DMPlex: Unstructured Grids#
This chapter introduces the DMPLEX
subclass of DM
, which allows
the user to handle unstructured grids using the generic DM
interface
for hierarchy and multi-physics. DMPLEX
was created to remedy a huge
problem in all current PDE simulation codes, namely that the
discretization was so closely tied to the data layout and solver that
switching discretizations in the same code was not possible. Not only
does this preclude the kind of comparison that is necessary for
scientific investigation, but it makes library (as opposed to monolithic
application) development impossible.
Representing Unstructured Grids#
The main advantage of DMPLEX
in representing topology is that it
treats all the different pieces of a mesh, e.g. cells, faces, edges, and
vertices, in the same way. This allows the interface to be
small and simple, while remaining flexible and general. This also allows
“dimension independent programming”, which means that the same algorithm
can be used unchanged for meshes of different shapes and dimensions.
All pieces of the mesh (vertices, edges, faces, and cells) are treated as points, which are each identified by a
PetscInt
. A mesh is built by relating points to other points, in
particular specifying a “covering” relation among the points. For
example, an edge is defined by being covered by two vertices, and a
triangle can be defined by being covered by three edges (or even by
three vertices). This structure is known as a Hasse Diagram, which is a
Directed Acyclic Graph (DAG) representing a cell complex using the
covering relation. The graph edges represent the relation, which also
encodes a partially ordered set (poset).
For example, we can encode the doublet mesh as in Fig. 8,
which can also be represented as the DAG in Fig. 9.
To use the PETSc API, we consecutively number the mesh pieces. The PETSc convention in 3 dimensions is to number first cells, then vertices, then faces, and then edges. In 2 dimensions the convention is to number faces, vertices, and then edges. In terms of the labels in Fig. 8, these numberings are
First, we declare the set of points present in a mesh,
DMPlexSetChart(dm, 0, 11);
Note that a chart here corresponds to a semi-closed interval (e.g \([0,11) = \{0,1,\ldots,10\}\)) specifying the range of indices we’d like to use to define points on the current rank. We then define the covering relation, which we call the cone, which are also the in-edges in the DAG. In order to preallocate correctly, we first provide sizes,
/* DMPlexSetConeSize(dm, point, number of points that cover the point); */
DMPlexSetConeSize(dm, 0, 3);
DMPlexSetConeSize(dm, 1, 3);
DMPlexSetConeSize(dm, 6, 2);
DMPlexSetConeSize(dm, 7, 2);
DMPlexSetConeSize(dm, 8, 2);
DMPlexSetConeSize(dm, 9, 2);
DMPlexSetConeSize(dm, 10, 2);
DMSetUp(dm);
and then point values (recall each point is an integer that represents a single geometric entity, a cell, face, edge, or vertex),
/* DMPlexSetCone(dm, point, [points that cover the point]); */
DMPlexSetCone(dm, 0, [6, 7, 8]);
DMPlexSetCone(dm, 1, [7, 9, 10]);
DMPlexSetCone(dm, 6, [2, 3]);
DMPlexSetCone(dm, 7, [3, 4]);
DMPlexSetCone(dm, 8, [4, 2]);
DMPlexSetCone(dm, 9, [4, 5]);
DMPlexSetCone(dm, 10, [5, 3]);
There is also an API for providing the dual relation, using
DMPlexSetSupportSize()
and DMPlexSetSupport()
, but this can be
calculated automatically using the provided DMPlexSetConeSize()
and DMPlexSetCone()
information and then calling
DMPlexSymmetrize(dm);
The “symmetrization” is in the sense of the DAG. Each point knows its covering (cone) and each point knows what it covers (support). Note that when using automatic symmetrization, cones will be ordered but supports will not. The user can enforce an ordering on supports by rewriting them after symmetrization using DMPlexSetSupport()
.
In order to support efficient queries, we construct fast search structures and indices for the different types of points using
DMPlexStratify(dm);
Dealing with Periodicity#
Plex allows you to represent periodic domains is two ways. Using the default scheme, periodic topology can be represented directly. This ensures that all topological queries can be satisified, but then care must be taken in representing functions over the mesh, such as the coordinates. The second method is to use a non-periodic topology, but connect certain mesh points using the local-to-global map for that DM. This allows a more general set of mappings to be implemented, such as partial twists, but topological queries on the periodic boundary cease to function.
