Search results for "GPU"

Distributed multi-objective optimization methods for shape design using evolutionary algorithms and game strategies

2012

Fourth Workshop on using Emerging Parallel Architectures

2012

AbstractThe Fourth Workshop on Using Emerging Parallel Architectures (WEPA), held in conjunction with ICCS 2012, provides a forum for exploring the capabilities of emerging parallel architectures such as GPUs, FPGAs, Cell B.E., Intel M.I.C. and multicores to accelerate computational science applications.

Yleinen laskenta grafiikkasuorittimilla

2012

Esitellään nykyaikaisten grafiikkasuorittimien rakennetta, toimintaperiaatteita ja tutkitaan OpenCL:ää keinona käyttää niiden laskentakykyä yleisempään laskentaan. Toteutetaan osa JPEG-kuvanpakkausalgoritmia grafiikkasuorittimella OpenCL:n avulla.

Image processing applications in object detection and graph matching : from Matlab development to GPU framework

2020

Automatically finding correspondences between object features in images is of main interest for several applications, as object detection and tracking, flow velocity estimation, identification, registration, and many derived tasks. In this thesis, we address feature correspondence within the general framework of graph matching optimization and with the principal aim to contribute, at a final step, to the design of new and parallel algorithms and their implementation on GPU (Graphics Processing Unit) systems. Graph matching problems can have many declinations, depending on the assumptions of the application at hand. We observed a gap between applications based on local cost objective functio…

WiseEye: A Platform to Manage and Experiment on Smart Camera Networks

2016

International audience; Embedded vision is probably at the edge of phenomenal expansion. The smart cameras are embedding some processing units which are more and more powerful. Last decade, high-speed image processing can be implemented on specifically designed architectures [1] nevertheless the designing time of such systems was quite high and time to market therefore as well. Since, powerful chips (i.e System On Chip) and quick prototyping methodologies are contently emerging [2],[3],[4] and enable more complex algorithms to be implemented faster. Moreover, smart cameras which are embedding flexible and powerful multi-core processors or Graphic Processors Unit (GPU) are now available and …

Large-scale genome-wide association studies on a GPU cluster using a CUDA-accelerated PGAS programming model

2015

[Abstract] Detecting epistasis, such as 2-SNP interactions, in genome-wide association studies (GWAS) is an important but time consuming operation. Consequently, GPUs have already been used to accelerate these studies, reducing the runtime for moderately-sized datasets to less than 1 hour. However, single-GPU approaches cannot perform large-scale GWAS in reasonable time. In this work we present multiEpistSearch, a tool to detect epistasis that works on GPU clusters. While CUDA is used for parallelization within each GPU, the workload distribution among GPUs is performed with Unified Parallel C++ (UPC++), a novel extension of C++ that follows the Partitioned Global Address Space (PGAS) model…

Simulazione elettromagnetica tramite il metodo FDTD: implementazione in ambiente computazionale avanzato

2012

Mapping of BLASTP Algorithm onto GPU Clusters

2011

Searching protein sequence database is a fundamental and often repeated task in computational biology and bioinformatics. However, the high computational cost and long runtime of many database scanning algorithms on sequential architectures heavily restrict their applications for large-scale protein databases, such as GenBank. The continuing exponential growth of sequence databases and the high rate of newly generated queries further deteriorate the situation and establish a strong requirement for time-efficient scalable database searching algorithms. In this paper, we demonstrate how GPU clusters, powered by the Compute Unified Device Architecture (CUDA), OpenMP, and MPI parallel programmi…

First Experiences on an Accurate SPH Method on GPUs

2017

It is well known that the standard formulation of the Smoothed Particle Hydrodynamics is usually poor when scattered data distribution is considered or when the approximation near the boundary occurs. Moreover, the method is computational demanding when a high number of data sites and evaluation points are employed. In this paper an enhanced version of the method is proposed improving the accuracy and the efficiency by using a HPC environment. Our implementation exploits the processing power of GPUs for the basic computational kernel resolution. The performance gain demonstrates the method to be accurate and suitable to deal with large sets of data.

GPU-accelerated exhaustive search for third-order epistatic interactions in case–control studies

2015

This is a post-peer-review, pre-copyedit version of an article published in Journal of Computational Science. The final authenticated version is available online at: https://doi.org/10.1016/j.jocs.2015.04.001 [Abstract] Interest in discovering combinations of genetic markers from case–control studies, such as Genome Wide Association Studies (GWAS), that are strongly associated to diseases has increased in recent years. Detecting epistasis, i.e. interactions among k markers (k ≥ 2), is an important but time consuming operation since statistical computations have to be performed for each k-tuple of measured markers. Efficient exhaustive methods have been proposed for k = 2, but exhaustive thi…