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Fix quadratic cost in adaptive mesh refinement's coarse/fine cell-map construction #5326

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pbrubeck merged 4 commits into from
Aug 6, 2026
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Fix quadratic cost in adaptive mesh refinement's coarse/fine cell-map construction #5326

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30b10a5
Fix quadratic cost in adaptive mesh refinement's coarse/fine cell-map…
pbrubeck Aug 5, 2026
c2c5f05
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pbrubeck Aug 5, 2026
b70f7b7
Update adaptive_multigrid demo output for post-#5215 behaviour
pbrubeck Aug 5, 2026
62be0b7
Trim comment in adaptive_parent_child_cell_maps to the present approach
pbrubeck Aug 5, 2026
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24 changes: 12 additions & 12 deletions demos/adaptive_multigrid/adaptive_multigrid.py.rst
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Expand Up @@ -235,18 +235,18 @@ Moreover, the multigrid iteration count is robust to the level of refinement ::
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======== ================

A runnable python version of this demo can be found :demo:`here<adaptive_multigrid.py>`.
Expand Down
68 changes: 38 additions & 30 deletions firedrake/adapt.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
from firedrake.functionspace import FunctionSpace
from firedrake.mesh import Mesh, DISTRIBUTION_PARAMETERS_NOOP
from firedrake.netgen import _transfer_high_order_coordinates
from firedrake.petsc import PETSc


# PETSc's DMAdaptFlag value requesting refinement, for the adapt label.
Expand All @@ -28,20 +29,22 @@ def _adapt_marked_cells(mesh, cell_marker):
dm = mesh.topology_dm
ncoarse = mesh.cell_set.size

dm.createLabel(ADAPT_LABEL)
adapt_label = dm.getLabel(ADAPT_LABEL)
adapt_indicator = np.zeros(cell_marker.dat.data_ro_with_halos.shape, dtype=IntType)
adapt_indicator[:ncoarse] = cell_marker.dat.data_ro.real > 0
dmcommon.mark_points_with_function_array(
dm, cell_marker.function_space().dm.getSection(), 0,
adapt_indicator, adapt_label, DM_ADAPT_REFINE,
)
with PETSc.Log.Event("AdaptiveRefine: mark cells"):
dm.createLabel(ADAPT_LABEL)
adapt_label = dm.getLabel(ADAPT_LABEL)
adapt_indicator = np.zeros(cell_marker.dat.data_ro_with_halos.shape, dtype=IntType)
adapt_indicator[:ncoarse] = cell_marker.dat.data_ro.real > 0
dmcommon.mark_points_with_function_array(
dm, cell_marker.function_space().dm.getSection(), 0,
adapt_indicator, adapt_label, DM_ADAPT_REFINE,
)

parameters = {"dm_plex_transform_type": "refine_sbr"}
try:
# options_prefix="" is essential
with petsctools.inserted_options(parameters=parameters, options_prefix=""):
new_dm = dm.adaptLabel(ADAPT_LABEL)
with PETSc.Log.Event("AdaptiveRefine: adaptLabel"):
new_dm = dm.adaptLabel(ADAPT_LABEL)
finally:
# Ensure the temporary label is removed even if adaptation fails
dm.removeLabel(ADAPT_LABEL)
Expand Down Expand Up @@ -99,33 +102,37 @@ def refine_marked_elements(mesh, cell_marker):
num_refinements = max(int(np.rint(num_refinements)), 1)

coarse_dm = mesh.topology_dm
impl.set_adaptive_parent_label(coarse_dm, mesh._cell_numbering, PARENT_LABEL)
with PETSc.Log.Event("AdaptiveRefine: set_adaptive_parent_label"):
impl.set_adaptive_parent_label(coarse_dm, mesh._cell_numbering, PARENT_LABEL)