For the default scheme, a call to DMLocalizeCoordinates() (which usually happens automatically on mesh creation) creates a second, discontinuous coordinate field. These values can be accessed using DMGetCellCoordinates() and DMGetCellCoordinatesLocal(). Plex provides a convenience method, DMPlexGetCellCoordinates(), that extracts cell coordinates correctly, depending on the periodicity of the mesh. An example of its use is shown below:
const PetscScalar *array;
PetscScalar *coords = NULL;
PetscInt numCoords;
PetscBool isDG;
PetscCall(DMPlexGetCellCoordinates(dm, cell, &isDG, &numCoords, &array, &coords));
for (PetscInt cc = 0; cc < numCoords/dim; ++cc) {
if (cc > 0) PetscCall(PetscPrintf(PETSC_COMM_SELF, " -- "));
PetscCall(PetscPrintf(PETSC_COMM_SELF, "("));
for (PetscInt d = 0; d < dim; ++d) {
if (d > 0) PetscCall(PetscPrintf(PETSC_COMM_SELF, ", "));
PetscCall(PetscPrintf(PETSC_COMM_SELF, "%g", (double)PetscRealPart(coords[cc * dim + d])));
}
PetscCall(PetscPrintf(PETSC_COMM_SELF, ")"));
}
PetscCall(PetscPrintf(PETSC_COMM_SELF, "\n"));
PetscCall(DMPlexRestoreCellCoordinates(dm, cell, &isDG, &numCoords, &array, &coords));
Connecting Data on Grids to its Location in arrays or Vec (PetscSection)#
The strongest links between solvers and discretizations are
the relationship between the layout of data (unknowns) over a mesh (or similar structure) and the data layout in arrays and
Vec
used for computation,data (unknowns) partitioning, and
ordering of data (unknowns).
To enable modularity, we encode the operations above in simple data
structures that can be understood by the linear algebra (Vec
, Mat
, KSP
, PC
, SNES
), time integrator (TS
), and optimization (Tao
) engines in PETSc
without explicit reference to the mesh (topology) or discretization (analysis).
Data Layout by Hand#
Specific entries (or collections of entries) in a Vec
(or a simple array) can be associated with a “location” on a mesh (or other types of data structure) using the PetscSection
object.
A point is a PetscInt
that serves as an abstract “index” into arrays from iteratable sets, such as points on a mesh.
PetscSection
has two modes of operation.
Mode 1:
A PetscSection
associates a set of degrees of freedom (dof), (a small space
\(\{e_k\} 0 < k < d_p\)), with every point. The number of dof and their meaning may be different for different points. For example, the dof on a cell point may represent pressure
while a dof on a face point may represent velocity. Though points must be
contiguously numbered, they can be in any range
\([\mathrm{pStart}, \mathrm{pEnd})\), which is called a chart. A PetscSection
in mode 1 may be thought of as defining a two dimensional array indexed by point in the outer dimension with
a variable length inner dimension indexed by the dof at that point, \(v[pStart <= point < pEnd][0 <= dof <d_p]\) [1].
The sequence for constructing a PetscSection
in mode 1 is the following:
Specify the range of points, or chart, with
PetscSectionSetChart()
.Specify the number of dofs per point, with
PetscSectionSetDof()
. Any values not set will be zero.Set up the
PetscSection
withPetscSectionSetUp()
.
Below we demonstrate such a process used by DMPLEX
but first we introduce the second mode for working with PetscSection
.
Mode 2:
A PetscSection
consists of one more fields each of which is represented (internally) by a PetscSection
.
A PetscSection
in mode 2 may be thought of as defining a three dimensional array indexed by point and field in the outer dimensions with
a variable length inner dimension indexed by the dof at that point. The actual order the values in the array are stored can be set with
PetscSectionSetPointMajor
(PetscSection
, PETSC_TRUE
, PETSC_FALSE
). In point major order all the degrees of freedom for each point for all fields are stored contiguously, otherwise
all degrees of freedom for each field are stored are stored contiguously. With point major order the fields are said to be interlaced.
Consider a PetscSection
with 2 fields and 3 points (from 0 to 2) with 1 dof for each point. In point major order the array has the storage
(values for all the fields at point 0, values for all the fields at point 1, values for all the fields at point 2) while in field major order it is
(values for all points in field 0, values for all points in field 1).
