def schedule(self,
loop,
packs,
vec_reg_size=16,
prepend_invariant=False,
overwrite_funcs=None):
cm = GenericCostModel(self.cpu, 0)
cm.profitable = lambda: True
pairs = []
for pack in packs:
for i in range(len(pack.operations) - 1):
o1 = pack.operations[i]
o2 = pack.operations[i + 1]
pair = Pair(o1, o2)
pairs.append(pair)
packset = FakePackSet(pairs)
state = VecScheduleState(loop.graph, packset, self.cpu, cm)
for name, overwrite in (overwrite_funcs or {}).items():
setattr(state, name, overwrite)
renamer = Renamer()
metainterp_sd = FakeMetaInterpStaticData(self.cpu)
jitdriver_sd = FakeJitDriverStaticData()
opt = VectorizingOptimizer(metainterp_sd, jitdriver_sd, 0)
opt.packset = packset
opt.combine_packset()
opt.schedule(state)
# works for now. might be the wrong class?
# wrap label + operations + jump it in tree loop otherwise
loop = state.graph.loop
if prepend_invariant:
loop.operations = loop.prefix + loop.operations
return loop
def savings(self, loop):
metainterp_sd = FakeMetaInterpStaticData(self.cpu)
jitdriver_sd = FakeJitDriverStaticData()
opt = VectorizingOptimizer(metainterp_sd, jitdriver_sd, 0)
opt.orig_label_args = loop.label.getarglist()[:]
graph = opt.dependency_graph = DependencyGraph(loop)
self.show_dot_graph(graph, 'costmodel')
for k,m in graph.memory_refs.items():
graph.memory_refs[k] = FakeMemoryRef(m.array, m.index_var)
opt.find_adjacent_memory_refs(graph)
opt.extend_packset()
opt.combine_packset()
for pack in opt.packset.packs:
print "pack: \n ",
print '\n '.join([str(op.getoperation()) for op in pack.operations])
print
costmodel = FakeCostModel(X86_CostModel(self.cpu, 0))
costmodel.reset_savings()
state = VecScheduleState(graph, opt.packset, self.cpu, costmodel)
opt.schedule(state)
return costmodel.getsavings()
def schedule(self, loop, packs, vec_reg_size=16,
prepend_invariant=False, overwrite_funcs=None):
cm = X86_CostModel(self.cpu, 0)
cm.profitable = lambda: True
pairs = []
for pack in packs:
for i in range(len(pack.operations)-1):
o1 = pack.operations[i]
o2 = pack.operations[i+1]
pair = Pair(o1,o2)
pairs.append(pair)
packset = FakePackSet(pairs)
state = VecScheduleState(loop.graph, packset, self.cpu, cm)
for name, overwrite in (overwrite_funcs or {}).items():
setattr(state, name, overwrite)
renamer = Renamer()
metainterp_sd = FakeMetaInterpStaticData(self.cpu)
jitdriver_sd = FakeJitDriverStaticData()
opt = VectorizingOptimizer(metainterp_sd, jitdriver_sd, 0)
opt.packset = packset
opt.combine_packset()
opt.schedule(state)
# works for now. might be the wrong class?
# wrap label + operations + jump it in tree loop otherwise
loop = state.graph.loop
if prepend_invariant:
loop.operations = loop.prefix + loop.operations
return loop
def vectoroptimizer(self, loop):
metainterp_sd = FakeMetaInterpStaticData(self.cpu)
jitdriver_sd = FakeJitDriverStaticData()
opt = VectorizingOptimizer(metainterp_sd, jitdriver_sd, 0)
opt.orig_label_args = loop.label.getarglist()[:]
return opt
def vectoroptimizer(self, loop):
metainterp_sd = FakeMetaInterpStaticData(self.cpu)
jitdriver_sd = FakeJitDriverStaticData()
opt = VectorizingOptimizer(metainterp_sd, jitdriver_sd, 0)
opt.orig_label_args = loop.label.getarglist()[:]
return opt
def savings(self, loop):
metainterp_sd = FakeMetaInterpStaticData(self.cpu)
jitdriver_sd = FakeJitDriverStaticData()
opt = VectorizingOptimizer(metainterp_sd, jitdriver_sd, 0)
opt.orig_label_args = loop.label.getarglist()[:]
graph = opt.dependency_graph = DependencyGraph(loop)
self.show_dot_graph(graph, 'costmodel')
for k, m in graph.memory_refs.items():
graph.memory_refs[k] = FakeMemoryRef(m.array, m.index_var)
opt.find_adjacent_memory_refs(graph)
opt.extend_packset()
opt.combine_packset()
for pack in opt.packset.packs:
print "pack: \n ",
print '\n '.join(
[str(op.getoperation()) for op in pack.operations])
print
costmodel = FakeCostModel(GenericCostModel(self.cpu, 0))
costmodel.reset_savings()
state = VecScheduleState(graph, opt.packset, self.cpu, costmodel)
opt.schedule(state)
return costmodel.getsavings()
