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FusionContractorArrayContext update + TP transformations #13

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72060f4
update FusionContractorArrayContext
a-alveyblanc Feb 17, 2025
535a760
remove unneeded tag check
a-alveyblanc Feb 23, 2025
9020e06
add tensor-product metadata to meshmode from grudge
a-alveyblanc Feb 23, 2025
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218 changes: 191 additions & 27 deletions meshmode/array_context.py
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Original file line number Diff line number Diff line change
Expand Up @@ -47,6 +47,14 @@
_PytestPytatoPyOpenCLArrayContextFactory,
register_pytest_array_context_factory,
)
from meshmode.transform_metadata import (
FaceMassOperatorTag,
MassInverseOperatorTag,
TensorProductDOFAxisTag,
TensorProductMassInverseOperatorTag,
TensorProductOperatorAxisTag,
TensorProductOperatorTag
)
from loopy.translation_unit import for_each_kernel

from loopy.tools import memoize_on_disk
Expand Down Expand Up @@ -901,6 +909,8 @@
# transforming it.
orig_knl = knl

import time

knl = _fuse_loops_over_a_discr_entity(knl, DiscretizationFaceAxisTag,
"iface",
False,
Expand All @@ -915,6 +925,7 @@
"idof",
False,
orig_knl)

knl = _fuse_loops_over_a_discr_entity(knl, DiscretizationDimAxisTag,
"idim",
False,
Expand All @@ -924,15 +935,29 @@
"iface",
True,
orig_knl)

knl = _fuse_loops_over_a_discr_entity(knl, DiscretizationDOFAxisTag,
"idof",
True,
orig_knl)

knl = _fuse_loops_over_a_discr_entity(knl, DiscretizationDimAxisTag,
"idim",
True,
orig_knl)

knl = _fuse_loops_over_a_discr_entity(knl,
TensorProductDOFAxisTag,
"idof_tp",
False,
orig_knl)

knl = _fuse_loops_over_a_discr_entity(knl,
TensorProductDOFAxisTag,
"idof_tp",
True,
orig_knl)

return knl


Expand Down Expand Up @@ -1028,7 +1053,10 @@
for iname in kernel.all_inames()
if (kernel
.inames[iname]
.tags_of_type(DiscretizationDOFAxisTag))
.tags_of_type(DiscretizationDOFAxisTag) or
kernel
.inames[iname]
.tags_of_type(TensorProductDOFAxisTag))
}
iface_inames = {iname
for iname in kernel.all_inames()
Expand Down Expand Up @@ -1058,6 +1086,9 @@
raise NotImplementedError(f"The <iel> loop {insn.within_inames}"
" does not appear as a singly nested"
" loop.")

# {{{ <iel, idof> loop (simplicial)

elif ((len(insn.within_inames) == 2)
and (len(insn.within_inames & iel_inames) == 1)
and (len(insn.within_inames & idof_inames) == 1)):
Expand All @@ -1068,9 +1099,41 @@
for dof_insn in kernel.iname_to_insns()[idof]):
pass
else:
for dof_insn in kernel.iname_to_insns()[idof]:
if iel not in kernel.id_to_insn[dof_insn].within_inames:
print(f"_get_iel_to_idofs: {str(kernel.id_to_insn[dof_insn])=}")
raise NotImplementedError("The <iel,idof> loop "
f"'{insn.within_inames}' has the idof-loop"
" that's not nested within the iel-loop.")
# }}}

# {{{ <iel, idof, ...> loop (tensor product)

elif ((len(insn.within_inames) > 2)
and (len(insn.within_inames & iel_inames) == 1)
and (len(insn.within_inames & idof_inames) > 1)):

iel, = insn.within_inames & iel_inames
for idof in insn.within_inames & idof_inames:
iel_to_idofs[iel].add(idof)

if all((iel in kernel.id_to_insn[dof_insn].within_inames)
for dof_insn in kernel.iname_to_insns()[idof]):
pass
else:
for dof_insn in kernel.iname_to_insns()[idof]:
if iel not in kernel.id_to_insn[dof_insn].within_inames:
print("_get_iel_to_idofs: "
f"{str(kernel.id_to_insn[dof_insn])=}")
raise NotImplementedError("The <iel,idof> loop "
f"'{insn.within_inames}' has the "
"idof-loop that's not nested "
"within the iel-loop.")

# }}}

# {{{ <iel, idof, iface> loop

elif ((len(insn.within_inames) > 2)
and (len(insn.within_inames & iel_inames) == 1)
and (len(insn.within_inames & idof_inames) == 1)
Expand All @@ -1086,7 +1149,11 @@
else:
raise NotImplementedError("Could not fit into <iel,idof,iface>"
" loop nest pattern.")