The sequence for constructing such a PetscSection
is the following:
Specify the range of points, or chart, with
PetscSectionSetChart()
. All fields share the same chart.Specify the number of fields with
PetscSectionSetNumFields()
.Optionally provide a name for the fields with
PetscSectionSetFieldName()
.Set the number of dof for each point on each field with
PetscSectionSetFieldDof()
. Again, values not set will be zero.Set the total number of dof for each point with
PetscSectionSetDof()
. Thus value must be greater than or equal to the sum of the values set withPetscSectionSetFieldDof()
at that point. Again, values not set will be zero.Set up the
PetscSection
withPetscSectionSetUp()
.
Once a PetscSection
has been created one can use PetscSectionGetStorageSize
(PetscSection
, PetscInt
*
) to determine the total number of entries that can be stored in an array or Vec
accessible by the PetscSection
. The memory locations in the associated array are found using an offset which can be obtained with:
Mode 1:
PetscSectionGetOffset(PetscSection, PetscInt point, PetscInt &offset);
Mode 2:
PetscSectionGetFieldOffset(PetscSection, PetscInt point, PetscInt field, PetscInt &offset);
The value in the array is then accessed with array[offset]
. If there are multiple dof at a point (and field in mode 2) then array[offset + 1]
, etc give access to each of those dof.
Using the mesh from
Fig. 8, we provide an example of creating a PetscSection
using mode 1. We can lay out data for
a continuous Galerkin \(P_3\) finite element method,
PetscInt pStart, pEnd, cStart, cEnd, c, vStart, vEnd, v, eStart, eEnd, e;
DMPlexGetChart(dm, &pStart, &pEnd);
DMPlexGetHeightStratum(dm, 0, &cStart, &cEnd); // cells
DMPlexGetHeightStratum(dm, 1, &eStart, &eEnd); // edges
DMPlexGetHeightStratum(dm, 2, &vStart, &vEnd); // vertices, equivalent to DMPlexGetDepthStratum(dm, 0, &vStart, &vEnd);
PetscSectionSetChart(s, pStart, pEnd);
for(c = cStart; c < cEnd; ++c)
PetscSectionSetDof(s, c, 1);
for(v = vStart; v < vEnd; ++v)
PetscSectionSetDof(s, v, 1);
for(e = eStart; e < eEnd; ++e)
PetscSectionSetDof(s, e, 2); // two dof on each edge
PetscSectionSetUp(s);
DMPlexGetHeightStratum()
returns all the points of the requested height
in the DAG. Since this problem is in two dimensions the edges are at
height 1 and the vertices at height 2 (the cells are always at height
0). One can also use DMPlexGetDepthStratum()
to use the depth in the
DAG to select the points. DMPlexGetDepth(dm,&depth)
returns the depth
of the DAG, hence DMPlexGetDepthStratum(dm,depth-1-h,)
returns the
same values as DMPlexGetHeightStratum(dm,h,)
.
For \(P_3\) elements there is one degree of freedom at each vertex, 2 along each edge (resulting in a total of 4 degrees of freedom along each edge including the vertices, thus being able to reproduce a cubic function) and 1 degree of freedom within the cell (the bubble function which is zero along all edges).
Now a PETSc local vector can be created manually using this layout,
PetscSectionGetStorageSize(s, &n);
VecSetSizes(localVec, n, PETSC_DETERMINE);
VecSetFromOptions(localVec);
When working with DMPLEX
and PetscFE
(see below) one can simply get the sections (and related vectors) with
DMSetLocalSection(dm, s);
DMGetLocalVector(dm, &localVec);
DMGetGlobalVector(dm, &globalVec);
A global vector is missing both the shared dofs which are not owned by this process, as well as constrained dofs. These constraints represent essential (Dirichlet) boundary conditions. They are dofs that have a given fixed value, so they are present in local vectors for assembly purposes, but absent from global vectors since they are never solved for during algebraic solves.
