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import py
from rpython.jit.metainterp.history import TargetToken, JitCellToken, TreeLoop
from rpython.jit.metainterp.optimizeopt.util import equaloplists
from rpython.jit.metainterp.optimizeopt.vector import (Pack, GenericCostModel,
NotAProfitableLoop, VectorizingOptimizer, CostModel)
from rpython.jit.metainterp.optimizeopt.schedule import VecScheduleState
from rpython.jit.metainterp.optimizeopt.dependency import Node, DependencyGraph
from rpython.jit.metainterp.optimizeopt.test.test_util import LLtypeMixin
from rpython.jit.metainterp.optimizeopt.test.test_schedule import SchedulerBaseTest
from rpython.jit.metainterp.optimizeopt.test.test_vecopt import (FakeMetaInterpStaticData,
FakeJitDriverStaticData)
from rpython.jit.metainterp.resoperation import rop, ResOperation, AbstractValue
from rpython.jit.tool.oparser import parse as opparse
from rpython.jit.tool.oparser_model import get_model
class FakeMemoryRef(object):
def __init__(self, array, iv):
self.index_var = iv
self.array = array
def is_adjacent_after(self, other):
if self.array is not other.array:
return False
iv = self.index_var
ov = other.index_var
val = (int(str(ov.var)[1:]) - int(str(iv.var)[1:]))
# i0 and i1 are adjacent
# i1 and i0 ...
# but not i0, i2
# ...
#print iv, 'is after', ov, "?", val == 1
return val == 1
def prepost_savings(orig_func):
def func(self, *args):
f = getattr(self.proxy, orig_func.__name__)
before_savings = self.proxy.savings
r = f(*args)
after_savings = self.proxy.savings
print " CM %s (%d -> %d, diff: %d) " % (orig_func.__name__,
before_savings, after_savings,
(after_savings - before_savings),)
print " args: ", args
return r
return func
class FakeCostModel(CostModel):
def __init__(self, proxy):
self.proxy = proxy
def getsavings(self):
return self.proxy.savings
@prepost_savings
def reset_savings(self):
raise NotImplementedError
@prepost_savings
def record_cast_int(self, op):
raise NotImplementedError
@prepost_savings
def record_pack_savings(self, pack, times):
raise NotImplementedError
@prepost_savings
def record_vector_pack(self, box, index, count):
raise NotImplementedError
@prepost_savings
def record_vector_unpack(self, box, index, count):
raise NotImplementedError
@prepost_savings
def unpack_cost(self, op, index, count):
raise NotImplementedError
@prepost_savings
def savings_for_pack(self, pack, times):
raise NotImplementedError
def profitable(self):
return self.proxy.savings >= 0
class CostModelBaseTest(SchedulerBaseTest):
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()
def assert_operations_match(self, loop_a, loop_b):
assert equaloplists(loop_a.operations, loop_b.operations)
def test_load_2_unpack(self):
loop1 = self.parse_trace("""
f10 = raw_load_f(p0, i0, descr=double)
f11 = raw_load_f(p0, i1, descr=double)
guard_true(i0) [f10]
guard_true(i1) [f11]
""")
# for double the costs are
# unpack index 1 savings: -2
# unpack index 0 savings: -1
savings = self.savings(loop1)
assert savings == -2
def test_load_4_unpack(self):
loop1 = self.parse_trace("""
i10 = raw_load_i(p0, i0, descr=float)
i11 = raw_load_i(p0, i1, descr=float)
i12 = raw_load_i(p0, i2, descr=float)
i13 = raw_load_i(p0, i3, descr=float)
guard_true(i0) [i10]
guard_true(i1) [i11]
guard_true(i2) [i12]
guard_true(i3) [i13]
""")
savings = self.savings(loop1)
assert savings == -1
def test_load_2_unpack_1(self):
loop1 = self.parse_trace("""
f10 = raw_load_f(p0, i0, descr=double)
f11 = raw_load_f(p0, i1, descr=double)
guard_true(i0) [f10]
