A GPU capable method for surface reconstruction from unorganized point clouds without additional information, called GLT (GPU Local Triangulation), is presented. The main objective of this research is the generation of a GPU interpolating reconstruction based on local Delaunay triangulations, inspired by a pre-existing reconstruction algorithm. Current graphics hardware accelerated algorithms a...

Parallel computing has been in use for decades, and throughout many researchers have sought to define a model for algorithm design for such a platform. Valiant developed a model for parallel computing, which was later extended to later include multi-core processors, but it still may not be best suited for the unique GPU architecture. With the current advances in high performance computing, it i...

The mixed precision variable preconditioning (VP) Krylov subspace method is implemented on Graphics Processing Unit (GPU) and Many Integrated Core (MIC) architecture, and the linear system obtained from an electromagnetic analysis is solved by the method. In recent year, high-performance multi/many core computer architecture can be cheap and easily available, and the simulation code must be par...

This paper presents briefly describes the state of the art of accelerating image processing with graphics hardware (GPU) and discusses some of its caveats. Then it describes GpuCV, an open source multi-platform library for GPU-accelerated image processing and Computer Vision operators and applications. It is meant for computer vision scientist not familiar with GPU technologies. GpuCV is design...

Developing high performance GPU code is labor intensive. Ideally, developers could recoup high GPU development costs by generating high-performance programs for CPUs and other architectures from the same source code. However, current OpenCL compilers for non-GPUs do not fully exploit optimizations in well-tuned GPU codes. To address this problem, we develop an OpenCL implementation that efficie...

In practice, combinatorial optimization problems are complex and computationally time-intensive. Local search algorithms are powerful heuristics which allow to significantly reduce the computation time cost of the solution exploration space. In these algorithms, the multistart model may improve the quality and the robustness of the obtained solutions. However, solving large size and time-intens...

With the rapid growth of next generation sequencing technologies, such as Slex, more and more data have been discovered and published. To analyze such huge data the computational performance is an important issue. Recently, many tools, such as SOAP, have been implemented on Hadoop and GPU parallel computing architectures. BLASTP is an important tool, implemented on GPU architectures, for biolog...

An efficient GPU-based sorting algorithm is proposed in this paper together with a merging method on graphics devices. The proposed sorting algorithm is optimized for modern GPU architecture with the capability of sorting elements represented by integers, floats and structures, while the new merging method gives a way to merge two ordered lists efficiently on GPU without using the slow atomic f...

Multi-core based high performance computing systems are available with a reasonable price. Parallel programming paradigm needs to be adjusted to an individual system. Parallel computing systems were compared in this paper. Electroencephalography signals were collected in order to measure performance of parallel computing for CPU and GPU based systems. A CPU based system showed better performanc...