diff --git a/python/dune/perftool/pdelab/localoperator.py b/python/dune/perftool/pdelab/localoperator.py
index 467a81156f0f76084c566196b5fac1f7beaf95f1..7457dd834c081cd810f8701882a1cf2784fb3b58 100644
--- a/python/dune/perftool/pdelab/localoperator.py
+++ b/python/dune/perftool/pdelab/localoperator.py
@@ -501,10 +501,6 @@ def generate_kernel(integrals):
def extract_kernel_from_cache(tag):
- # Preprocess some instruction!
- from dune.perftool.sumfact.sumfact import expand_sumfact_kernels
- expand_sumfact_kernels(tag)
-
# Now extract regular loopy kernel components
from dune.perftool.loopy.target import DuneTarget
domains = [i for i in retrieve_cache_items("{} and domain".format(tag))]
diff --git a/python/dune/perftool/sumfact/sumfact.py b/python/dune/perftool/sumfact/sumfact.py
index 7f32ed52aeaf20c46669a9b182e31271d93344ba..059488f99d873be0e354e9817e795d33292a0e8d 100644
--- a/python/dune/perftool/sumfact/sumfact.py
+++ b/python/dune/perftool/sumfact/sumfact.py
@@ -59,178 +59,6 @@ import pymbolic.primitives as prim
from pytools import product
-class IndexFiddleMapper(IdentityMapper):
- def __init__(self, var, index, pos):
- assert isinstance(var, str)
- self.var = var
- self.index = index
- if isinstance(index, str):
- self.index = prim.Variable(index)
- self.pos = pos
-
- def map_variable(self, expr):
- if expr.name == self.var:
- return prim.Subscript(expr, (self.var,))
- else:
- return IdentityMapper.map_variable(self, expr)
-
- def map_subscript(self, expr):
- if expr.aggregate.name == self.var:
- ind = expr.index
- if not isinstance(ind, tuple):
- ind = (ind,)
- if self.pos is None:
- ind = ind + (self.index,)
- else:
- raise NotImplementedError
- return prim.Subscript(expr.aggregate, ind)
- else:
- return IdentityMapper.map_subscript(self, expr)
-
-
-def fiddle_in_index(expr, var, index, pos=None):
- return IndexFiddleMapper(var, index, pos)(expr)
-
-
-def default_resolution(insns):
- for insn in insns:
- if isinstance(insn, (lp.Assignment, lp.CallInstruction)):
- replace = {}
- deps = []
- for sumf in find_sumfact(insn.expression):
- # Maybe set up the input
- if sumf.setup_method:
- shape = product(mat.cols for mat in sumf.a_matrices)
- shape = (shape,)
- inp = get_buffer_temporary(sumf.buffer, shape=shape)
- silenced_warning('read_no_write({})'.format(inp))
-
- func, args = sumf.setup_method
- insn_dep = frozenset({func(inp, *args)})
- else:
- insn_dep = sumf.insn_dep
-
- # Call the sum factorization algorithm
- var, dep = sum_factorization_kernel(sumf.a_matrices, sumf.buffer, insn_dep, sumf.additional_inames)
- replace[sumf] = prim.Variable(var)
- deps.append(dep)
-
- if replace:
- built_instruction(insn.copy(expression=substitute(insn.expression, replace),
- depends_on=frozenset(*deps)
- )
- )
- if isinstance(insn, lp.Assignment):
- from dune.perftool.generation.loopy import expr_instruction_impl
- expr_instruction_impl.remove_by_value(insn)
- if isinstance(insn, lp.CallInstruction):
- from dune.perftool.generation.loopy import call_instruction_impl
- call_instruction_impl.remove_by_value(insn)
-
-
-def apply_sumfact_grad_vectorization(insns, stage):
- sumfact_kernels = []
- for insn in insns:
- if isinstance(insn, (lp.Assignment, lp.CallInstruction)):
- sumf = find_sumfact(insn.expression)
- if sumf:
- sumf, = sumf
- if sumf.stage == stage:
- sumfact_kernels.append(sumf)
-
- # Now apply some heuristics when to vectorize...
- if len(set(sumfact_kernels)) < 3:
- return
- else:
- # Vectorize!!!
