Newer
Older
queue = cl.CommandQueue(ctx)
if ctx.devices[0].platform.name.startswith("Portable"):
# Accurate as of 2015-10-08
pytest.skip("POCL miscompiles vector code")
knl = lp.make_kernel(
''' { [i,j,k]: 0<=i,j,k<4 } ''',
''' out[i,j,k] = indexof_vec(out[i,j,k])''')
knl = lp.tag_inames(knl, {"i": "vec"})
knl = lp.tag_data_axes(knl, "out", "vec,c,c")
knl = lp.set_options(knl, write_cl=True)
(evt, (out,)) = knl(queue)
#out = out.get()
#assert np.array_equal(out.ravel(order="C"), np.arange(25))
Andreas Klöckner
committed
def test_is_expression_equal():
from loopy.symbolic import is_expression_equal
from pymbolic import var
x = var("x")
y = var("y")
assert is_expression_equal(x+2, 2+x)
assert is_expression_equal((x+2)**2, x**2 + 4*x + 4)
assert is_expression_equal((x+y)**2, x**2 + 2*x*y + y**2)
@pytest.mark.parametrize("dtype", [np.int32, np.int64, np.float32, np.float64])
def test_atomic(ctx_factory, dtype):
ctx = ctx_factory()
if (
np.dtype(dtype).itemsize == 8
and "cl_khr_int64_base_atomics" not in ctx.devices[0].extensions):
pytest.skip("64-bit atomics not supported on device")
import pyopencl.version # noqa
if (
cl.version.VERSION < (2015, 2)
and dtype == np.int64):
pytest.skip("int64 RNG not supported in PyOpenCL < 2015.2")
knl = lp.make_kernel(
"{ [i]: 0<=i<n }",
"out[i%20] = out[i%20] + 2*a[i] {atomic}",
[
lp.GlobalArg("out", dtype, shape=lp.auto, for_atomic=True),
lp.GlobalArg("a", dtype, shape=lp.auto),
"..."
],
assumptions="n>0")
ref_knl = knl
knl = lp.split_iname(knl, "i", 512)
knl = lp.split_iname(knl, "i_inner", 128, outer_tag="unr", inner_tag="g.0")
lp.auto_test_vs_ref(ref_knl, ctx, knl, parameters=dict(n=10000))
def test_within_inames_and_reduction():
# See https://github.com/inducer/loopy/issues/24
# This is (purposefully) somewhat un-idiomatic, to replicate the conditions
# under which the above bug was found. If assignees were phi[i], then the
# iname propagation heuristic would not assume that dependent instructions
# need to run inside of 'i', and hence the forced_iname_* bits below would not
# be needed.
i1 = lp.CInstruction("i",
"doSomethingToGetPhi();",
from pymbolic.primitives import Subscript, Variable
i2 = lp.Assignment("a",
lp.Reduction("sum", "j", Subscript(Variable("phi"), Variable("j"))),
within_inames=frozenset(),
within_inames_is_final=True)
k = lp.make_kernel("{[i,j] : 0<=i,j<n}",
[i1, i2],
[
lp.GlobalArg("a", dtype=np.float32, shape=()),
lp.ValueArg("n", dtype=np.int32),
lp.TemporaryVariable("phi", dtype=np.float32, shape=("n",)),
],
target=lp.CTarget(),
)
k = lp.preprocess_kernel(k)
assert 'i' not in k.insn_inames("insn_0_j_update")
print(k.stringify(with_dependencies=True))
def test_literal_local_barrier(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(
"{ [i]: 0<=i<n }",
"""
for i
... lbarrier
end
""", seq_dependencies=True)
knl = lp.fix_parameters(knl, n=128)
ref_knl = knl
lp.auto_test_vs_ref(ref_knl, ctx, knl, parameters=dict(n=5))
def test_kernel_splitting(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(
"{ [i]: 0<=i<n }",
"""
for i
c[i] = a[i + 1]
... gbarrier
out[i] = c[i]
end
""", seq_dependencies=True)
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
knl = lp.add_and_infer_dtypes(knl,
{"a": np.float32, "c": np.float32, "out": np.float32, "n": np.int32})
ref_knl = knl
knl = lp.split_iname(knl, "i", 128, outer_tag="g.0", inner_tag="l.0")
