@MastersThesis{Jasansky-TR-2007-11,
  UPDATE  = { 2007-07-24 },
  author =     {Jasansk{\'y}, Marek},
  supervisor = {Kybic, Jan},
  language =   {czech},
  title =      {Paralelizace {\v r}e{\v s}en{\'\i} p{\v r}{\'\i}m{\'e}ho
                probl{\'e}mu {EEG} rekonstrukce metodou {BEM}},
  e_title =    {A Parallelization of The EEG Forward Problem by 
                The Boundary Element Method},
  school =     {Center for Machine Perception, K13133 FEE Czech Technical
                University},
  address =    {Prague, Czech Republic},
  year =       {2007},
  month =      {June},
  day =        {19},
  type =       {{MSc Thesis CTU--CMP--2007--11}},
  issn =       {1213-2365},
  pages =      {44},
  figures =    {11},
  authorship = {100},
  psurl = {[PDF, 1.3MB]},
  url =  {ftp://cmp.felk.cvut.cz/pub/cmp/articles/kybic/Jasansky-MSthesis2007.pdf},
  project =    {MSM6840770012},
  annote = {To compute the electric current sources locations inside
    of the brain we need to solve EEG/MEG forward task. We propose a
    parallel implementation based on existing boundary element method
    (BEM) solver in OCaml language. Our parallel version uses standard
    message passing system MPI and it can run on heterogenous cluster
    of cumputers.  The master-slave method is used. The
    parallelization is based on the division of the system matrix into
    submatrices distributed between working processes (slaves). For
    optimal load balancing the system matrix is divided to a number of
    submatrices which are dynamically assigned to the slaves. MINRES
    iterations runs on the master node, but the matrix vector products
    are computed in parallel. Our program was tested on a nine-node
    cluster and we achieved almost linear acceleration with respect to
    the number of processors.},
  keywords = {boundary element method, MEG, EEG, parallelization, Ocaml},
}