphic processor units (GPGPU), specifically for NVIDIA’s CUDA Framework. The two main stages of the algorithm, substring matching and encoding, are studied in detail to […]

This paper presents a GPU implementation of a partial demosaicing scheme that is specially designed for stereo matching of CFA image. This method consists of three main techniques keys: the adapted matching cost for CFA image, the estimated Second color component based on Hamilton’s estimate method and a robust cost aggregation window. Experiments are carried […]

Cosmic dust particles effectively attenuate starlight. Their absorption of starlight produces emission spectra from the near- to far-infrared, which depends on the sizes and properties of the dust grains, and spectrum of the heating radiation field. The near- to mid-infrared is dominated by the emissions by very small grains. Modeling the absorption of starlight by […]