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Commit 4819d3f5 authored by Mark Florisson's avatar Mark Florisson
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Disallow nested parallel blocks and propagate sharing attributes

parent 84ee26c5
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Showing with 178 additions and 71 deletions
Cython/Compiler/Nodes.py
View file @ 4819d3f5
......@@ -5764,36 +5764,101 @@ class ParallelStatNode(StatNode, ParallelNode):
def __init__(self, pos, **kwargs):
super(ParallelStatNode, self).__init__(pos, **kwargs)
# All assignments in this scope
self.assignments = kwargs.get('assignments') or {}
# Insertion point before the outermost parallel section
self.before_parallel_section_point = None
# Insertion point after the outermost parallel section
self.post_parallel_section_point = None
def analyse_expressions(self, env):
self.body.analyse_expressions(env)
# All seen closure cnames and their temporary cnames
self.seen_closure_vars = set()
# Dict of variables that should be declared (first|last|)private or
# reduction { Entry: op }. If op is not None, it's a reduction.
self.privates = {}
def analyse_declarations(self, env):
super(ParallelStatNode, self).analyse_declarations(env)
self.body.analyse_declarations(env)
def lookup_assignment(self, entry):
def analyse_expressions(self, env):
self.body.analyse_expressions(env)
def analyse_sharing_attributes(self, env):
"""
Return an assignment's pos and operator. If the parent has the
assignment, return the parent's assignment, otherwise our own.
Analyse the privates for this block and set them in self.privates.
This should be called in a post-order fashion during the
analyse_expressions phase
"""
parent_assignment = self.parent and self.parent.lookup_assignment(entry)
return parent_assignment or self.assignments.get(entry)
for entry, (pos, op) in self.assignments.iteritems():
if self.is_private(entry):
self.propagate_var_privatization(entry, op)
def is_private(self, entry):
"""
True if this scope should declare the variable private, lastprivate
or reduction.
"""
parent_or_our_entry = self.lookup_assignment(entry)
our_entry = self.assignments.get(entry)
return (self.is_parallel or
(self.parent and entry not in self.parent.privates))
def propagate_var_privatization(self, entry, op):
"""
Propagate the sharing attributes of a variable. If the privatization is
determined by a parent scope, done propagate further.
If we are a prange, we propagate our sharing attributes outwards to
other pranges. If we are a prange in parallel block and the parallel
block does not determine the variable private, we propagate to the
parent of the parent. Recursion stops at parallel blocks, as they have
no concept of lastprivate or reduction.
So the following cases propagate:
sum is a reduction for all loops:
for i in prange(n):
for j in prange(n):
for k in prange(n):
sum += i * j * k
sum is a reduction for both loops, local_var is private to the
parallel with block:
for i in prange(n):
with parallel:
local_var = ... # private to the parallel
for j in prange(n):
sum += i * j
This does not propagate to the outermost prange:
#pragma omp parallel for lastprivate(i)
for i in prange(n):
#pragma omp parallel private(j, sum)
with parallel:
#pragma omp parallel
with parallel:
#pragma omp for lastprivate(j) reduction(+:sum)
for j in prange(n):
sum += i
# sum and j are well-defined here
# sum and j are undefined here
# sum and j are undefined here
"""
self.privates[entry] = op
if self.is_prange:
if not self.is_parallel and entry not in self.parent.assignments:
# Parent is a parallel with block
parent = self.parent.parent
else:
parent = self.parent
return self.is_parallel or parent_or_our_entry == our_entry
if parent:
parent.propagate_var_privatization(entry, op)
def _allocate_closure_temp(self, code, entry):
"""
......@@ -5803,11 +5868,19 @@ class ParallelStatNode(StatNode, ParallelNode):
if self.parent:
return self.parent._allocate_closure_temp(code, entry)
if entry.cname in self.seen_closure_vars:
return entry.cname
cname = code.funcstate.allocate_temp(entry.type, False)
# Add both the actual cname and the temp cname, as the actual cname
# will be replaced with the temp cname on the entry
self.seen_closure_vars.add(entry.cname)
self.seen_closure_vars.add(cname)
self.modified_entries.append((entry, entry.cname))
code.putln("%s = %s;" % (cname, entry.cname))
entry.cname = cname
return cname
def declare_closure_privates(self, code):
"""
......@@ -5821,19 +5894,18 @@ class ParallelStatNode(StatNode, ParallelNode):
after the parallel section. This kind of copying should be done only
in the outermost parallel section.
