high performance computing on graphics processing units: hgpu.org

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 […]

We present real-time vascular visualization methods, which extend on illustrative rendering techniques to particularly accentuate spatial depth and to improve the perceptive separation of important vascular properties such as branching level and supply area. The resulting visualization can and has already been used for direct projection on a patient’s organ in the operation theater where […]

CAMShift is a well-established and fundamental algorithm for kernel-based visual object tracking. While it performs well with objects that have a simple and constant appearance, it is not robust in more complex cases. As it solely relies on back projected probabilities it can fail in cases when the object’s appearance changes (e.g., due to object […]

This work explores how the graphics processing unit (GPU) pipeline model can influence future multi-core architectures which include reconfigurable logic cores. The design challenges of implementing five algorithms on two field programmable gate arrays (FPGAs) and two GPUs are explained and performance results contrasted. Explored algorithm features include data dependence, flexible data reuse patterns and […]

With higher bandwidth requirements and more complex protocols, software defined radio (SDR) has ever growing computational demands. SDR applications have different levels of parallelism that can be exploited on multicore platforms, but design and programming difficulties have inhibited the adoption of specialized multicore platforms like graphics processors (GPUs). In this work we propose a new […]