diff --git a/python/dune/perftool/sumfact/accumulation.py b/python/dune/perftool/sumfact/accumulation.py
index 9566efb71e358dcaf346bd3a24b94858e3a56f26..a01fb8eac5db2b8045be31e472f4a8b909a18ffc 100644
--- a/python/dune/perftool/sumfact/accumulation.py
+++ b/python/dune/perftool/sumfact/accumulation.py
@@ -32,7 +32,7 @@ from dune.perftool.sumfact.tabulation import (basis_functions_per_direction,
from dune.perftool.sumfact.switch import (get_facedir,
get_facemod,
)
-from dune.perftool.sumfact.symbolic import SumfactKernel, SumfactKernelInputBase
+from dune.perftool.sumfact.symbolic import SumfactKernel, SumfactKernelOutputBase
from dune.perftool.ufl.modified_terminals import extract_modified_arguments
from dune.perftool.tools import get_pymbolic_basename
from dune.perftool.error import PerftoolError
@@ -81,21 +81,35 @@ def accum_iname(element, bound, i):
return sumfact_iname(bound, "accum{}".format(suffix))
-class AlreadyAssembledInput(SumfactKernelInputBase):
- def __init__(self, index):
- self.index = index
-
- def __eq__(self, other):
- return type(self) == type(other) and self.index == other.index
-
- def __repr__(self):
- return "AlreadyAssembledInput({})".format(self.index)
-
- def __hash__(self):
- return hash(self.index)
+class AccumulationOutput(SumfactKernelOutputBase, ImmutableRecord):
+ def __init__(self,
+ accumvar=None,
+ restriction=None,
+ test_element=None,
+ test_element_index=None,
+ trial_element=None,
+ trial_element_index=None,
+ ):
+ #TODO: Isnt accumvar superfluous in the presence of all the other infos?
+ ImmutableRecord.__init__(self,
+ accumvar=accumvar,
+ restriction=None,
+ test_element=test_element,
+ test_element_index=test_element_index,
+ trial_element=trial_element,
+ trial_element_index=trial_element_index,
+ )
- def __str__(self):
- return "Input{}".format(self.index[0])
+ @property
+ def within_inames(self):
+ if self.trial_element is None:
+ return ()
+ else:
+ from dune.perftool.sumfact.basis import lfs_inames
+ element = self.trial_element
+ if isinstance(element, MixedElement):
+ element = element.extract_component(self.trial_element_index)[1]
+ return lfs_inames(element, self.restriction)
class SumfactAccumulationInfo(ImmutableRecord):
@@ -266,16 +280,18 @@ def generate_accumulation_instruction(expr, visitor):
if priority is None:
priority = 3
+ output = AccumulationOutput(accumvar=accumvar,
+ restriction=(test_info.restriction, trial_info.restriction),
+ test_element=test_info.element,
+ test_element_index=test_info.element_index,
+ trial_element=trial_info.element,
+ trial_element_index=trial_info.element_index,
+ )
+
sf = SumfactKernel(matrix_sequence=matrix_sequence,
- restriction=(test_info.restriction, trial_info.restriction),
stage=3,
position_priority=priority,
- accumvar=accumvar,
- test_element=test_info.element,
- test_element_index=test_info.element_index,
- trial_element=trial_info.element,
- trial_element_index=trial_info.element_index,
- input=AlreadyAssembledInput(index=(test_info.element_index,)),
+ output=output,
predicates=predicates,
)
diff --git a/python/dune/perftool/sumfact/symbolic.py b/python/dune/perftool/sumfact/symbolic.py
index 09d597bba2ad3fd08621ed49a56be57864d0daa1..eb9df93108748e7bd68d583cad0aa8b6dbf1c3ad 100644
--- a/python/dune/perftool/sumfact/symbolic.py
+++ b/python/dune/perftool/sumfact/symbolic.py
@@ -24,12 +24,28 @@ class SumfactKernelInputBase(object):
return False
def realize(self, sf, dep, index=0):
- return frozenset()
+ return dep
def realize_direct(self, inames):
raise NotImplementedError
+class SumfactKernelOutputBase(object):
+ @property
+ def direct_output_is_possible(self):
+ return False
+
+ @property
+ def within_inames(self):
+ return ()
+
+ def realize(self, sf, dep):
+ return dep
+
+ def realize_direct(self):
+ raise NotImplementedError
+
+
class VectorSumfactKernelInput(SumfactKernelInputBase):
def __init__(self, inputs):
assert(isinstance(inputs, tuple))
@@ -82,14 +98,9 @@ class SumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable):
buffer=None,
stage=1,
position_priority=None,
- restriction=None,
insn_dep=frozenset(),
- input=None,
- accumvar=None,
- test_element=None,
- test_element_index=None,
- trial_element=None,
- trial_element_index=None,
+ input=SumfactKernelInputBase(),
+ output=SumfactKernelOutputBase(),
predicates=frozenset(),
):
"""Create a sum factorization kernel
@@ -165,11 +176,8 @@ class SumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable):
assert stage in (1, 3)
- if stage == 1:
- assert isinstance(input, SumfactKernelInputBase)
-
- if stage == 3:
- assert isinstance(restriction, tuple)
+ assert isinstance(input, SumfactKernelInputBase)
+ assert isinstance(output, SumfactKernelOutputBase)
assert isinstance(insn_dep, frozenset)
@@ -215,21 +223,28 @@ class SumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable):
def cache_key(self):
""" The cache key that can be used in generation magic
Any two sum factorization kernels having the same cache_key
- are realized simulatenously!