# }}}

else:
print(f"_get_iel_to_idofs: {str(insn)=}")
raise NotImplementedError(f"Cannot fit loop nest '{insn.within_inames}'"
" into known set of loop-nest patterns.")

Expand Down Expand Up @@ -1126,8 +1193,10 @@


def _prepare_kernel_for_parallelization(kernel):
from meshmode.transform_metadata import TensorProductDOFAxisTag
discr_tag_to_prefix = {DiscretizationElementAxisTag: "iel",
DiscretizationDOFAxisTag: "idof",
TensorProductDOFAxisTag: "idof_tp",
DiscretizationDimAxisTag: "idim",
DiscretizationAmbientDimAxisTag: "idim",
DiscretizationTopologicalDimAxisTag: "idim",
Expand All @@ -1136,7 +1205,7 @@
import loopy as lp
from loopy.match import ObjTagged

# A mapping from inames that the instruction accesss to

Check warning on line 1208 in meshmode/array_context.py

View workflow job for this annotation

GitHub Actions / Typos 

"accesss" should be "access".
# the instructions ids within that iname.
ensm_buckets = {}
vng = kernel.get_var_name_generator()
Expand Down Expand Up @@ -1252,11 +1321,13 @@


from pytools.persistent_dict import WriteOncePersistentDict
from pytato.analysis import PytatoKeyBuilder
from pytato.analysis import PytatoKeyBuilder, get_num_nodes

class FusionContractorArrayContext(
SingleGridWorkBalancingPytatoArrayContext):

t_units = []

def __init__(
self, queue: "cl.CommandQueue", allocator=None, *,
use_memory_pool: Optional[bool] = None,
Expand All @@ -1282,6 +1353,8 @@
def transform_dag(self, dag):
import pytato as pt

initial_node_count = get_num_nodes(dag)

# {{{ Remove FEMEinsumTags that might have been propagated

# TODO: Is this too hacky?
Expand Down Expand Up @@ -1355,6 +1428,28 @@
with ProcessLogger(logger, "transform_dag.deduplicate_data_wrappers"):
dag = pt.transform.deduplicate_data_wrappers(dag)

# {{{ freeze and thaw tensor product operators

# FIXME: this is a hack
def thaw_freeze_tp_operators(expr):
if isinstance(expr, pt.Einsum) and \
expr.tags_of_type(TensorProductOperatorTag):
ref_mass_inv, stiff_t = expr.args
data = self.to_numpy(ref_mass_inv) @ self.to_numpy(stiff_t)
axis_tags = (TensorProductOperatorAxisTag(),)
return (self.from_numpy(data).copy(
axes=(
pt.Axis(tags=frozenset(axis_tags)),
pt.Axis(tags=frozenset(axis_tags))
)
).tagged(TensorProductOperatorTag())
.tagged(pt.tags.PrefixNamed("diff_op")))
return expr

dag = pt.transform.map_and_copy(dag, thaw_freeze_tp_operators)

# }}}

# {{{ get rid of copies for different views of a cl-array

def eliminate_reshapes_of_data_wrappers(ary):
Expand All @@ -1379,12 +1474,24 @@
expr,
"ifj,fej,fej->ei")):
mat, jac, vec = expr.args
return (pt.einsum("ifj,fej,fej->ei",
mat,
jac,
vec.tagged(pt.tags.ImplStored()))
.tagged((pt.tags.ImplStored(),
pt.tags.PrefixNamed("face_mass"))))
if mat.tags_of_type(FaceMassOperatorTag):
return (pt.einsum("ifj,fej,fej->ei",
mat,
jac,
vec.tagged(pt.tags.ImplStored()))
.tagged((pt.tags.ImplStored(),
pt.tags.PrefixNamed("face_mass_result"))))
elif (isinstance(expr, pt.Einsum)
and pt.analysis.is_einsum_similar_to_subscript(
expr,
"ifj,fej->ei")):
mat, vec = expr.args
if mat.tags_of_type(FaceMassOperatorTag):
return (pt.einsum("ifj,fej->ei",
mat,
vec.tagged(pt.tags.ImplStored()))
.tagged((pt.tags.ImplStored(),
pt.tags.PrefixNamed("face_mass_result"))))
else:
return expr