We can indicate constraints in a local section using PetscSectionSetConstraintDof()
, to set the number of constrained dofs for a given point, and PetscSectionSetConstraintIndices()
which indicates which dofs on the given point are constrained. Once we have this information, a global section can be created using PetscSectionCreateGlobalSection()
, and this is done automatically by the DM
. A global section returns \(-(dof+1)\) for the number of dofs on an unowned point, and \(-(off+1)\) for its offset on the owning process. This can be used to create global vectors, just as the local section is used to create local vectors.
Data Layout using DMPLEX and PetscFE#
A DM
can automatically create the local section if given a description of the discretization, for example using a PetscFE
object. We demonstrate this by creating
a PetscFE
that can be configured from the command line. It is a single, scalar field, and is added to the DM
using DMSetField()
.
When a local or global vector is requested, the DM
builds the local and global sections automatically.
DMPlexIsSimplex(dm, &simplex);
PetscFECreateDefault(PETSC_COMM_SELF, dim, 1, simplex, NULL, -1, &fe);
DMSetField(dm, 0, NULL, (PetscObject) fe);
DMCreateDS(dm);
Here the call to DMSetField()
declares the discretization will have one field with the integer label 0 that has one degree of freedom at each point on the DMPlex
.
To get the \(P_3\) section above, we can either give the option -petscspace_degree 3
, or call PetscFECreateLagrange()
and set the degree directly.
Partitioning and Ordering#
In the same way as MatPartitioning
or
MatGetOrdering()
, give the results of a partitioning or ordering of a graph defined by a sparse matrix,
PetscPartitionerDMPlexPartition
or DMPlexPermute
are encoded in
an IS
. However, the graph is not the adjacency graph of the matrix
but the mesh itself. Once the mesh is partitioned and
reordered, the data layout from a PetscSection
can be used to
automatically derive a problem partitioning/ordering.
Influence of Variables on One Another#
The Jacobian of a problem represents the influence of some
variable on other variables in the problem. Very often, this influence
pattern is determined jointly by the computational mesh and
discretization. DMCreateMatrix()
must compute this pattern when it
automatically creates the properly preallocated Jacobian matrix. In
DMDA
the influence pattern, or what we will call variable
adjacency, depends only on the stencil since the topology is Cartesian
and the discretization is implicitly finite difference.
In DMPLEX
,
we allow the user to specify the adjacency topologically, while
maintaining good defaults. The pattern is controlled by two flags. The first flag, useCone
,
indicates whether variables couple first to their boundary [2]
and then to
neighboring entities, or the reverse. For example, in finite elements,
the variables couple to the set of neighboring cells containing the mesh
point, and we set the flag to useCone = PETSC_FALSE
. By constrast,
in finite volumes, cell variables first couple to the cell boundary, and
then to the neighbors, so we set the flag to useCone = PETSC_TRUE
.
The second flag, useClosure
, indicates whether we consider the
transitive closure of the neighbor relation above, or just a single
level. For example, in finite elements, the entire boundary of any cell
couples to the interior, and we set the flag to
useClosure = PETSC_TRUE
. By contrast, in most finite volume methods,
cells couple only across faces, and not through vertices, so we set the
flag to useClosure = PETSC_FALSE
. However, the power of this method
is its flexibility. If we wanted a finite volume method that coupled all
cells around a vertex, we could easily prescribe that by changing to
useClosure = PETSC_TRUE
.
Evaluating Residuals#
The evaluation of a residual or Jacobian, for most discretizations has the following general form:
Traverse the mesh, picking out pieces (which in general overlap),
Extract some values from the current solution vector, associated with this piece,
Calculate some values for the piece, and
Insert these values into the residual vector
DMPlex separates these different concerns by passing sets of points from mesh traversal routines to data
extraction routines and back. In this way, the PetscSection
which
structures the data inside a Vec
does not need to know anything
about the mesh inside a DMPLEX
.
The most common mesh traversal is the transitive closure of a point,
which is exactly the transitive closure of a point in the DAG using the
covering relation. In other words, the transitive closure consists of
all points that cover the given point (generally a cell) plus all points
that cover those points, etc. So in 2d the transitive closure for a cell
consists of edges and vertices while in 3d it consists of faces, edges,
and vertices. Note that this closure can be calculated orienting the
arrows in either direction. For example, in a finite element
calculation, we calculate an integral over each element, and then sum up
the contributions to the basis function coefficients. The closure of the
element can be expressed discretely as the transitive closure of the
element point in the mesh DAG, where each point also has an orientation.