# schedule
from loopy.preprocess import preprocess_kernel
knl = preprocess_kernel(knl)
from loopy.schedule import get_one_scheduled_kernel
knl = get_one_scheduled_kernel(knl)
# map schedule onto host or device
print(knl)
cgr = lp.generate_code_v2(knl)
assert len(cgr.device_programs) == 2
print(cgr.device_code())
print(cgr.host_code())
lp.auto_test_vs_ref(ref_knl, ctx, knl, parameters=dict(n=5))
def test_kernel_splitting_with_loop(ctx_factory):
knl = lp.make_kernel(
"{ [i,k]: 0<=i<n and 0<=k<3 }",
"""
for i, k
... gbarrier
c[k,i] = a[k, i + 1]
... gbarrier
out[k,i] = c[k,i]
end
""", seq_dependencies=True)
knl = lp.add_and_infer_dtypes(knl,
{"a": np.float32, "c": np.float32, "out": np.float32, "n": np.int32})
knl = lp.split_iname(knl, "i", 128, outer_tag="g.0", inner_tag="l.0")
# schedule
from loopy.preprocess import preprocess_kernel
knl = preprocess_kernel(knl)
from loopy.schedule import get_one_scheduled_kernel
knl = get_one_scheduled_kernel(knl)
# map schedule onto host or device
print(knl)
cgr = lp.generate_code_v2(knl)
assert len(cgr.device_programs) == 2
print(cgr.device_code())
print(cgr.host_code())
lp.auto_test_vs_ref(ref_knl, ctx, knl, parameters=dict(n=5))
def save_and_reload_temporaries_test(queue, knl, out_expect, debug=False):
from loopy.preprocess import preprocess_kernel
from loopy.schedule import get_one_scheduled_kernel
knl = preprocess_kernel(knl)
knl = get_one_scheduled_kernel(knl)
from loopy.transform.save import save_and_reload_temporaries
knl = save_and_reload_temporaries(knl)
knl = get_one_scheduled_kernel(knl)
if debug:
print(knl)
cgr = lp.generate_code_v2(knl)
print(cgr.device_code())
print(cgr.host_code())
1/0
_, (out,) = knl(queue, out_host=True)
assert (out == out_expect).all(), (out, out_expect)
@pytest.mark.parametrize("hw_loop", [True, False])
def test_save_of_private_scalar(ctx_factory, hw_loop, debug=False):
"{ [i]: 0<=i<8 }",
"""
for i
<>t = i
... gbarrier
out[i] = t
end
""", seq_dependencies=True)
if hw_loop:
knl = lp.tag_inames(knl, dict(i="g.0"))
save_and_reload_temporaries_test(queue, knl, np.arange(8), debug)
"{ [i]: 0<=i<8 }",
"""
for i
<>t[i] = i
... gbarrier
out[i] = t[i]
end
""", seq_dependencies=True)
knl = lp.set_temporary_scope(knl, "t", "private")
save_and_reload_temporaries_test(queue, knl, np.arange(8), debug)
def test_save_of_private_array_in_hw_loop(ctx_factory, debug=False):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
"{ [i,j,k]: 0<=i,j,k<8 }",
"""
for i
for j
<>t[j] = j
... gbarrier
for k
out[i,k] = t[k]
knl = lp.tag_inames(knl, dict(i="g.0"))
knl = lp.set_temporary_scope(knl, "t", "private")
save_and_reload_temporaries_test(
queue, knl, np.vstack((8 * (np.arange(8),))), debug)
def test_save_of_private_multidim_array(ctx_factory, debug=False):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(
"{ [i,j,k,l,m]: 0<=i,j,k,l,m<8 }",
"""
for i
for j, k
<>t[j,k] = k
end
... gbarrier
for l, m
out[i,l,m] = t[l,m]
end
end
""", seq_dependencies=True)
knl = lp.set_temporary_scope(knl, "t", "private")
result = np.array([np.vstack((8 * (np.arange(8),))) for i in range(8)])
save_and_reload_temporaries_test(queue, knl, result, debug)
def test_save_of_private_multidim_array_in_hw_loop(ctx_factory, debug=False):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(
"{ [i,j,k,l,m]: 0<=i,j,k,l,m<8 }",
