high performance computing on graphics processing units: hgpu.org

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 […]

For solving large instances of the Travelling Salesman Problem (TSP), the use of a candidate set (or candidate list) is essential to limit the search space and reduce the overall execution time when using heuristic search methods such as Ant Colony Optimisation (ACO). Recent contributions have implemented ACO in parallel on the Graphics Processing Unit […]

In this paper we present three-dimensional numerical simulations of electromagnetic waves. The Maxwell equations are solved by the Discontinuous Galerkin (DG) method. For achieving high performance, we exploit two levels of parallelism. The coarse grain parallelism is managed through MPI and a classical domain decomposition. The fine grain parallelism is managed with OpenCL in order […]

This thesis deals with manipulating huge geometric data in the field of computer graphics. The proposed approach uses a data stream technique to allow processing gigantic datasets that by far exceed the size of the main memory. The amount of data is hierarchically reduced by clustering and replacing each cluster by a representative. The input […]

Graphics Processing Unit (GPU) programming techniques have been applied to a range of scientific and engineering computations. In computational electromagnetics, uses of the GPU technique have dramatically increased since the release of NVIDIA’s Compute Unified Device Architecture (CUDA), a powerful and simple-to-use programmer environment that renders GPU computing easy accessibility to developers not specialized in […]

Mathematicians and computational scientists are often limited in their ability to model complex phenomena by the time it takes to run simulations. This thesis will inform interested researchers on how the development of highly parallel computer graphics hardware and the compiler frameworks to exploit it are expanding the range of algorithms that can be explored […]

Neural networks and machine learning algorithms in general require a flexible environment where new algorithm prototypes and experiments can be set up as quickly as possible with best possible computational performance. To that end, we provide a new framework called Torch7, that is especially suited to achieve both of these competing goals. Torch7 is a […]

This book follows an example-driven, simplified, and practical approach to using OpenCL for general purpose GPU programming. If you are a beginner in parallel programming and would like to quickly accelerate your algorithms using OpenCL, this book is perfect for you! You will find the diverse topics and case studies in this book interesting and […]