current_mesh = mesh
current_mark = cell_marker
try:
for ref in range(num_refinements):
new_dm = _adapt_marked_cells(current_mesh, current_mark)
current_mesh = Mesh(
new_dm,
dim=mesh.geometric_dimension,
reorder=False,
distribution_parameters=DISTRIBUTION_PARAMETERS_NOOP,
comm=mesh.comm,
tolerance=mesh.tolerance,
)
coarse_to_fine, fine_to_coarse = impl.adaptive_parent_child_cell_maps(
coarse_dm, new_dm, current_mesh._cell_numbering, PARENT_LABEL
)
with PETSc.Log.Event("AdaptiveRefine: Mesh()"):
current_mesh = Mesh(
new_dm,
dim=mesh.geometric_dimension,
reorder=False,
distribution_parameters=DISTRIBUTION_PARAMETERS_NOOP,
comm=mesh.comm,
tolerance=mesh.tolerance,
)
with PETSc.Log.Event("AdaptiveRefine: adaptive_parent_child_cell_maps"):
coarse_to_fine, fine_to_coarse = impl.adaptive_parent_child_cell_maps(
coarse_dm, new_dm, current_mesh._cell_numbering, PARENT_LABEL
)
if ref < num_refinements - 1:
# A cell asking for n refinements stays marked until n rounds
# have happened, so its descendants inherit n minus the number
# of rounds so far.
ancestor = fine_to_coarse[:, 0]
refined = ancestor >= 0
current_mark = Function(FunctionSpace(current_mesh, "DG", 0))
current_mark.dat.data_wo[refined] = \
cell_marker.dat.data_ro[ancestor[refined]] - (ref + 1)
with PETSc.Log.Event("AdaptiveRefine: re-mark"):
# A cell asking for n refinements stays marked until n rounds
# have happened, so its descendants inherit n minus the number
# of rounds so far.
ancestor = fine_to_coarse[:, 0]
refined = ancestor >= 0
current_mark = Function(FunctionSpace(current_mesh, "DG", 0))
current_mark.dat.data_wo[refined] = \
cell_marker.dat.data_ro[ancestor[refined]] - (ref + 1)
finally:
# Ensure the temporary label is removed even if adaptation fails
coarse_dm.removeLabel(PARENT_LABEL)
Expand All @@ -134,7 +141,8 @@ def refine_marked_elements(mesh, cell_marker):
if hasattr(mesh, "netgen_mesh"):
order = mesh.coordinates.function_space().ufl_element().degree()
if order > 1:
final_mesh = _transfer_high_order_coordinates(mesh, final_mesh, order)
with PETSc.Log.Event("AdaptiveRefine: recurve netgen coords"):
final_mesh = _transfer_high_order_coordinates(mesh, final_mesh, order)

final_mesh.topology_dm.removeLabel(PARENT_LABEL)
final_mesh.adaptive_parent = mesh
Expand Down
26 changes: 20 additions & 6 deletions firedrake/cython/mgimpl.pyx
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Expand Up @@ -296,8 +296,10 @@ def adaptive_parent_child_cell_maps(PETSc.DM coarse_dm,
cdef:
PetscInt ncoarse = num_owned_cells(coarse_dm)
PetscInt nfine = num_owned_cells(fine_dm)
PetscInt cStart, cEnd, c, off, parent, max_children
PetscInt cStart, cEnd, c, off, parent, i, stratum_size, max_children
DMLabel parent_label = NULL
PETSc.PetscIS stratum_is = NULL
const PetscInt *stratum_points = NULL
PetscInt[::1] child_counts
PetscInt[:, ::1] coarse_to_fine
PetscInt[:, ::1] fine_to_coarse
Expand All @@ -307,14 +309,26 @@ def adaptive_parent_child_cell_maps(PETSc.DM coarse_dm,
fine_to_coarse = np.full((nfine, 1), -1, dtype=IntType)
child_counts = np.zeros(ncoarse, dtype=IntType)
cStart, cEnd = fine_dm.getHeightStratum(0)
for c in range(cStart, cEnd):
CHKERR(PetscSectionGetOffset(fine_cell_numbering.sec, c, &off))
if not (0 <= off < nfine):
# Walking by stratum (coarse cell) resolves each one through PETSc's O(1)
# value -> stratum hash map and touches every fine cell exactly once, for
# O(nfine + ncoarse) overall.
for parent in range(ncoarse):
CHKERR(DMLabelGetStratumSize(parent_label, parent, &stratum_size))
if stratum_size <= 0:
continue
CHKERR(DMLabelGetValue(parent_label, c, &parent))
if 0 <= parent < ncoarse:
CHKERR(DMLabelGetStratumIS(parent_label, parent, &stratum_is))
CHKERR(ISGetIndices(stratum_is, &stratum_points))
for i in range(stratum_size):
c = stratum_points[i]
if not (cStart <= c < cEnd):
continue
CHKERR(PetscSectionGetOffset(fine_cell_numbering.sec, c, &off))
if not (0 <= off < nfine):
continue
fine_to_coarse[off, 0] = parent
child_counts[parent] += 1
CHKERR(ISRestoreIndices(stratum_is, &stratum_points))
CHKERR(ISDestroy(&stratum_is))

# coarse_to_fine is rectangular, so every coarse cell's row must be wide
# enough for its most prolific sibling. Different coarse cells can be
Expand Down
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