Then we can retrieve the data using PetscSection
methods,
PetscScalar *a;
PetscInt numPoints, *points = NULL, p;
VecGetArrayRead(u,&a);
DMPlexGetTransitiveClosure(dm,cell,PETSC_TRUE,&numPoints,&points);
for (p = 0; p <= numPoints*2; p += 2) {
PetscInt dof, off, d;
PetscSectionGetDof(section, points[p], &dof);
PetscSectionGetOffset(section, points[p], &off);
for (d = 0; d <= dof; ++d) {
myfunc(a[off+d]);
}
}
DMPlexRestoreTransitiveClosure(dm, cell, PETSC_TRUE, &numPoints, &points);
VecRestoreArrayRead(u, &a);
This operation is so common that we have built a convenience method around it which returns the values in a contiguous array, correctly taking into account the orientations of various mesh points:
const PetscScalar *values;
PetscInt csize;
DMPlexVecGetClosure(dm, section, u, cell, &csize, &values);
// Do integral in quadrature loop putting the result into r[]
DMPlexVecRestoreClosure(dm, section, u, cell, &csize, &values);
DMPlexVecSetClosure(dm, section, residual, cell, &r, ADD_VALUES);
A simple example of this kind of calculation is in
DMPlexComputeL2Diff_Plex()
(source).
Note that there is no restriction on the type of cell or dimension of
the mesh in the code above, so it will work for polyhedral cells, hybrid
meshes, and meshes of any dimension, without change. We can also reverse
the covering relation, so that the code works for finite volume methods
where we want the data from neighboring cells for each face:
PetscScalar *a;
PetscInt points[2*2], numPoints, p, dofA, offA, dofB, offB;
VecGetArray(u, &a);
DMPlexGetTransitiveClosure(dm, cell, PETSC_FALSE, &numPoints, &points);
assert(numPoints == 2);
PetscSectionGetDof(section, points[0*2], &dofA);
PetscSectionGetDof(section, points[1*2], &dofB);
assert(dofA == dofB);
PetscSectionGetOffset(section, points[0*2], &offA);
PetscSectionGetOffset(section, points[1*2], &offB);
myfunc(a[offA], a[offB]);
VecRestoreArray(u, &a);
This kind of calculation is used in TS Tutorial ex11.
Saving and Loading DMPlex Data with HDF5#
PETSc allows users to save/load DMPLEX
s representing meshes,
PetscSection
s representing data layouts on the meshes, and
Vec
s defined on the data layouts to/from an HDF5 file in
parallel, where one can use different number of processes for saving
and for loading.
Saving#
The simplest way to save DM
data is to use options for configuration.
This requires only the code
DMViewFromOptions(dm, NULL, "-dm_view");
VecViewFromOptions(vec, NULL, "-vec_view")
along with the command line options
$ ./myprog -dm_view hdf5:myprog.h5 -vec_view hdf5:myprog.h5::append
Options prefixes can be used to separately control the saving and loading of various fields.
However, the user can have finer grained control by explicitly creating the PETSc objects involved.
To save data to “example.h5” file, we can first create a PetscViewer
of type PETSCVIEWERHDF5
in FILE_MODE_WRITE
mode as:
PetscViewer viewer;
PetscViewerHDF5Open(PETSC_COMM_WORLD, "example.h5", FILE_MODE_WRITE, &viewer);
As dm
is a DMPLEX
object representing a mesh, we first give it a mesh name, “plexA”, and save it as:
PetscObjectSetName((PetscObject)dm, "plexA");
PetscViewerPushFormat(viewer, PETSC_VIEWER_HDF5_PETSC);
DMView(dm, viewer);
PetscViewerPopFormat(viewer);
The DMView()
call is shorthand for the following sequence
DMPlexTopologyView(dm, viewer);
DMPlexCoordinatesView(dm, viewer);
DMPlexLabelsView(dm, viewer);
If the mesh name is not explicitly set, the default name is used.
In the above PETSC_VIEWER_HDF5_PETSC
format was used to save the entire representation of the mesh.
This format also saves global point numbers attached to the mesh points.
In this example the set of all global point numbers is \(X = [0, 11)\).
The data layout, s
, needs to be wrapped in a DM
object for it to be saved.
