Function comm_graph

python/dolfinx/graph.py:149–182

Build a parallel communication graph from an index map. The communication graph is a directed graph that represents the communication pattern for a distributed array, and specifically the forward scatter operation where the values for owned indices are sent to ghosting ranks. The gr

(map: _cpp.common.IndexMap, root: int = 0)

def comm_graph(map: _cpp.common.IndexMap, root: int = 0) -> AdjacencyList:
    """Build a parallel communication graph from an index map.

    The communication graph is a directed graph that represents the
    communication pattern for a distributed array, and specifically the
    forward scatter operation where the values for owned indices are
    sent to ghosting ranks. The graph is built from an index map, which
    describes the local and ghosted indices of the array.

    Edges in the graph represent communication from the owning rank to
    ranks that ghost the data. The edge data holds the (0) target node,
    (1) edge weight, and (2) an indicator for whether the sending and
    receiving ranks share memory (``local==1``) or if the ranks do not
    share memory (``local==0``). The node data holds the local size
    (number of owned indices) and the number of ghost indices.

    The graph can be processed using :func:`comm_graph` to build data
    structures that can be used to build a `NetworkX
    <https://networkx.org/>`_ directed graph.

    Note:
        This function is collective across all MPI ranks. The
        communication graph is returned on the `root` rank. All other
        ranks return an empty graph

    Args:
        map: Index map to build the communication graph from.
        root: Rank that will return the communication graph. Other ranks
            return an empty graph.

    Returns:
        An adjacency list representing the communication graph.
    """
    return AdjacencyList(_cpp.graph.comm_graph(map))


def comm_graph_data(