"""
self.privates = {}
self.modified_entries = []
for entry, (pos, op) in self.assignments.iteritems():
cname = entry.cname
if entry.from_closure or entry.in_closure:
cname = self._allocate_closure_temp(code, entry)
if self.is_private(entry):
self.privates[cname] = op
self._allocate_closure_temp(code, entry)
def release_closure_privates(self, code):
"Release any temps used for variables in scope objects"
"""
Release any temps used for variables in scope objects. As this is the
outermost parallel block, we don't need to delete the cnames from
self.seen_closure_vars
"""
for entry, original_cname in self.modified_entries:
code.putln("%s = %s;" % (original_cname, entry.cname))
code.funcstate.release_temp(entry.cname)
......@@ -5847,15 +5919,23 @@ class ParallelWithBlockNode(ParallelStatNode):
nogil_check = None
def analyse_expressions(self, env):
super(ParallelWithBlockNode, self).analyse_expressions(env)
self.analyse_sharing_attributes(env)
def generate_execution_code(self, code):
self.declare_closure_privates(code)
code.putln("#ifdef _OPENMP")
code.put("#pragma omp parallel ")
code.putln(' '.join(["private(%s)" % e.cname
for e in self.assignments
if self.is_private(e)]))
code.putln("#endif")
if self.privates:
code.put(
'private(%s)' % ', '.join([e.cname for e in self.privates]))
code.putln("")
code.putln("#endif /* _OPENMP */")
code.begin_block()
self.body.generate_execution_code(code)
code.end_block()
......@@ -5924,11 +6004,18 @@ class ParallelRangeNode(ParallelStatNode):
return
self.target.analyse_target_types(env)
self.index_type = self.target.type
if self.index_type.is_pyobject:
# nogil_check will catch this, for now, assume a valid type
if not self.target.type.is_numeric:
# Not a valid type, assume one for now anyway
if not self.target.type.is_pyobject:
# nogil_check will catch the is_pyobject case
error(self.target.pos,
"Must be of numeric type, not %s" % self.target.type)
self.index_type = PyrexTypes.c_py_ssize_t_type
else:
self.index_type = self.target.type
# Setup start, stop and step, allocating temps if needed
self.names = 'start', 'stop', 'step'
......@@ -5951,10 +6038,20 @@ class ParallelRangeNode(ParallelStatNode):
self.index_type = PyrexTypes.widest_numeric_type(
self.index_type, node.type)
self.body.analyse_expressions(env)
super(ParallelRangeNode, self).analyse_expressions(env)
if self.else_clause is not None:
self.else_clause.analyse_expressions(env)
# Although not actually an assignment in this scope, it should be
# treated as such to ensure it is unpacked if a closure temp, and to
# ensure lastprivate behaviour and propagation. If the target index is
# not a NameNode, it won't have an entry, and an error was issued by
# ParallelRangeTransform
if hasattr(self.target, 'entry'):
self.assignments[self.target.entry] = self.target.pos, None
self.analyse_sharing_attributes(env)
def nogil_check(self, env):
names = 'start', 'stop', 'step', 'target'
nodes = self.start, self.stop, self.step, self.target
......@@ -6003,9 +6100,7 @@ class ParallelRangeNode(ParallelStatNode):
4) release our temps and write back any private closure variables
"""
# Ensure to unpack the target index variable if it's a closure temp
self.assignments[self.target.entry] = self.target.pos, None
self.declare_closure_privates(code) #self.insertion_point(code))
self.declare_closure_privates(code)
# This can only be a NameNode
target_index_cname = self.target.entry.cname
......@@ -6064,8 +6159,6 @@ class ParallelRangeNode(ParallelStatNode):
code.end_block()
def generate_loop(self, code, fmt_dict):
target_index_cname = fmt_dict['target']
code.putln("#ifdef _OPENMP")
if not self.is_parallel:
......@@ -6073,23 +6166,18 @@ class ParallelRangeNode(ParallelStatNode):
else:
code.put("#pragma omp parallel for")
for private, op in self.privates.iteritems():
for entry, op in self.privates.iteritems():
# Don't declare the index variable as a reduction
if private != target_index_cname:
if op and op in "+*-&^|":
code.put(" reduction(%s:%s)" % (op, private))
else:
code.put(" lastprivate(%s)" % private)
if op and op in "+*-&^|" and entry != self.target.entry:
code.put(" reduction(%s:%s)" % (op, entry.cname))
else:
code.put(" lastprivate(%s)" % entry.cname)
if self.schedule:
code.put(" schedule(%s)" % self.schedule)
if self.is_parallel or self.target.entry not in self.parent.assignments:
code.putln(" lastprivate(%s)" % target_index_cname)
else:
code.putln("")
code.putln("#endif")
code.putln("")
code.putln("#endif /* _OPENMP */")
code.put("for (%(i)s = 0; %(i)s < %(nsteps)s; %(i)s++)" % fmt_dict)
code.begin_block()
......@@ -6098,6 +6186,8 @@ class ParallelRangeNode(ParallelStatNode):
code.end_block()
#------------------------------------------------------------------------------------
#
# Runtime support code
......
