From e27b8015f898ce829d90a57ec37cbff1118ecf64 Mon Sep 17 00:00:00 2001
From: Marcel Koch <marcel.koch@uni-muenster.de>
Date: Thu, 14 Feb 2019 16:30:17 +0100
Subject: [PATCH] separate c index array and vectorized index array
---
.../codegen/blockstructured/vectorization.py | 58 ++++++++++++++-----
1 file changed, 44 insertions(+), 14 deletions(-)
diff --git a/python/dune/codegen/blockstructured/vectorization.py b/python/dune/codegen/blockstructured/vectorization.py
index c3a4b81f..b45d92f8 100644
--- a/python/dune/codegen/blockstructured/vectorization.py
+++ b/python/dune/codegen/blockstructured/vectorization.py
@@ -338,38 +338,67 @@ def find_accumulation_inames(knl):
return inames
-def add_iname_array(knl, vec_iname):
- insns_with_macro_points = lp.find_instructions(knl, Tagged(vec_iname))
+def add_iname_array(knl, iname):
+ insns_with_macro_points = lp.find_instructions(knl, Tagged(iname))
if insns_with_macro_points:
- array_name = vec_iname + '_arr'
- vector_name = vec_iname + '_vec'
+ new_iname = knl.get_var_name_generator()(iname)
+
+ new_dom = BasicSet('{{ [{0}] : 0<={0}<{1} }}'.format(new_iname, get_form_option('number_of_blocks')))
+
+ array_name = iname + '_arr'
new_temporaries = dict()
new_temporaries[array_name] = DuneTemporaryVariable(array_name, managed=True,
shape=(get_form_option('number_of_blocks'),),
scope=lp.temp_var_scope.PRIVATE, dtype=np.float64,
- base_storage=vec_iname + '_buff',
+ base_storage=array_name + '_buff',
_base_storage_access_may_be_aliasing=True)
+
+ replacemap = dict()
+ replacemap[iname] = prim.Subscript(prim.Variable(array_name), (prim.Variable(iname),))
+
+ new_insns = [lp.Assignment(assignee=prim.Subscript(prim.Variable(array_name), (prim.Variable(new_iname),)),
+ expression=prim.Variable(new_iname),
+ id='init_{}_buffer'.format(array_name),
+ within_inames=frozenset({new_iname}), within_inames_is_final=True)]
+
+ for insn in knl.instructions:
+ if insn in insns_with_macro_points:
+ transformed_insn = insn.with_transformed_expressions(lambda expr: substitute(expr, replacemap))
+ new_insns.append(transformed_insn.copy(depends_on='init_{}_buffer'.format(array_name)))
+ else:
+ new_insns.append(insn)
+
+ knl = knl.copy(instructions=new_insns, domains=knl.domains + [new_dom],
+ temporary_variables=dict(**knl.temporary_variables, **new_temporaries))
+
+ return knl
+
+
+def add_vcl_iname_array(knl, iname, vec_iname, vcl_size):
+ insns_with_macro_points = lp.find_instructions(knl, And((Tagged(iname), Iname(vec_iname))))
+
+ if insns_with_macro_points:
+ iname_array = iname + '_arr'
+ vector_name = iname + '_vec{}'.format(vcl_size)
+
+ new_temporaries = dict()
new_temporaries[vector_name] = DuneTemporaryVariable(vector_name, managed=True,
shape=(get_form_option('number_of_blocks'),),
scope=lp.temp_var_scope.PRIVATE, dtype=np.float64,
- base_storage=vec_iname + '_buff',
+ base_storage=iname_array + '_buff',
_base_storage_access_may_be_aliasing=True)
silenced_warning = ["read_no_write({})".format(vector_name)]
- new_insns = [lp.Assignment(assignee=prim.Subscript(prim.Variable(array_name), (prim.Variable(vec_iname),)),
- expression=prim.Variable(vec_iname),
- id='init_{}_buffer'.format(vec_iname),
- within_inames=frozenset({vec_iname}), within_inames_is_final=True)]
-
replacemap = dict()
- replacemap[vec_iname] = prim.Subscript(prim.Variable(vector_name), (prim.Variable(vec_iname),))
+ replacemap[iname_array] = prim.Variable(vector_name)
+ new_insns = []
for insn in knl.instructions:
if insn in insns_with_macro_points:
transformed_insn = insn.with_transformed_expressions(lambda expr: substitute(expr, replacemap))
- new_insns.append(transformed_insn.copy(depends_on='init_{}_buffer'.format(vec_iname)))
+ new_insns.append(transformed_insn.copy(depends_on='init_{}_buffer'.format(iname_array)))
else:
new_insns.append(insn)
@@ -377,7 +406,8 @@ def add_iname_array(knl, vec_iname):
temporary_variables=dict(**knl.temporary_variables, **new_temporaries),
silenced_warnings=knl.silenced_warnings + silenced_warning)
- knl = lp.duplicate_inames(knl, [vec_iname], within=Id('init_{}_buffer'.format(vec_iname)))
+ knl = lp.split_array_axis(knl, (vector_name,), 0, vcl_size)
+ knl = lp.tag_array_axes(knl, (vector_name,), ('c', 'vec'))
return knl
--
GitLab