Expand All @@ -1398,17 +1505,41 @@
# {{{ materialize inverse mass inputs

def materialize_inverse_mass_inputs(expr):
def is_tp_einsum(expr):
if pt.analysis.is_einsum_similar_to_subscript(
expr, "il,eljk->eijk"):
return True
elif pt.analysis.is_einsum_similar_to_subscript(
expr, "jl,eilk->eijk"):
return True
elif pt.analysis.is_einsum_similar_to_subscript(
expr, "kl,eijl->eijk"):
return True
return False

if (isinstance(expr, pt.Einsum)
and pt.analysis.is_einsum_similar_to_subscript(
expr,
"ei,ij,ej->ei")):
arg1, arg2, arg3 = expr.args
if not arg3.tags_of_type(pt.tags.PrefixNamed):
arg3 = arg3.tagged(pt.tags.PrefixNamed("mass_inv_inp"))
if not arg3.tags_of_type(pt.tags.ImplStored):
arg3 = arg3.tagged(pt.tags.ImplStored())

return expr.copy(args=(arg1, arg2, arg3))
"ij,ej->ei")):
mat, vec = expr.args
if mat.tags_of_type(MassInverseOperatorTag):
if not vec.tags_of_type(pt.tags.PrefixNamed):
vec = vec.tagged(pt.tags.PrefixNamed("input_vec"))
if not vec.tags_of_type(pt.tags.ImplStored):
vec = vec.tagged(pt.tags.ImplStored())

return expr.copy(args=(mat, vec))

elif (isinstance(expr, pt.Einsum) and is_tp_einsum(expr)):
mat, vec = expr.args
if mat.tags_of_type(TensorProductMassInverseOperatorTag):
if not vec.tags_of_type(pt.tags.PrefixNamed):
vec = vec.tagged(pt.tags.PrefixNamed("input_vec_tp"))
if not vec.tags_of_type(pt.tags.ImplStored):
vec = vec.tagged(pt.tags.ImplStored())

return expr.copy(args=(mat, vec))

else:
return expr

Expand Down Expand Up @@ -1638,6 +1769,15 @@

# }}}

final_node_count = get_num_nodes(dag)
with ProcessLogger(logger, "final node count"):
logger.info(
"Final DAG size: %d nodes, started with %d nodes, %s %d nodes",
final_node_count, initial_node_count,
("added" if initial_node_count < final_node_count else
"removed"), abs(initial_node_count - final_node_count)
)

return dag

def transform_loopy_program(self, t_unit):
Expand All @@ -1660,6 +1800,7 @@
# from loopy.transform.instruction import simplify_indices
# t_unit = simplify_indices(t_unit)

knl = t_unit.default_entrypoint

logger.info(f"Transforming kernel '{knl.name}' with {len(knl.instructions)} statements.")

Expand Down Expand Up @@ -1820,7 +1961,8 @@
t_unit = t_unit.with_kernel(knl)
del knl

if False and t_unit.default_entrypoint.tags_of_type(FromArrayContextCompile):
if False and t_unit.default_entrypoint.tags_of_type(
FromArrayContextCompile):
# FIXME: Enable this branch, WIP for now and hence disabled it.
from loopy.match import ObjTagged
import feinsum as fnsm
Expand Down Expand Up @@ -1863,17 +2005,40 @@
knl = t_unit.default_entrypoint
for iel, idofs in sorted(iel_to_idofs.items()):
if idofs:
nunit_dofs = {knl.get_constant_iname_length(idof)
for idof in idofs}
idof, = idofs
if len(idofs) == 1:
nunit_dofs = {
knl.get_constant_iname_length(idof)
for idof in idofs
}
l_one, l_zero = _get_group_size_for_dof_array_loop(
nunit_dofs)

idof, = idofs

knl = lp.split_iname(knl, iel, l_one,
inner_tag="l.1",
outer_tag="g.0")
knl = lp.split_iname(knl, idof, l_zero,
inner_tag="for",
outer_tag="l.0")

l_one_size, l_zero_size = _get_group_size_for_dof_array_loop(
nunit_dofs)
else:
def idof_tp_sort_key(idof):
tag, = knl.inames[idof].tags_of_type(
TensorProductDOFAxisTag
)
return tag.iaxis

inames_to_tags = {iel: "g.0"}
inames_to_tags.update({
idof: f"l.{i}"
for i, idof in enumerate(
sorted(idofs, key=idof_tp_sort_key)[:-1]
)
})

knl = lp.tag_inames(knl, inames_to_tags)

knl = lp.split_iname(knl, iel, l_one_size,
inner_tag="l.1", outer_tag="g.0")
knl = lp.split_iname(knl, idof, l_zero_size,
inner_tag="l.0", outer_tag="unr")
else:
knl = lp.split_iname(knl, iel, 32,
outer_tag="g.0", inner_tag="l.0")
Expand All @@ -1886,5 +2051,4 @@

return t_unit


# vim: foldmethod=marker
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