METIS partitioner for mesh and graph
Project description
Introduction
mgmetis is a mesh and graph Partitioning suite wrapped on top of METIS & ParMETIS. It targets at intermediate level of package developers who work in, e.g., finite element libraries.
mgmetis provides all functionalities from original METIS/ParMETIS via 1) a Cython interface and 2) a native Python interface through ctypes.
Installation
mgmetis can be installed via pip, i.e.,
$ pip3 install mgmetis --user
If you have MPI and mpi4py installed, then the parallel components will be built automatically. Note that mpi4py is NOT an installation dependency.
Examples
It’s worth noting that mgmetis simply wraps around original METIS interfaces. mgmetis doesn’t have complicated data structures for graphs and meshes, everything is passed in as arrays as per CSR format. The variable names are preserved as what they are in the original documentation. For more information, please refer to http://glaros.dtc.umn.edu/gkhome/metis/metis/download and http://glaros.dtc.umn.edu/gkhome/metis/parmetis/download for METIS and ParMETIS original documentation PDF files, respectively.
Python Mode
For graph Partitioning, either multilevel recursive bisection or multilevel k-way partitioning methods, the interfaces are exactly the same. The mandatory parameters are nparts (number of partitions), xadj (the starting positions of adjacent list) and adjncy (the compressed adjacent list).
Give a a directed graph based on the following structure:
0---1---2 | | | 3---4---5 | | | 6---7---8
We can have the set up a simple graph representation, which looks like
>>> graph = {
... 0: [1, 3],
... 1: [0, 2, 4],
... 2: [1, 5],
... 3: [0, 4, 6],
... 4: [1, 3, 5, 7],
... 5: [2, 4, 8],
... 6: [3, 7],
... 7: [4, 6, 8],
... 8: [5, 7],
... }
We can then convert it into CSR graph
>>> xadj = [0]
>>> for edges in graph.values():
... xadj.append(xadj[-1]+len(edges))
...
>>> xadj
[0, 2, 5, 7, 10, 14, 17, 19, 22, 24]
>>> adjncy = [node for edges in graph.values() for node in edges]
Then a partition of 2 with recursive algorithm can be simply done via
>>> from mgmetis import metis
>>> objval, part = metis.part_graph_recursive(2, xadj, adjncy)
>>> part
array([0, 0, 1, 0, 0, 1, 1, 1, 1])
Notice that the structure in this example can also be viewed as a mesh with 12 bar cells, of which the user may want to determine a element-wise partition.
cells = [
... [0, 1],
... [1, 2],
... [3, 4],
... [4, 5],
... [6, 7],
... [7, 8],
... [0, 3],
... [1, 4],
... [2, 5],
... [3, 6],
... [4, 7],
... [5, 8],
... ]
Then, partitoning the mesh into 2 components can be done via part_mesh_dual
>>> objval, epart, npart = metis.part_mesh_dual(2, cells)
>>> epart
array([0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1])
For other supported advanced features, such as weights, please consult the METIS documentation. All the arguments are supported via keyword inputs. Here, we further demonstrate how to customize options, a.k.a. control parameters, in METIS. The parameters in metis are specified via a fixed length 40 integer array.
>>> opts = metis.get_default_options()
>>> opts
Options([-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-1, -1, -1, -1, -1, -1, -1, -1], dtype=int32)
If you are familiar with METIS, you can directly work with the parameters. mgmetis implements a helper module mgmetis.enums to help the user work with control parameters. Let’s say the user has a Fortran-based index graph
>>> from mgmetis.enums import OPTION
>>> opts[OPTION.NUMBERING] = 1
>>> xadj = [x + 1 for x in xadj]
>>> adjncy = [x + 1 for x in adjncy]
>>> objval, part = metis.part_graph_recursive(2, xadj, adjncy, options=opts)
>>> part
array([1, 1, 2, 1, 1, 2, 2, 2, 2])
ctypes Mode
A powerful feature of mgmetis is that it allows the user to directly work with the underlying C functions through ctypes. However, by dealing with foreign C interfaces, the user needs to explicitly ensure the type consistency.
mgmetis supports both 32-bit and 64-bit integer builds of METIS. The original METIS functions all have prefix METIS_, whereas in mgmetis ctypes module, the prefix is trimmed out. Let’s see the following example to see how to use the ctypes interface.