+ are realized simultaneously!
"""
- return (self.matrix_sequence, self.restriction, self.stage, self.buffer, self.test_element_index)
+ if self.buffer is None:
+ # During dry run, we return something unique to this kernel
+ return repr(self)
+ else:
+ # Later we identify parallely implemented kernels by the assigned buffer
+ return self.buffer
+# return (self.matrix_sequence, self.restriction, self.stage, self.buffer, self.test_element_index)
@property
- def input_key(self):
+ def inout_key(self):
""" A cache key for the input coefficients
Any two sum factorization kernels having the same input_key
- work on the same input coefficient
+ work on the same input coefficient (stage 1) or accumulate
+ into the same thing (stage 3)
"""
- return (self.input, self.restriction, self.accumvar, self.trial_element_index)
+ return (self.input, self.output)
@property
def group_name(self):
- return "sfgroup_{}_{}_{}_{}".format(self.input, self.restriction, self.accumvar, self.trial_element_index)
+ return "sfgroup_{}_{}".format(self.input, self.output)
#
# Some convenience methods to extract information about the sum factorization kernel
@@ -238,7 +253,7 @@ class SumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable):
def __lt__(self, other):
if self.parallel_key != other.parallel_key:
return self.parallel_key < other.parallel_key
- if self.input_key != other.input_key:
+ if self.inout_key != other.inout_key:
return self.input_key < other.input_key
if self.position_priority == other.position_priority:
return repr(self) < repr(other)
@@ -263,14 +278,7 @@ class SumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable):
@property
def within_inames(self):
- if self.trial_element is None:
- return ()
- else:
- from dune.perftool.sumfact.basis import lfs_inames
- element = self.trial_element
- if isinstance(element, MixedElement):
- element = element.extract_component(self.trial_element_index)[1]
- return lfs_inames(element, self.restriction)
+ return self.output.within_inames
def vec_index(self, sf):
""" Map an unvectorized sumfact kernel object to its position
@@ -553,8 +561,8 @@ class VectorizedSumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable)
return (tuple(k.cache_key for k in self.kernels), self.buffer)
@property
- def input_key(self):
- return tuple(k.input_key for k in self.kernels)
+ def inout_key(self):
+ return tuple(k.inout_key for k in self.kernels)
@property
def group_name(self):
@@ -570,7 +578,7 @@ class VectorizedSumfactKernel(SumfactKernelBase, ImmutableRecord, prim.Variable)
def horizontal_index(self, sf):
for i, k in enumerate(self.kernels):
- if sf.input_key == k.input_key:
+ if sf.inout_key == k.inout_key:
if tuple(mat.derivative for mat in sf.matrix_sequence) == tuple(mat.derivative for mat in k.matrix_sequence):
return i
diff --git a/python/dune/perftool/sumfact/vectorization.py b/python/dune/perftool/sumfact/vectorization.py
index e4a044edf0e62b8b2176efe4755a21617f0fcd8c..8d0081dbf4739005c7fb9c5ffc9fa7aa48806c93 100644
--- a/python/dune/perftool/sumfact/vectorization.py
+++ b/python/dune/perftool/sumfact/vectorization.py
@@ -284,8 +284,8 @@ def _level2_optimal_vectorization_strategy_generator(sumfacts, width, qp, alread
yielded = False
# Find the number of input coefficients we can work on
- keys = frozenset(sf.input_key for sf in sumfacts)
- inputkey_sumfacts = [tuple(sorted(filter(lambda sf: sf.input_key == key, sumfacts))) for key in keys]
+ keys = frozenset(sf.inout_key for sf in sumfacts)
+ inoutkey_sumfacts = [tuple(sorted(filter(lambda sf: sf.inout_key == key, sumfacts))) for key in keys]
for parallel in (1, 2):
if parallel == 2 and next(iter(sumfacts)).stage == 3:
@@ -294,7 +294,7 @@ def _level2_optimal_vectorization_strategy_generator(sumfacts, width, qp, alread
it.permutations(range(len(keys)), parallel)):
horizontal = 1
while horizontal <= width // parallel:
- combo = sum((inputkey_sumfacts[part][:horizontal] for part in which), ())
+ combo = sum((inoutkey_sumfacts[part][:horizontal] for part in which), ())
vecdict = get_vectorization_dict(combo, width // (horizontal * parallel), horizontal * parallel, qp)
horizontal *= 2