high performance computing on graphics processing units: hgpu.org

Although trivial background subtraction algorithms (such as temporal averaging) can execute quite quickly, they do not give useful results in most situations. More complex algorithms usually provide better results, but are typically too slow for widespread use. Here, we examine the architecture of the GPU and describe how a multimodal background subtraction algorithm can be […]

We present a graphics hardware implementation of the tangent-plane algorithm for computing the kth-order Voronoi diagram of a set of point sites in image space. Correct and efficient implementation of this algorithm using graphics hardware is possible only with the use of an appropriate shader program on the GPU. This is achieved by rendering in […]

The Fourier volume rendering technique operates in the frequency domain and creates line integral projections of a 3D scalar field. These projections can be efficiently generated in O(N^2 log N) by utilizing the Fourier Slice-Projection theorem. However, until now, the mathematical difficulty of the Fast Fourier Transform prevented acceleration by graphics hardware and therefore limited […]

The GPUs pack high computation power and a restricted architecture into easily available hardware today. They are now used as computation co-processors and come with programming models that treat them as standard parallel architectures. We explore the problem of realtime ray casting of large deformable models (over a million triangles) on large displays (a million […]

The computational power and memory bandwidth of graphics processing units (GPUs) have turned them into attractive platforms for general-purpose applications. In this paper, we exploit this power in the context of biomedical image processing by establishing a cooperative environment between the CPU and the GPU. We deal with phenotype and color analysis on a wide […]

We capitalize on recent advances in modern programmable graphics hardware, originally designed to support advanced local illumination models for shading, to instead perform two different kinds of global illumination models for light transport. We first use the new floating-point texture map formats to find matrix radiosity solutions for light transport in a diffuse environment, and […]

Graphics processing units (GPUs) are providing increasingly higher performance with programmable internal processors, namely vertex processors (VPs) and fragment processors (FPs). Such newly added capabilities motivate us to perform general-purpose computation on GPUs (GPGPU) beyond graphics applications. Although VPs and FPs are connected in a pipeline, many GPGPU implementations utilize only FPs as a computational […]

We propose a method for generating all possible rules of multi-dimension Boolean cellular automata (CA). Based on an original encoding method and the programming of graphical processor units (GPU), this method allows us to visualize the CA information flow in real-time so that emerging behaviors can be easily identified. Algorithms of first and von Neumann […]

This work presents an implementation of neocognitron neural network, using a high performance computing architecture based on GPU (graphics processing unit). Neocognitron is an artificial neural network, proposed by Fukushima and collaborators, constituted of several hierarchical stages of neuron layers, organized in two-dimensional matrices called cellular planes. For the high performance computation of face recognition […]

Linear algebra algorithms are fundamental to many computing applications. Modern GPUs are suited for many general purpose processing tasks and have emerged as inexpensive high performance co-processors due to their tremendous computing power. In this paper, we present the implementation of singular value decomposition (SVD) of a dense matrix on GPU using the CUDA programming […]

In this paper a novel implementation of the saliency map model on a multi-GPU platform using CUDA technology is presented. The saliency map model is a well-known computational model for bottom-up attention selection and serves as a basis of many attention control strategies of cognitive vision systems. A real-time implementation is the prerequisite of an […]

We are currently faced with the situation where applications have increasing computational demands and there is a wide selection of parallel processor systems. In this paper we focus on exploiting fine-grain parallelism for a demanding bioinformatics application – MrBayes – and its phylogenetic likelihood functions (PLF) using different architectures. Our experiments compare side-by-side the scalability […]