>>> import numpy as np
>>> xadj = np.asarray(xadj) # from list of ints, the dtype is int64
>>> adjncy = np.asarray(adjncy)
>>> part = np.empty(xadj.size - 1, dtype=int) # output
>>> opts = np.assarray(opts, dtype=int)
Recall that the graph partitioning routine takes all arguments as their references. This can be done via ctypes
>>> import ctypes as c
>>> nv = c.c_int64(part.size)
>>> ncon = c.c_int64(1)
>>> objval = c.c_int64(0) # output
>>> nparts = c.c_int64(2)
>>> xadj_ptr = xadj.ctypes.data_as(c.POINTER(c.c_int64))
>>> adj_ptr = adjncy.ctypes.data_as(c.POINTER(c.c_ind64))
>>> opts_ptr = opts.ctypes.data_as(c.POINTER(c.c_int64))
>>> part_ptr = part.ctypes.data_as(c.POINTER(c.c_int64)) # output address
We now need to access the ctype interface in mgmetis
>>> from mgmetis.metis import libmetis64 # libmetis for 32bit int
>>> libmetis64.PartGraphRecursive(
... c.byref(nv),
... c.byref(ncon),
... xadj_ptr,
... adj_ptr,
... None, # NULL
... None,
... None,
... c.byref(nparts),
... None,
... None,
... opts_ptr,
... c.byref(objval),
... part_ptr,
... )
For more details for ctypes, please refer to https://docs.python.org/3.8/library/ctypes.html. Also, take a look at np.ndarray.ctypes.
Enable METIS in Cython
Each of the METIS routine has a Cython interface, whose naming convention is samilar as it’s in ctypes mode. mgmetis resolves the issues regarding linking to METIS. In addition, each of the Cython function is defined with nogil specifier.
The following code shows how to access the METIS_PartGraphRecursive
cimport mgmetis.libmetis as metis # 32 bit
# then each of the function in METIS public domain has a Cython interface
# without prefix METIS_
cdef int ret = metis.PartGraphRecursive(...)
if ret != metis.OK:
raise ValueError
When you compile your Cython code, you don’t need to worry about linking to METIS, Python will load the correct symbol in runtime.
Work with MPI
The native Python mode supports parallel partitioning of a static graph or mesh. The underlying routines are:
ParMETIS_V3_PartKway,
ParMETIS_V3_PartGeomKway,
ParMETIS_V3_PartGeom, and
ParMETIS_V3_PartMeshKway.
Their usage is similar to the serial version, please take a look at the unit testing scripts.
A complete support of ParMETIS can be done (for now) via either ctypes mode or Cython mode. For ctypes mode
from mgmetis.parmetis import libparmetis # libparmetis64 for 64bit
help(libparmetis)
and for the Cython mode
cimport mgmetis.parmetis as parmetis # mgmetis.parmetis64 for 64 bit
cdef int ret = parmetis.PartKway(...)
Notice that for Cython mode, you will need to access mpi4py Cython interface. It will, then, require you to add its path during specifying Extension, and the compiler needs to be set to mpicc.
License
mgmetis is considerred as a wrapper of METIS, and it is distributed under MIT license. Users should also refer to http://glaros.dtc.umn.edu/gkhome/views/metis for the licenses of METIS and ParMETIS.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file mgmetis-0.1.1.tar.gz
.
File metadata
- Download URL: mgmetis-0.1.1.tar.gz
- Upload date:
- Size: 381.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.7.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 60ff5aad6e0eefc8bdf5b66ee0a90f0cd88dbd369f78510ce480146697f95c15 |
|
MD5 | 09900a3b88b42a9d7ae145b950e92c09 |
|
BLAKE2b-256 | 4ca74457860096acddbfbe9949da40a9c42a3432bafaa486f7eb74812deae649 |