short course, IMVIP 2004 conference, Dublin

Discussion in 'VHDL' started by Abbes Amira, Jun 27, 2004.

  1. Abbes Amira

    Abbes Amira Guest

    Short course: IMVIP 2004

    http://www.cs.tcd.ie/IMVIP2004/ShortCourses.html

    Accelerating Matrix Algorithms on Reconfigurable Hardware for Image
    and Signal Processing Applications presented by Dr. Abbes Amira,
    Queens University, Belfast. (Provisional Schedule: Tuesday, August
    31st 11.30-13.30).


    "Accelerating Matrix Algorithms on Reconfigurable Hardware for Image
    and Signal Processing Applications"
    In this Course, Dr. Amira will be presenting a number of solutions and
    tools to address and perform a range of applications in image, video
    and signal processing, 3D graphics and scientific applications. Dr.
    Amira will focus on the design, implementation and acceleration of
    matrix algorithms such as matrix operations, transforms and
    decompositions for image and signal processing using Field
    Programmable Gates Arrays FPGAs, different architectures, arithmetic
    techniques, design methodologies and design entries (Handel C,
    Schematic and VHDL). A range of matrix algorithms will be addressed
    including: Discrete Orthogonal Transforms DOTs for image and signal
    processing, Matrix Multiplication for array processing, Fast Fourier
    Transform (FFT) for frequency image filtering, Discrete Wavelet
    Transform (DWT) for Image and Video Compression, Singular Value
    Decomposition (SVD) for image denoising. Optimisation solutions will
    be also presented for reconfigurable hardware design using intelligent
    techniques. The problem of processing large matrices will be also
    addressed in this course.
    Course instructor
    Dr. Abbes Amira obtained an "Ingéniorat d'Etat" degree in Electronics
    and a DEA degree in image and speech processing from the National
    Polytechnic School of Algiers "ENP", a PhD degree in Computer Science
    and a PGCHET degree from Queen's University, Belfast (UK). He is
    currently a lecturer in Computer Science at Queen's University,
    Belfast, teaching computer architecture and algorithms and data
    structures. His research interests are in Design and Implementation of
    Digital Image and Signal Processing algorithms, Custom Computing using
    Field Programmable Gate Array (FPGAs), Hardware/Software Co- Design,
    System on Chip, Image Processing based Wavelet Transforms, Telecom
    Applications, Information Systems, Artificial Intelligence,
    Optimisation Techniques and Information Retrieval. He has written
    several papers in peer-reviwed conferences and premier journals and
    chaired a number of sessions in prestigious conferences. He is a
    regular reviewer for several IEEE, ACM, Elsevier Journals and
    Conferences such as DSP, TIP, ISCAS, ICASSP and DAC. Dr. Amira is a
    member of IEEE, ACM and SIGDA.
    He has carried out successful work in the use of FPGAs for
    implementing a range of matrix algorithms for signal and image
    processing applications. He is author of over 80 refereed conference
    and journal papers during his career to date. In October 2001 he was
    awarded an EPSRC grant for a proposal entitled "Coprocessor based
    Matrix Algorithms for Image and Signal Processing". This is a
    three-year project (worth £112,445). A number of solutions have been
    successfully implemented for processing large matrix multiplications,
    transforms and decompositions for image and signal processing
    applications.
    The research carried out during Dr. Amira's PhD project was concerned
    with an investigation into the design and implementation of a range of
    matrix algorithms such as matrix multiplication and one-dimensional
    transforms using a novel custom coprocessor system for MATrix
    algorithms based on Reconfigurable Computing (RCMAT). New algorithms
    for matrix multiplication, using both systolic and distributed
    arithmetic design methodologies have been developed. The architectures
    developed for matrix multiplication exploit different arithmetic
    techniques such as bit parallel, bit serial and digit serial design
    methods. In addition, novel architectures were developed to perform
    matrix transforms using both systolic and distributed arithmetic
    design methodologies. These architectures are scalable, modular and
    require less area and time complexity with reduced latency in
    comparison with existing structures. One of the most notable
    achievements of this work was a parallel matrix multiplier developed,
    outperforming the PAMBlox multiplier developed at Stanford University,
    USA.
    Dr. Amira has been invited several times to give talks to Universities
    and companies in UK and US, including University of Oakland at
    Michigan State, USA, University of Dundee, Scotland, UK and ANDOR
    company in Belfast.
     
    Abbes Amira, Jun 27, 2004
    #1
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