""")
assert loop1.operations[2].getfailargs()[0] is loop1.operations[0]
savings = self.savings(loop1)
assert savings == 0
assert loop1.operations[2].getfailargs()[0] is loop1.operations[-2]
def test_load_2_unpack_1_index1(self):
loop1 = self.parse_trace("""
f10 = raw_load_f(p0, i0, descr=double)
f11 = raw_load_f(p0, i1, descr=double)
guard_true(i0) [f11]
""")
savings = self.savings(loop1)
assert savings == -1
def test_load_arith1(self):
loop1 = self.parse_trace("""
i10 = raw_load_i(p0, i0, descr=int)
i11 = raw_load_i(p0, i1, descr=int)
i12 = raw_load_i(p0, i2, descr=int)
i13 = raw_load_i(p0, i3, descr=int)
i15 = int_add(i10, 1)
i16 = int_add(i11, 1)
i17 = int_add(i12, 1)
i18 = int_add(i13, 1)
""")
savings = self.savings(loop1)
assert savings == 6
def test_load_arith_store(self):
import platform
size = 4
if not platform.machine().startswith('x86'):
size = 8
loop1 = self.parse_trace("""
f10 = raw_load_f(p0, i0, descr=double)
f11 = raw_load_f(p0, i1, descr=double)
i20 = cast_float_to_int(f10)
i21 = cast_float_to_int(f11)
i30 = int_signext(i20, {size})
i31 = int_signext(i21, {size})
raw_store(p0, i3, i30, descr=int)
raw_store(p0, i4, i31, descr=int)
""".format(size=size))
savings = self.savings(loop1)
assert savings >= 0
def test_sum(self):
loop1 = self.parse_trace("""
f10 = raw_load_f(p0, i0, descr=double)
f11 = raw_load_f(p0, i1, descr=double)
f12 = float_add(f1, f10)
f13 = float_add(f12, f11)
""")
savings = self.savings(loop1)
assert savings == -2
@py.test.mark.parametrize("bytes,s", [(4,0),(8,0)])
def test_sum_float_to_int(self, bytes, s):
loop1 = self.parse_trace("""
f10 = raw_load_f(p0, i0, descr=double)
f11 = raw_load_f(p0, i1, descr=double)
i10 = cast_float_to_int(f10)
i11 = cast_float_to_int(f11)
i12 = int_signext(i10, {c})
i13 = int_signext(i11, {c})
i14 = int_add(i1, i12)
i16 = int_signext(i14, {c})
i15 = int_add(i16, i13)
i17 = int_signext(i15, {c})
""".format(c=bytes))
try:
savings = self.savings(loop1)
if s is None:
py.test.fail("must fail")
# it does not benefit because signext has
# a very inefficient implementation (x86
# does not provide nice instr to convert
# integer sizes)
# signext -> no benefit, + 2x unpack
assert savings <= s
except NotAProfitableLoop:
if s is not None:
py.test.fail("must not fail")
def test_cast(self):
loop1 = self.parse_trace("""
i100 = raw_load_i(p0, i1, descr=float)
i101 = raw_load_i(p0, i2, descr=float)
i102 = raw_load_i(p0, i3, descr=float)
i103 = raw_load_i(p0, i4, descr=float)
#
i104 = raw_load_i(p1, i1, descr=short)
i105 = raw_load_i(p1, i2, descr=short)
i106 = raw_load_i(p1, i3, descr=short)
i107 = raw_load_i(p1, i4, descr=short)
i108 = raw_load_i(p1, i5, descr=short)
i109 = raw_load_i(p1, i6, descr=short)
i110 = raw_load_i(p1, i7, descr=short)
i111 = raw_load_i(p1, i8, descr=short)
#
f100 = cast_int_to_float(i104)
f101 = cast_int_to_float(i105)
f102 = cast_int_to_float(i106)
f103 = cast_int_to_float(i107)
f104 = cast_int_to_float(i108)
f105 = cast_int_to_float(i109)
f106 = cast_int_to_float(i110)
f107 = cast_int_to_float(i111)
""")
try:
self.savings(loop1)
py.test.fail("must not be profitable!")
except NotAProfitableLoop:
pass
def test_force_int_to_float_cast(self):
trace = self.parse_trace("""
i10 = raw_load_i(p0, i1, descr=long)
i11 = raw_load_i(p0, i2, descr=long)
f10 = cast_int_to_float(i10)
f11 = cast_int_to_float(i11)
""")
number = self.savings(trace)
assert number >= 1
class Test(CostModelBaseTest, LLtypeMixin):
pass
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