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Manuscript Title: XMDS2: Fast, scalable simulation of coupled stochastic partial differential equations
Authors: Graham R. Dennis, Joseph J. Hope, Mattias T. Johnsson
Program title: XMDS2
Catalogue identifier: AENK_v1_0
Distribution format: tar.gz
Journal reference: Comput. Phys. Commun. 184(2013)201
Programming language: Python and C++.
Computer: Any computer with a Unix-like system, a C++ compiler and Python.
Operating system: Any Unix-like system; developed under Mac OS X and GNU/Linux.
RAM: Problem dependent (roughly 50 bytes per grid point)
Keywords: Initial value problems, differential equations, stochastic partial differential equations.
PACS: 02.50.Ey, 02.60.Cb, 02.60.Lj, 02.70.Jn.
Classification: 4.3, 6.5.

External routines: The external libraries required are problem-dependent.
Uses FFTW3 Fourier transforms (used only for FFT-based spectral methods),
dSFMT random number generation (used only for stochastic problems),
MPI message-passing interface (used only for distributed problems),
HDF5, GNU Scientific Library (used only for Bessel-based spectral methods)
and a BLAS implementation (used only for non-FFT-based spectral methods).

Nature of problem:
General coupled initial-value stochastic partial differential equations.

Solution method:
Spectral method with method-of-lines integration

Running time:
Determined by the size of the problem