Here, we create the wrapping DM
, sdm
, with DMClone()
, give it a dm name, “dmA”, attach s
to sdm
, and save it as:
DMClone(dm, &sdm);
PetscObjectSetName((PetscObject)sdm, "dmA");
DMSetLocalSection(sdm, s);
DMPlexSectionView(dm, viewer, sdm);
If the dm name is not explicitly set, the default name is to be used.
In the above, instead of using DMClone()
, one could also create a new DMSHELL
object to attach s
to.
The first argument of DMPlexSectionView()
is a DMPLEX
object that represents the mesh, and the third argument is a DM
object that carries the data layout that we would like to save.
They are, in general, two different objects, and the former carries a mesh name, while the latter carries a dm name.
These names are used to construct a group structure in the HDF5 file.
Note that the data layout points are associated with the mesh points, so each of them can also be tagged with a global point number in \(X\); DMPlexSectionView()
saves these tags along with the data layout itself, so that, when the mesh and the data layout are loaded separately later, one can associate the points in the former with those in the latter by comparing their global point numbers.
We now create a local vector assiciated with sdm
, e.g., as:
Vec vec;
DMGetLocalVector(sdm, &vec);
After setting values of vec
, we name it “vecA” and save it as:
PetscObjectSetName((PetscObject)vec, "vecA");
DMPlexLocalVectorView(dm, viewer, sdm, vec);
A global vector can be saved in the exact same way with trivial changes.
After saving, we destroy the PetscViewer
with:
PetscViewerDestroy(&viewer);
The output file “example.h5” now looks like the following:
$ h5dump --contents example.h5
HDF5 "example.h5" {
FILE_CONTENTS {
group /
group /topologies
group /topologies/plexA
group /topologies/plexA/dms
group /topologies/plexA/dms/dmA
dataset /topologies/plexA/dms/dmA/order
group /topologies/plexA/dms/dmA/section
dataset /topologies/plexA/dms/dmA/section/atlasDof
dataset /topologies/plexA/dms/dmA/section/atlasOff
group /topologies/plexA/dms/dmA/vecs
group /topologies/plexA/dms/dmA/vecs/vecA
dataset /topologies/plexA/dms/dmA/vecs/vecA/vecA
group /topologies/plexA/labels
group /topologies/plexA/topology
dataset /topologies/plexA/topology/cells
dataset /topologies/plexA/topology/cones
dataset /topologies/plexA/topology/order
dataset /topologies/plexA/topology/orientation
}
}
Saving in the new parallel HDF5 format#
Since PETSc 3.19, we offer a new format which supports parallel loading. To write in this format, you currently need to specify it explicitly using the option
-dm_plex_view_hdf5_storage_version 3.0.0
The storage version is stored in the file and set automatically when loading (described below). You can check the storage version of the HDF5 file with
$ h5dump -a /dmplex_storage_version example.h5
To allow for simple and efficient implementation, and good load balancing, the 3.0.0 format changes the way the mesh topology is stored.
Different strata (sets of mesh entities with an equal dimension; or vertices, edges, faces, and cells) are now stored separately.
The new structure of /topologies/<mesh_name>/topology
is following:
$ h5dump --contents example.h5
HDF5 "example.h5" {
FILE_CONTENTS {
...
group /topologies/plexA/topology
dataset /topologies/plexA/topology/permutation
group /topologies/plexA/topology/strata
group /topologies/plexA/topology/strata/0
dataset /topologies/plexA/topology/strata/0/cone_sizes
dataset /topologies/plexA/topology/strata/0/cones
dataset /topologies/plexA/topology/strata/0/orientations
group /topologies/plexA/topology/strata/1
dataset /topologies/plexA/topology/strata/1/cone_sizes
dataset /topologies/plexA/topology/strata/1/cones
dataset /topologies/plexA/topology/strata/1/orientations
group /topologies/plexA/topology/strata/2
dataset /topologies/plexA/topology/strata/2/cone_sizes
dataset /topologies/plexA/topology/strata/2/cones
dataset /topologies/plexA/topology/strata/2/orientations
group /topologies/plexA/topology/strata/3
dataset /topologies/plexA/topology/strata/3/cone_sizes
dataset /topologies/plexA/topology/strata/3/cones
dataset /topologies/plexA/topology/strata/3/orientations
}
}
Group /topologies/<mesh_name>/topology/strata
contains a subgroup for each stratum depth (dimension; 0 for vertices up to 3 for cells).