"""
for i
for j, k
<>t[j,k] = k
end
... gbarrier
for l, m
out[i,l,m] = t[l,m]
end
end
""", seq_dependencies=True)
knl = lp.set_temporary_scope(knl, "t", "private")
knl = lp.tag_inames(knl, dict(i="g.0"))
result = np.array([np.vstack((8 * (np.arange(8),))) for i in range(8)])
save_and_reload_temporaries_test(queue, knl, result, debug)
@pytest.mark.parametrize("hw_loop", [True, False])
def test_save_of_multiple_private_temporaries(ctx_factory, hw_loop, debug=False):
for i
for k
<> t_arr[k] = k
end
<> t_scalar = 1
for j
... gbarrier
out[j] = t_scalar
... gbarrier
t_scalar = 10
<> flag = i == 9
out[i] = t_arr[i] {if=flag}
end
""", seq_dependencies=True)
knl = lp.set_temporary_scope(knl, "t_arr", "private")
if hw_loop:
knl = lp.tag_inames(knl, dict(i="g.0"))
result = np.array([1, 10, 10, 10, 10, 10, 10, 10, 10, 9])
save_and_reload_temporaries_test(queue, knl, result, debug)
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(
"{ [i,j]: 0<=i,j<8 }",
"""
for i, j
<>t[2*j] = j
t[2*j+1] = j
... gbarrier
out[i] = t[2*i]
end
""", seq_dependencies=True)
knl = lp.set_temporary_scope(knl, "t", "local")
knl = lp.tag_inames(knl, dict(i="g.0", j="l.0"))
save_and_reload_temporaries_test(queue, knl, np.arange(8), debug)
1388
1389
1390
1391
1392
1393
1394
1395
1396
1397
1398
1399
1400
1401
1402
1403
1404
1405
1406
1407
1408
1409
def test_save_of_local_array_with_explicit_local_barrier(ctx_factory, debug=False):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(
"{ [i,j]: 0<=i,j<8 }",
"""
for i, j
<>t[2*j] = j
... lbarrier
t[2*j+1] = t[2*j]
... gbarrier
out[i] = t[2*i]
end
""", seq_dependencies=True)
knl = lp.set_temporary_scope(knl, "t", "local")
knl = lp.tag_inames(knl, dict(i="g.0", j="l.0"))
save_and_reload_temporaries_test(queue, knl, np.arange(8), debug)
def test_save_local_multidim_array(ctx_factory, debug=False):
"{ [i,j,k]: 0<=i<2 and 0<=k<3 and 0<=j<2}",
end
""", seq_dependencies=True)
knl = lp.set_temporary_scope(knl, "t_local", "local")
knl = lp.tag_inames(knl, dict(j="l.0", i="g.0"))
save_and_reload_temporaries_test(queue, knl, 1, debug)
1431
1432
1433
1434
1435
1436
1437
1438
1439
1440
1441
1442
1443
1444
1445
1446
1447
1448
1449
1450
1451
1452
1453
1454
1455
def test_save_with_base_storage(ctx_factory, debug=False):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(
"{[i]: 0 <= i < 10}",
"""
<>a[i] = 0
<>b[i] = i
... gbarrier
out[i] = a[i]
""",
"...",
seq_dependencies=True)
knl = lp.tag_inames(knl, dict(i="l.0"))
knl = lp.set_temporary_scope(knl, "a", "local")
knl = lp.set_temporary_scope(knl, "b", "local")
knl = lp.alias_temporaries(knl, ["a", "b"],
synchronize_for_exclusive_use=False)
save_and_reload_temporaries_test(queue, knl, np.arange(10), debug)
1456
1457
1458
1459
1460
1461
1462
1463
1464
1465
1466
1467
1468
1469
1470
1471
1472
1473
1474
1475
1476
1477
1478
1479
1480
1481
1482
1483
1484
1485
1486
1487
1488
1489
1490
1491
1492
1493
1494
1495
1496
1497
def test_save_ambiguous_storage_requirements():
knl = lp.make_kernel(
"{[i,j]: 0 <= i < 10 and 0 <= j < 10}",
"""
<>a[j] = j
... gbarrier
out[i,j] = a[j]
""",
seq_dependencies=True)
knl = lp.tag_inames(knl, dict(i="g.0", j="l.0"))
knl = lp.duplicate_inames(knl, "j", within="writes:out", tags={"j": "l.0"})
knl = lp.set_temporary_scope(knl, "a", "local")
knl = lp.preprocess_kernel(knl)
knl = lp.get_one_scheduled_kernel(knl)