Cython/Compiler/ParseTreeTransforms.py
View file @ 4819d3f5
......@@ -978,6 +978,10 @@ class ParallelRangeTransform(CythonTransform, SkipDeclarations):
# Keep track of whether we are in a parallel range section
in_prange = False
# One of 'prange' or 'with parallel'. This is used to disallow closely
# nested 'with parallel:' blocks
state = None
directive_to_node = {
u"cython.parallel.parallel": Nodes.ParallelWithBlockNode,
# u"cython.parallel.threadsavailable": ExprNodes.ParallelThreadsAvailableNode,
......@@ -1070,9 +1074,16 @@ class ParallelRangeTransform(CythonTransform, SkipDeclarations):
# There was an error, stop here and now
return None
if self.state == 'parallel with':
error(node.manager.pos,
"Closely nested 'with parallel:' blocks are disallowed")
self.state = 'parallel with'
self.visit(node.body)
self.state = None
newnode = Nodes.ParallelWithBlockNode(node.pos, body=node.body)
else:
newnode = node
......@@ -1088,6 +1099,7 @@ class ParallelRangeTransform(CythonTransform, SkipDeclarations):
was_in_prange = self.in_prange
self.in_prange = isinstance(node.iterator.sequence,
Nodes.ParallelRangeNode)
previous_state = self.state
if self.in_prange:
# This will replace the entire ForInStatNode, so copy the
......@@ -1104,11 +1116,13 @@ class ParallelRangeTransform(CythonTransform, SkipDeclarations):
error(node.target.pos,
"Can only iterate over an iteration variable")
self.visit(node.body)
self.state = 'prange'
self.visit(node.body)
self.state = previous_state
self.in_prange = was_in_prange
self.visit(node.else_clause)
self.visit(node.else_clause)
return node
def ensure_not_in_prange(name):
......
tests/errors/e_cython_parallel.pyx
View file @ 4819d3f5
......@@ -30,6 +30,12 @@ with nogil, cython.parallel.parallel:
for x[1] in prange(10):
pass
for x in prange(10):
pass
with cython.parallel.parallel:
pass
_ERRORS = u"""
e_cython_parallel.pyx:3:8: cython.parallel.parallel is not a module
e_cython_parallel.pyx:4:0: No such directive: cython.parallel.something
......@@ -41,4 +47,6 @@ e_cython_parallel.pyx:18:19: Invalid schedule argument to prange: 'invalid_sched
e_cython_parallel.pyx:21:5: The parallel section may only be used without the GIL
e_cython_parallel.pyx:27:10: target may not be a Python object as we don't have the GIL
e_cython_parallel.pyx:30:9: Can only iterate over an iteration variable
e_cython_parallel.pyx:33:10: Must be of numeric type, not int *
e_cython_parallel.pyx:36:24: Closely nested 'with parallel:' blocks are disallowed
"""
tests/run/parallel.pyx
View file @ 4819d3f5
......@@ -43,30 +43,25 @@ def test_descending_prange():
return sum
def test_nested_prange():
def test_propagation():
"""
Reduction propagation is not (yet) supported.
>>> test_nested_prange()
50
>>> test_propagation()
(9, 9, 9, 9, 450, 450)
"""
cdef int i, j
cdef int sum = 0
for i in prange(5, nogil=True):
for j in prange(5):
sum += i
# The value of sum is undefined here
cdef int i, j, x, y
cdef int sum1 = 0, sum2 = 0
sum = 0
for i in prange(10, nogil=True):
for j in prange(10):
sum1 += i
for i in prange(5, nogil=True):
for j in prange(5):
sum += i
sum += 0
with nogil, cython.parallel.parallel:
for x in prange(10):
with cython.parallel.parallel:
for y in prange(10):
sum2 += y
return sum
return i, j, x, y, sum1, sum2
def test_parallel():
......@@ -225,11 +220,11 @@ def test_parallel_numpy_arrays():
print i
return
x = numpy.zeros(10, dtype=np.int)
x = numpy.zeros(10, dtype=numpy.int)
for i in prange(x.shape[0], nogil=True):
x[i] = i - 5
for i in x:
print x
print i
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