DAG points (mesh entities) have an implicit global numbering, given by the position in orientations
(or cone_sizes
) plus the stratum offset.
The stratum offset is given by a sum of lengths of all previous strata with respect to the order stored in /topologies/<mesh_name>/topology/permutation
.
This global numbering is compatible with the explicit numbering in dataset topology/order
of previous versions.
For a DAG point with index i
at depth s
, cone_sizes[i]
gives a size of this point’s cone (set of adjacent entities with depth s-1
).
Let o = sum(cone_sizes[0:i]])
(in Python syntax).
Points forming the cone are then given by cones[o:o+cone_sizes[i]]
(in numbering relative to the depth s-1
).
The orientation of the cone with respect to point i
is then stored in orientations[i]
.
Loading#
To load data from “example.h5” file, we create a PetscViewer
of type PETSCVIEWERHDF5
in FILE_MODE_READ
mode as:
PetscViewerHDF5Open(PETSC_COMM_WORLD, "example.h5", FILE_MODE_READ, &viewer);
We then create a DMPLEX
object, give it a mesh name, “plexA”, and load
the mesh as:
DMCreate(PETSC_COMM_WORLD, &dm);
DMSetType(dm, DMPLEX);
PetscObjectSetName((PetscObject)dm, "plexA");
PetscViewerPushFormat(viewer, PETSC_VIEWER_HDF5_PETSC);
DMLoad(dm, viewer);
PetscViewerPopFormat(viewer);
where PETSC_VIEWER_HDF5_PETSC
format was again used. The user can have more control by replace the single load call with
PetscSF sfO;
DMCreate(PETSC_COMM_WORLD, &dm);
DMSetType(dm, DMPLEX);
PetscObjectSetName((PetscObject)dm, "plexA");
PetscViewerPushFormat(viewer, PETSC_VIEWER_HDF5_PETSC);
DMPlexTopologyLoad(dm, viewer, &sfO);
DMPlexCoordinatesLoad(dm, viewer, sfO);
PetscViewerPopFormat(viewer);
The object returned by DMPlexTopologyLoad()
, sfO
, is a
PetscSF
that pushes forward \(X\) to the loaded mesh,
dm
; this PetscSF
is constructed with the global point
number tags that we saved along with the mesh points.
As the DMPLEX
mesh just loaded might not have a desired distribution,
it is common to redistribute the mesh for a better distribution using
DMPlexDistribute()
, e.g., as:
DM distributedDM;
PetscInt overlap = 1;
PetscSF sfDist, sf;
DMPlexDistribute(dm, overlap, &sfDist, &distributedDM);
if (distributedDM) {
DMDestroy(&dm);
dm = distributedDM;
PetscObjectSetName((PetscObject)dm, "plexA");
}
PetscSFCompose(sfO, sfDist, &sf);
PetscSFDestroy(&sfO);
PetscSFDestroy(&sfDist);
Note that the new DMPLEX
does not automatically inherit the mesh name,
so we need to name it “plexA” once again. sfDist
is a PetscSF
that pushes forward the loaded mesh to the redistributed mesh, so, composed
with sfO
, it makes the PetscSF
that pushes forward \(X\)
directly to the redistributed mesh, which we call sf
.
We then create a new DM
, sdm
, with DMClone()
, give it
a dm name, “dmA”, and load the on-disk data layout into sdm
as:
PetscSF globalDataSF, localDataSF;
DMClone(dm, &sdm);
PetscObjectSetName((PetscObject)sdm, "dmA");
DMPlexSectionLoad(dm, viewer, sdm, sf, &globalDataSF, &localDataSF);
where we could also create a new
DMSHELL
object instead of using DMClone()
.
Each point in the on-disk data layout being tagged with a global
point number in \(X\), DMPlexSectionLoad()
internally constructs a PetscSF
that pushes forward the on-disk
data layout to \(X\).
Composing this with sf
, DMPlexSectionLoad()
internally
constructs another PetscSF
that pushes forward the on-disk
data layout directly to the redistributed mesh. It then
reconstructs the data layout s
on the redistributed mesh and
attaches it to sdm
. The objects returned by this function,
globalDataSF
and localDataSF
, are PetscSF
s that can
be used to migrate the on-disk vector data into local and global
Vec
s defined on sdm
.
