high performance computing on graphics processing units: hgpu.org

This paper proposes a GPU-accelerated patch search engine that efficiently Alls the unknown regions of an image caused by replacement or removal of part of the foreground. Previous approaches, such as inpainting and texture synthesis, are either fast, but not applicable for small-scale regions, or slow, but fills large regions with good quality. The algorithm […]

In this paper we present a method to compute and visualize volumetric white matter connectivity in diffusion tensor magnetic resonance imaging (DT-MRI) using a Hamilton-Jacobi (H-J) solver on the GPU (graphics processing unit). Paths through the volume are assigned costs that are lower if they are consistent with the preferred diffusion directions. The proposed method […]

Sort-last parallel rendering is an efficient technique to visualize huge datasets on COTS clusters. The dataset is subdivided and distributed across the cluster nodes. For every frame, each node renders a full resolution image of its data using its local GPU, and the images are composited together using a parallel image compositing algorithm. In this […]

Graphic Processing Units (GPUs) is a low-cost parallel programmable co-processor that can deliver extremely high computation throughput and is well suited for large-scale system design and simulation. In this paper, we utilize the parallel processing power of GPU to accelerate the simulation of MIMO systems. In our work, flat fading channel is considered and an […]

A Coarse Grain Reconfigurable Architecture (CGRA) tailored for accelerating bio-informatics algorithms is proposed. The key innovation is a light weight bio-informatics processor that can be reconfigured to perform different Add Compare and Select operations of the popular sequencing algorithms. A programmable and scalable architectural platform instantiates an array of such processing elements and allows arbitrary […]

Random Walks has less interaction, better accuracy and higher computing independency. We introduce local intensity entropy to modify the weight function in Random Walks, in order to consider not only the intensity change of adjacent pixels, but also the statistical features of regions. Then we put forward a real-time interactive object extraction system for high […]

This paper presents the latest research and developments in Modular Technology. That is, the optimized repetition of the same geometry or module, for the generation of large virtual environments for the simulators that are designed by CITEF. The current trend is on redirecting the maximum possible share of graphical calculation to the GPU to lighten […]

We present a real-time multisensor architecture for combined laser scanner and infra-red video-based pedestrian detection and tracking used within a road side unit for intersection assistance. In order to achieve outmost classification performance we propose a cascaded classifier using laser scanner hypothesis generation and histogram of oriented gradients (HOG) descriptors for video-based classification together with […]

Central Force Optimization (CFO) is a powerful new metaheuristic algorithm that has been demonstrated to be competitive with other metaheuristic algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Group Search Optimization (GSO). While CFO often shows superiority in terms of functional evaluations and solution quality, the algorithm is complex and often requires […]

Medical imaging techniques such as X-ray, Ultrasound, CT and MRI scan are widely used for diagnosis. The 2D medical images from these scans are difficult to interpret because they can only show cross section views of a human body. Interpreting these images requires experts or trained professionals. Reconstructing 2D images into 3D models can help […]

The visualization and analysis of AMR-based simulations is integral to the process of obtaining new insight in scientific research. We present a new method for performing query-driven visualization and analysis on AMR data, with specific emphasis on time-varying AMR data. Our work introduces a new method that directly addresses the dynamic spatial and temporal properties […]

This paper presents a graphics processing unit (GPU) based method capable of accelerating cone-beam reconstruction of large volume data, which cannot be entirely stored in video memory. Our method accelerates the Feldkamp, Davis and Kress (FDK) algorithm in a multi-GPU environment. We present how the entire volume can be efficiently decomposed into small portions to […]