high performance computing on graphics processing units: hgpu.org

Feature tracking is one of fundamental steps in many computer vision algorithms and the KLT (Kanade-Lucas-Tomasi) method has been successfully used for optical flow estimation. There has been also much effort to implement KLT on GPUs to increase the speed with more features. Many implementations have chosen the translation model to describe a template motion […]

Feature tracking is one of the most fundamental tasks in computer vision, being used as a preliminary step to many high-level algorithms. In general, however, the number of features tracked (leading to more accurate high-level algorithms) must be balanced against the computational requirements of the feature tracking algorithm. To enable a large number of features […]

In the method of moments (MOM) analysis of electromagnetic phenomena, the LU decomposition is often an important and costly step in the solution process. In this reported work, the acceleration of LU decomposition using graphics processing units (GPUs) has been considered. Although existing GPU methods, such as those supplied by MAGMA, provide significant speedup over […]

We developed a complete GPU based data processing for cone-beam micro CT application which performs not only the reconstruction but also all the correction of the projection images on-the-fly. Test measurements were performed and processing times was compared on different hardware setups. The performance of the GPU together with our modified algorithm allow to process […]

Neuroblastoma is one of the most malignant childhood cancers affecting infants mostly. The current prognosis is based on microscopic examination of slides by expert pathologists, a process that is error-prone, time consuming and may lead to inter- and intra-reader variations. Therefore, we are developing a Computer Aided Prognosis (CAP) system which provides computerized image analysis […]

Range Cell Migration Correction (RCMC) is a key step in the imaging procedure of Synthetic Aperture Radar (SAR). The performance of RCMC affects the final SAR image quality greatly. Traditionally, RCMC is carried out via an interpolation operation on CPU, and is a time-consuming phase in the whole processing flow. In this paper, a novel […]

We introduce an inverse problem for the local volatility model in option pricing. We solve the problem using the Levenberg-Marquardt algorithm and use the notion of the Frechet derivative when calculating the Jacobian matrix. We analyze the existence of the Frechet derivative and its numerical computation. To reduce the computational time of the inverse problem, […]

In this paper, we present a novel 3D model alignment method by analyzing the voxels of 3D meshes and a visual similarity based 3D model matching and retrieving method using active tabu search. Firstly, each 3D model is voxelized and applied voxels based PCA transformation, then it is represented by six depth images which are […]

Multi-core platform enters the territory of high performance computing (HPC). Moreover, the NVIDA GT200 has 240 cores and performs thousands upon thousands of threads simultaneously. The role of the Graphics Processing Units (GPU)accelerator has become more and more important for scientific computing and computational fluid dynamic (CFD) to obtain result quickly and efficiently. In this […]

The Parallel finite difference time domain (FDTD) algorithm is an important method to 1 enhance the speed in multiple data FDTD operation. The improvement of graphics processing unit (GPU) performance, especially the emergence of Computer Unit Device Architecture (CUDA), offers parallel FDTD method an efficient and simple solution. First of all, this paper explains parallel […]

The research on complex Brain Networks plays a vital role in understanding the connectivity patterns of the human brain and disease-related alterations. Recent studies have suggested a noninvasive way to model and analyze human brain networks by using multi-modal imaging and graph theoretical approaches. Both the construction and analysis of the Brain Networks require tremendous […]

New elastographic techniques such as poroelastography and viscoelasticity imaging aim at imaging the temporal mechanical behavior of tissues. These techniques usually involve the use of curve fitting methods being applied to noisy data to estimate new elastographic parameters. As of today, however, current elastographic implementations of poroelastography and viscoelasticity imaging methods are in general too […]