A new algorithm for numerical path following applied to an example from hydrodynamical flow
SIAM Journal on Scientific and Statistical Computing
Using MPI: portable parallel programming with the message-passing interface
Using MPI: portable parallel programming with the message-passing interface
Parallel programming with MPI
Matrix computations (3rd ed.)
Computation of Pseudospectra by Continuation
SIAM Journal on Scientific Computing
Pseudospectra of Linear Operators
SIAM Review
Basic Linear Algebra Subprograms for Fortran Usage
ACM Transactions on Mathematical Software (TOMS)
Parallel computation of pseudospectra of large sparse matrices
Parallel Computing - Parallel matrix algorithms and applications
Parallel computation of pseudospectra of large sparse matrices
Parallel Computing - Parallel matrix algorithms and applications
The design of a distributed MATLAB-based environment for computing pseudospectra
Future Generation Computer Systems - Special section: Complex problem-solving environments for grid computing
The design of a distributed MATLAB-based environment for computing pseudospectra
Future Generation Computer Systems - Special section: Complex problem-solving environments for grid computing
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This paper presents the programming environment of a new tool for the parallel computation of Pseudospectra. Based on the PPA Talgorithm described in [16, 17], this algorithm offers total reliability and can handle singularities along the level curve without difficulty. It offers a guarantee of termination even in the presence of round-off errors and makes use of the large granularity for parallelism in PAT [17]. This results in large speedups and high efficiency. The software is able to trace multiple level curves simultaneously and task in to account the symmetry of the pseudospectrum in the case of real matrices to reduce the total computational cost. The ability of the software to compute multiple slices of the same level curve simultaneously enhances the speedup and efficiency. The user drives the parallel application through a graphical user interface. The interface includes graphical features (zoom in, zoom out, color control,…) and computational features (raise or lower level curve priority, limit computation to a set of processors,…) crucial for the appreciation of the information provided by the pseudospectrum. Although the application was developed for the computation of the pseudospectrum, it can be used, provided minor modifications, to trace the level curves of any continuous, not necessarily smooth, function f(z): C → R