CoCalc -- classify_in_mpi

Path: Boolean-Cayley-graphs / boolean_cayley_graphs / classify_in_mpi_parallel.py
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r"""
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Classification in parallel using MPI
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====================================
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The ``classify_in_mpi_parallel`` module defines functions that
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use MPI to save Cayley graph classifications or partial classifications in parallel.
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AUTHORS:
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- Paul Leopardi (2017-10-13)
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"""
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#*****************************************************************************
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#       Copyright (C) 2016 Paul Leopardi [email protected]
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#
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#  Distributed under the terms of the GNU General Public License (GPL)
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#  as published by the Free Software Foundation; either version 2 of
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#  the License, or (at your option) any later version.
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#                  http://www.gnu.org/licenses/
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#*****************************************************************************
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from math import log
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from sage.crypto.boolean_function import BooleanFunction
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from sage.functions.other import Function_ceil
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from boolean_cayley_graphs.bent_function import BentFunction
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from boolean_cayley_graphs.classify_in_parallel import save_one_classification
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from boolean_cayley_graphs.classify_in_parallel import save_one_class_part
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def save_classifications_in_parallel(
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    comm,
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    name_prefix,
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    list_of_f,
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    start=0,
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    stop=None,
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    directory=None):
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    r"""
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    Using MPI, construct and save a number of Cayley graph classifications
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    corresponding to a list of bent functions.
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    INPUT:
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    - ``comm`` -- MPI communicator.
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    - ``name_prefix`` -- String. Name prefix to use with ``save_mangled`` to save each classification.
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    - ``list_of_f`` -- List of forms or bent functions.
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    - ``start`` -- Integer. Default=0. Index of start position in the list.
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    - ``stop`` -- Integer. Default=None. Index after end position, or ``None`` if whole remaining list.
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    - ``directory`` -- string, optional. The directory where the object
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      is to be saved. Default is None, meaning the current directory.
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    OUTPUT: None.
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    EFFECT: Uses ``name`` to save the classifications corresponding to ``list_of_f``.
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    """
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    rank = comm.Get_rank()
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    size = comm.Get_size()
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    if stop == None:
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        stop = len(list_of_f)
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    for n in range(start + rank, stop, size):
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        name = name_prefix + '_' + str(n)
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        form = BooleanFunction(list_of_f[n]).truth_table(format='hex')
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        save_one_classification(
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            name,
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            form,
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            directory=directory)
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def save_class_parts_in_parallel(
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    comm,
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    name_prefix,
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    form,
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    c_len=1,
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    directory=None):
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    r"""
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    Using MPI, construct a complete list of the partial Cayley graph classifications
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    corresponding to a given bent function or algebraic normal form.
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    INPUT:
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    - ``comm`` -- MPI communicator.
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    - ``name_prefix`` -- String. Name prefix to use with ``save_mangled`` to save each class part.
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    - ``form`` -- A bent function or an algebraic normal form.
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    - ``c_len`` -- Integer. Default=1. The number of values of `c` to use in each class part.
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    - ``directory`` -- string, optional. The directory where the object
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      is to be saved. Default is None, meaning the current directory.
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    OUTPUT: None.
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    EFFECT: Uses ``name_prefix`` to save all partial classifications corresponding to ``bentf``.
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    """
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    rank = comm.Get_rank()
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    size = comm.Get_size()
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    bentf = BentFunction(form)
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    dim = bentf.nvariables()
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    v = 2 ** dim
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    ceil = Function_ceil()
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    nbr_parts = ceil(v * 1.0 / c_len)
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    # Include the case where size > nbr_parts and therefore
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    # this function is being applied to many bent functions in parallel.
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    if size > nbr_parts:
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        beg_n = rank % nbr_parts
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        end_n = beg_n + 1
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    else:
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        beg_n = rank
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        end_n = nbr_parts
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    nbr_digits = ceil(log(nbr_parts, 10))
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    for n in range(beg_n, end_n, size):
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        n_str = '{0:0={width}}'.format(n, width=nbr_digits)
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        save_one_class_part(
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            name=name_prefix + '_' + n_str,
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            bentf=bentf,
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            c_start=c_len * n,
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            c_stop=c_len * (n + 1),
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            directory=directory)
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