- sumfact_kernels = sorted(sumfact_kernels, key=lambda s: s.preferred_interleaving_position)
- # Pad to 4
- if len(sumfact_kernels) < 4:
- sumfact_kernels.append(sumfact_kernels[0])
-
- # Determine a name for the buffer in use
- buffer = "_".join(sf.buffer for sf in sumfact_kernels)
- insn_dep = frozenset()
-
- # Maybe initialize the input buffer
- if sumfact_kernels[0].setup_method:
- assert stage == 1
- shape = product(mat.cols for mat in sumfact_kernels[0].a_matrices)
- shape = (shape, 4)
- initialize_buffer(buffer, base_storage_size=4 * shape[0])
- inp = get_buffer_temporary(buffer, shape=shape)
- silenced_warning('read_no_write({})'.format(inp))
-
- # Call the individual setup_methods
- for i, sumf in enumerate(sumfact_kernels):
- func, args = sumf.setup_method
- insn_dep = insn_dep.union({func(inp, *args, additional_indices=(i,))})
- else:
- assert stage == 3
- # No setup method defined. We need to make sure the input is correctly setup
- shape = tuple(mat.cols for mat in sumfact_kernels[0].a_matrices) + (4,)
- initialize_buffer(buffer, base_storage_size=4 * shape[0])
- dim_tags = ",".join("f" * (len(shape) - 1)) + ",c"
- inp = get_buffer_temporary(buffer, shape=shape, dim_tags=dim_tags)
-
- for i, sumf in enumerate(sumfact_kernels):
- assert sumf.input_temporary
- for insn in insns:
- if isinstance(insn, lp.Assignment):
- if get_pymbolic_basename(insn.assignee) == sumf.input_temporary:
- built_instruction(insn.copy(assignee=prim.Subscript(prim.Variable(inp), insn.assignee.index + (i,)),
- id=insn.id + "__{}".format(i)))
- insn_dep = insn_dep.union(insn.depends_on)
- from dune.perftool.generation.loopy import expr_instruction_impl
- expr_instruction_impl.remove_by_value(insn)
-
- # Determine the joined AMatrix
- large_a_matrices = []
- for i in range(len(sumfact_kernels[0].a_matrices)):
- assert len(set(tuple(sf.a_matrices[i].rows for sf in sumfact_kernels))) == 1
- assert len(set(tuple(sf.a_matrices[i].cols for sf in sumfact_kernels))) == 1
- large = LargeAMatrix(rows=sumfact_kernels[0].a_matrices[i].rows,
- cols=sumfact_kernels[0].a_matrices[i].cols,
- transpose=tuple(sf.a_matrices[i].transpose for sf in sumfact_kernels),
- derivative=tuple(sf.a_matrices[i].derivative for sf in sumfact_kernels),
- )
- large_a_matrices.append(large)
-
- # Join the instruction dependencies
- insn_dep = insn_dep.union(*tuple(sf.insn_dep for sf in sumfact_kernels))
-
- var, dep = sum_factorization_kernel(large_a_matrices, buffer, insn_dep, sumfact_kernels[0].additional_inames, add_vec_tag=True)
-
- for insn in insns:
- if isinstance(insn, (lp.Assignment, lp.CallInstruction)):
- sumfacts = find_sumfact(insn.expression)
- if sumfacts:
- sumf, = sumfacts
- if sumf.stage == stage:
- replace = {}
- replace[sumf] = prim.Variable(var)
- newexpr = substitute(insn.expression, replace)
- newexpr = fiddle_in_index(newexpr, var, sumf.preferred_interleaving_position)
- assert newexpr
- built_instruction(insn.copy(expression=newexpr,
- depends_on=dep,
- ))
-
- if isinstance(insn, lp.Assignment):
- from dune.perftool.generation.loopy import expr_instruction_impl
- expr_instruction_impl.remove_by_value(insn)
- if isinstance(insn, lp.CallInstruction):
- from dune.perftool.generation.loopy import call_instruction_impl
- call_instruction_impl.remove_by_value(insn)
-
-
-def expand_sumfact_kernels(tag):
- if get_option("vectorize_grads"):
- apply_sumfact_grad_vectorization([i for i in retrieve_cache_items("{} and instruction".format(tag))], 1)
- apply_sumfact_grad_vectorization([i for i in retrieve_cache_items("{} and instruction".format(tag))], 3)
- default_resolution(retrieve_cache_items("{} and instruction".format(tag)))
-
-
@iname
def _sumfact_iname(bound, _type, count):
name = "sf_{}_{}".format(_type, str(count))