We now create a local vector assiciated with sdm
, e.g., as:
Vec vec;
DMGetLocalVector(sdm, &vec);
We then name vec
“vecA” and load the on-disk vector into vec
as:
PetscObjectSetName((PetscObject)vec, "vecA");
DMPlexLocalVectorLoad(dm, viewer, sdm, localDataSF, localVec);
where localDataSF
knows how to migrate the on-disk vector
data into a local Vec
defined on sdm
.
The on-disk vector can be loaded into a global vector associated with
sdm
in the exact same way with trivial changes.
After loading, we destroy the PetscViewer
with:
PetscViewerDestroy(&viewer);
The above infrastructure works seamlessly in distributed-memory parallel settings, in which one can even use different number of processes for saving and for loading; a more comprehensive example is found in DMPlex Tutorial ex12.
Metric-based mesh adaptation#
DMPlex supports mesh adaptation using the Riemannian metric framework. The idea is to use a Riemannian metric space within the mesher. The metric space dictates how mesh resolution should be distributed across the domain. Using this information, the remesher transforms the mesh such that it is a unit mesh when viewed in the metric space. That is, the image of each of its elements under the mapping from Euclidean space into the metric space has edges of unit length.
One of the main advantages of metric-based mesh adaptation is that it allows for fully anisotropic remeshing. That is, it provides a means of controlling the shape and orientation of elements in the adapted mesh, as well as their size. This can be particularly useful for advection-dominated and directionally-dependent problems.
See [Ala10] for further details on metric-based anisotropic mesh adaptation.
The two main ingredients for metric-based mesh adaptation are an input mesh
(i.e. the DMPLEX
) and a Riemannian metric. The implementation in PETSc assumes
that the metric is piecewise linear and continuous across elemental boundaries.
Such an object can be created using the routine
DMPlexMetricCreate(DM dm, PetscInt field, Vec *metric);
A metric must be symmetric positive-definite, so that distances may be properly defined. This can be checked using
This routine may also be used to enforce minimum and maximum tolerated metric magnitudes (i.e. cell sizes), as well as maximum anisotropy. These quantities can be specified using
DMPlexMetricSetMinimumMagnitude(DM dm, PetscReal h_min);
DMPlexMetricSetMaximumMagnitude(DM dm, PetscReal h_max);
DMPlexMetricSetMaximumAnisotropy(DM dm, PetscReal a_max);
or the command line arguments
-dm_plex_metric_h_min <h_min>
-dm_plex_metric_h_max <h_max>
-dm_plex_metric_a_max <a_max>
One simple way to combine two metrics is by simply averaging them entry-by-entry. Another is to intersect them, which amounts to choosing the greatest level of refinement in each direction. These operations are available in PETSc through the routines
However, before combining metrics, it is important that they are scaled in the same way. Scaling also allows the user to control the number of vertices in the adapted mesh (in an approximate sense). This is achieved using the \(L^p\) normalization framework, with the routine
There are two important parameters for the normalization: the normalization order \(p\) and the target metric complexity, which is analogous to the vertex count. They are controlled using
DMPlexMetricSetNormalizationOrder(DM dm, PetscReal p);
DMPlexMetricSetTargetComplexity(DM dm, PetscReal target);
or the command line arguments
-dm_plex_metric_p <p>
-dm_plex_metric_target_complexity <target>
Two different metric-based mesh adaptation tools are available in PETSc:
Mmg is a serial package, whereas ParMmg is the MPI version. Note that surface meshing is not currently supported and that ParMmg works only in three dimensions. Mmg can be used for both two and three dimensional problems. Pragmatic, Mmg and ParMmg may be specified by the command line arguments
-dm_adaptor pragmatic
-dm_adaptor mmg
-dm_adaptor parmmg
Once a metric has been constructed, it can be used to perform metric-based mesh adaptation using the routine
where bdLabel
and rgLabel
are boundary and interior tags to be
preserved under adaptation, respectively.
Footnotes
Frédéric Alauzet. Metric-based anisotropic mesh adaptation. https://pages.saclay.inria.fr/frederic.alauzet/cours/cea2010_V3.pdf, 2010.