from loopy.diagnostic import LoopyError
with pytest.raises(LoopyError):
lp.save_and_reload_temporaries(knl)
def test_save_across_inames_with_same_tag(ctx_factory, debug=False):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(
"{[i]: 0 <= i < 10}",
"""
<>a[i] = i
... gbarrier
out[i] = a[i]
""",
"...",
seq_dependencies=True)
knl = lp.tag_inames(knl, dict(i="l.0"))
knl = lp.duplicate_inames(knl, "i", within="reads:a", tags={"i": "l.0"})
save_and_reload_temporaries_test(queue, knl, np.arange(10), debug)
def test_missing_temporary_definition_detection():
knl = lp.make_kernel(
"{ [i]: 0<=i<10 }",
"""
for i
<> t = 1
... gbarrier
out[i] = t
end
""", seq_dependencies=True)
from loopy.diagnostic import MissingDefinitionError
with pytest.raises(MissingDefinitionError):
lp.generate_code_v2(knl)
def test_missing_definition_check_respects_aliases():
# Based on https://github.com/inducer/loopy/issues/69
knl = lp.make_kernel("{ [i] : 0<=i<n }",
["a[i] = 0",
"c[i] = b[i]"],
temporary_variables={
"a": lp.TemporaryVariable("a",
dtype=np.float64, shape=("n",), base_storage="base"),
"b": lp.TemporaryVariable("b",
dtype=np.float64, shape=("n",), base_storage="base")
},
target=lp.CTarget(),
silenced_warnings=frozenset(["read_no_write(b)"]))
lp.generate_code_v2(knl)
def test_global_temporary(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(
"{ [i]: 0<=i<n}",
"""
for i
<> c[i] = a[i + 1]
... gbarrier
out[i] = c[i]
end
""", seq_dependencies=True)
knl = lp.add_and_infer_dtypes(knl,
{"a": np.float32, "c": np.float32, "out": np.float32, "n": np.int32})
knl = lp.set_temporary_scope(knl, "c", "global")
ref_knl = knl
knl = lp.split_iname(knl, "i", 128, outer_tag="g.0", inner_tag="l.0")
cgr = lp.generate_code_v2(knl)
assert len(cgr.device_programs) == 2
#print(cgr.device_code())
#print(cgr.host_code())
lp.auto_test_vs_ref(ref_knl, ctx, knl, parameters=dict(n=5))
def test_assign_to_linear_subscript(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl1 = lp.make_kernel(
"{ [i]: 0<=i<n}",
"a[i,i] = 1")
knl2 = lp.make_kernel(
"{ [i]: 0<=i<n}",
"a[[i*n + i]] = 1",
[lp.GlobalArg("a", shape="n,n"), "..."])
a1 = cl.array.zeros(queue, (10, 10), np.float32)
knl1(queue, a=a1)
a2 = cl.array.zeros(queue, (10, 10), np.float32)
knl2(queue, a=a2)
assert np.array_equal(a1.get(), a2.get())
1582
1583
1584
1585
1586
1587
1588
1589
1590
1591
1592
1593
1594
1595
1596
1597
1598
1599
1600
1601
1602
1603
1604
1605
1606
1607
1608
1609
1610
1611
1612
1613
1614
1615
1616
1617
1618
1619
1620
1621
1622
1623
1624
1625
1626
1627
1628
1629
1630
1631
1632
def test_finite_difference_expr_subst(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
grid = np.linspace(0, 2*np.pi, 2048, endpoint=False)
h = grid[1] - grid[0]
u = cl.clmath.sin(cl.array.to_device(queue, grid))
fin_diff_knl = lp.make_kernel(
"{[i]: 1<=i<=n}",
"out[i] = -(f[i+1] - f[i-1])/h",
[lp.GlobalArg("out", shape="n+2"), "..."])
flux_knl = lp.make_kernel(
"{[j]: 1<=j<=n}",
"f[j] = u[j]**2/2",
[
lp.GlobalArg("f", shape="n+2"),
lp.GlobalArg("u", shape="n+2"),
])
fused_knl = lp.fuse_kernels([fin_diff_knl, flux_knl],
data_flow=[
("f", 1, 0)
])
fused_knl = lp.set_options(fused_knl, write_cl=True)
evt, _ = fused_knl(queue, u=u, h=np.float32(1e-1))
fused_knl = lp.assignment_to_subst(fused_knl, "f")
fused_knl = lp.set_options(fused_knl, write_cl=True)
