Sökning: "high-performance computing"

Visar resultat 1 - 5 av 80 avhandlingar innehållade orden high-performance computing.

  1. 1. Design of High Performance Computing Software for Genericity and Variability

    Detta är en avhandling från Uppsala : Acta Universitatis Upsaliensis

    Författare :Malin Ljungberg; Michael Thuné; Kurt Otto; Hans Petter Langtangen; [2007]
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; PDE solver; high-performance; coordinate invariant; curvilinear coordinates; symmetry exploiting; generalized Fourier transform; finite difference; expression templates; feature modeling; variability; Beräkningsvetenskap; Scientific Computing;

    Sammanfattning : Computer simulations have emerged as a cost efficient complement to laboratory experiments, as computers have become increasingly powerful.The aim of the present work is to explore the ideas of some state of the art software development practices, and ways in which these can be useful for developing high performance research codes. LÄS MER

  2. 2. High-Performance Finite Element Methods with Application to Simulation of Diffusion MRI and Vertical Axis Wind Turbines

    Detta är en avhandling från KTH Royal Institute of Technology

    Författare :Van-Dang Nguyen; Johan Hoffman; Johan Jansson; Axel Målqvist; [2018]
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; High performance finite element method; computational diffusion MRI; turbulent flow; vertical axis wind turbine.; Datalogi; Computer Science;

    Sammanfattning : The finite element methods (FEM) have been developed over decades, and together with the growth of computer engineering, they become more and more important in solving large-scale problems in science and industry. The objective of this thesis is to develop high-performance finite element methods (HP-FEM), with two main applications in mind: computational diffusion magnetic resonance imaging (MRI), and simulation of the turbulent flow past a vertical axis wind turbine (VAWT). LÄS MER

  3. 3. Autonomous resource management for high performance datacenters

    Detta är en avhandling från Umeå : Umeå University

    Författare :Abel Souza; Johan Tordsson; Alexandru Iosup; [2020]
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Datacenters; high performance computing; scheduling; hybrid; Computer Science; datalogi;

    Sammanfattning : Over the last decade, new applications such as data intensive workflows have hit an inflection point in wide spread use and influenced the compute paradigm of most scientific and industrial endeavours. Data intensive workflows are highly dynamic and adaptable to resource changes, system faults, and by also allowing approximate solutions into their models. LÄS MER

  4. 4. Grid and High-Performance Computing for Applied Bioinformatics

    Detta är en avhandling från Stockholm : KTH

    Författare :Jorge Andrade; Jacob Odeberg; Luciano Milanesi; [2007]
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Grid computing; bioinformatics; genomics; proteomics; NATURAL SCIENCES Chemistry Theoretical chemistry Bioinformatics; NATURVETENSKAP Kemi Teoretisk kemi Bioinformatik;

    Sammanfattning : The beginning of the twenty-first century has been characterized by an explosion of biological information. The avalanche of data grows daily and arises as a consequence of advances in the fields of molecular biology and genomics and proteomics. LÄS MER

  5. 5. High-Performance Computing For Support Vector Machines

    Detta är en avhandling från Skövde : University of Skövde

    Författare :Shirin Tavara; Alexander Schliep; Alexander Karlsson; Richard Johansson; [2018]
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Skövde Artificial Intelligence Lab SAIL ; Skövde Artificial Intelligence Lab SAIL ; INF301 Data Science; INF301 Data Science;

    Sammanfattning : Machine learning algorithms are very successful in solving classification and regression problems, however the immense amount of data created by digitalization slows down the training and predicting processes, if solvable at all. High-Performance Computing(HPC) and particularly parallel computing are promising tools for improving the performance of machine learning algorithms in terms of time. LÄS MER