high performance computing on graphics processing units: hgpu.org

Heterogeneous computing using FPGA accelerators is a promising approach to boost the performance of application programs within given power consumption. This paper focuses on optimizations targeting FPGA-based reconfigurable dataflow computing platform, and shows how they benefit an application. In order to evaluate them, we use the Himeno benchmark, which is a floating point computation kernel […]

Cortical modeling is an area of research seeking to model and simulate the cerebral cortex of the brain, which is of fundamental importance to conscious thought and action. Computational power is a major challenge in this field and the problem is inherently well-suited to SIMD architectures. This suggests the implementation of a general-purpose GPU framework […]

H.264/AVC is a recent video standard embraced by many multimedia applications. Because of its demanding encoding requirements, a high amount of computational effort is often needed in order to compress a video stream in real time. The intra-prediction and encoding are two of several modules included by H.264 that requires a high computational power. On […]

Interest point detection is an important low-level image processing technique with a wide range of applications. The point detectors have to be robust under affine, scale and photometric changes. There are many scale and affine invariant point detectors but they are not robust to high illumination changes. Many affine invariant interest point detectors and region […]

Computing curve skeletons of 3D shapes is a challenging task. Recently, a high-potential technique for this task was proposed, based on integrating medial information obtained from several 2D projections of a 3D shape (Livesu et al., 2012). However effective, this technique is strongly influenced in terms of complexity by the quality of a so-called skeleton […]

Image magnification generally results in loss of image quality. Therefore image magnification requires interpolation to read between the pixels. Generally the enlarged images suffer from imperfect reconstructions, pixelization and jagged contours. The proposed system provides error-free high resolution for real images. The basic idea behind the system comprises two basic steps: Fast Curvature Based Interpolation […]

Nuclear emulsion, a tracking detector with sub-micron position resolution, has played a successful role in the field of particle physics and the analysis speed has been substantially improved by the development of automated scanning systems. This paper describes a newly developed automated scanning system and its application to the analysis of nuclear fragments emitted almost […]

We investigate applicability of GPU to DEM. NVIDIA’s code obtained superior performance than CPU in computational time. A model of contact forces in NVIDIA’s code is too simple for practical use. We modify this model by replacing it with the practical model. The simulation shows that the practical model obtains the computing speed 6 times […]

We present efficient algorithms to build data structures and the lists needed for fast multipole methods. The algorithms are capable of being efficiently implemented on both serial, data parallel GPU and on distributed architectures. With these algorithms it is possible to map the FMM efficiently on to the GPU or distributed heterogeneous CPU-GPU systems. Further, […]

Graph processing has gained renewed attention. The increasing large scale and wealth of connected data, such as those accrued by social network applications, demand the design of new techniques and platforms to efficiently derive actionable information from large scale graphs. Hybrid systems that host processing units optimized for both fast sequential processing and bulk processing […]

We present an efficient and robust algorithm to approximate the 3D Minkowski sum of two arbitrary polyhedra on Graphics Processing Unit (GPU). Our algorithm makes use of the idea of super-union, in which we decompose the two polyhedra into convex pieces as usual, but the way we perform pairwise convex Minkowski sum and merge the […]

The purpose of our project was to write a fast OpenCL LU-Decomposition (LUD) solution for the Intel/AMD CPU/GPU and Altera’s FPGA and record the amount of recoding required to optimize the algorithm for these platforms. LUD is the mathematical operation which factors a given matrix into the multiplication of a lower triangular and an upper […]