# This is the real test here: The automatically generated
# shape expressions are '2+n' and the ones above are 'n+2'.
# Is loopy smart enough to understand that these are equal?
evt, _ = fused_knl(queue, u=u, h=np.float32(1e-1))
fused0_knl = lp.affine_map_inames(fused_knl, "i", "inew", "inew+1=i")
gpu_knl = lp.split_iname(
fused0_knl, "inew", 128, outer_tag="g.0", inner_tag="l.0")
precomp_knl = lp.precompute(
gpu_knl, "f_subst", "inew_inner", fetch_bounding_box=True)
precomp_knl = lp.tag_inames(precomp_knl, {"j_0_outer": "unr"})
precomp_knl = lp.set_options(precomp_knl, return_dict=True)
evt, _ = precomp_knl(queue, u=u, h=h)
# {{{ call without returned values
def test_call_with_no_returned_value(ctx_factory):
import pymbolic.primitives as p
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(
"{:}",
[lp.CallInstruction((), p.Call(p.Variable("f"), ()))]
from library_for_test import no_ret_f_mangler, no_ret_f_preamble_gen
knl = lp.register_function_manglers(knl, [no_ret_f_mangler])
knl = lp.register_preamble_generators(knl, [no_ret_f_preamble_gen])
evt, _ = knl(queue)
knl = lp.make_kernel(
"{:}",
"f() {id=init}"
)
knl = lp.register_function_manglers(knl, [no_ret_f_mangler])
print(lp.generate_code_v2(knl).device_code())
Dominic Kempf
committed
def test_unschedulable_kernel_detection():
knl = lp.make_kernel(["{[i,j]:0<=i,j<n}"],
"""
mat1[i,j] = mat1[i,j] + 1 {inames=i:j, id=i1}
mat2[j] = mat2[j] + 1 {inames=j, id=i2}
mat3[i] = mat3[i] + 1 {inames=i, id=i3}
""")
knl = lp.preprocess_kernel(knl)
# Check that loopy can detect the unschedulability of the kernel
assert not lp.has_schedulable_iname_nesting(knl)
assert len(list(lp.get_iname_duplication_options(knl))) == 4
Dominic Kempf
committed
for inames, insns in lp.get_iname_duplication_options(knl):
fixed_knl = lp.duplicate_inames(knl, inames, insns)
assert lp.has_schedulable_iname_nesting(fixed_knl)
Dominic Kempf
committed
knl = lp.make_kernel(["{[i,j,k,l,m]:0<=i,j,k,l,m<n}"],
"""
mat1[l,m,i,j,k] = mat1[l,m,i,j,k] + 1 {inames=i:j:k:l:m}
mat2[l,m,j,k] = mat2[l,m,j,k] + 1 {inames=j:k:l:m}
mat3[l,m,k] = mat3[l,m,k] + 11 {inames=k:l:m}
mat4[l,m,i] = mat4[l,m,i] + 1 {inames=i:l:m}
""")
assert not lp.has_schedulable_iname_nesting(knl)
assert len(list(lp.get_iname_duplication_options(knl))) == 10
Andreas Klöckner
committed
def test_regression_no_ret_call_removal(ctx_factory):
# https://github.com/inducer/loopy/issues/32
knl = lp.make_kernel(
"{[i] : 0<=i<n}",
"f(sum(i, x[i]))")
knl = lp.add_and_infer_dtypes(knl, {"x": np.float32})
knl = lp.preprocess_kernel(knl)
assert len(knl.instructions) == 3
def test_regression_persistent_hash():
knl1 = lp.make_kernel(
"{[i] : 0<=i<n}",
"cse_exprvar = d[2]*d[2]")
knl2 = lp.make_kernel(
"{[i] : 0<=i<n}",
"cse_exprvar = d[0]*d[0]")
from loopy.tools import LoopyKeyBuilder
lkb = LoopyKeyBuilder()
assert lkb(knl1.instructions[0]) != lkb(knl2.instructions[0])
assert lkb(knl1) != lkb(knl2)
def test_sequential_dependencies(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(
"{[i]: 0<=i<n}",
"""
for i
<> aa = 5jf
<> bb = 5j
a[i] = imag(aa)
b[i] = imag(bb)
c[i] = 5f
end
""", seq_dependencies=True)
print(knl.stringify(with_dependencies=True))
lp.auto_test_vs_ref(knl, ctx, knl, parameters=dict(n=5))
def test_nop(ctx_factory):
knl = lp.make_kernel(
"{[i,itrip]: 0<=i<n and 0<=itrip<ntrips}",
"""
for itrip,i
... nop {dep=wr_z:wr_v,id=yoink}
knl = lp.fix_parameters(knl, n=15)
knl = lp.add_and_infer_dtypes(knl, {"z": np.float64})
lp.auto_test_vs_ref(knl, ctx, knl, parameters=dict(ntrips=5))
1767
1768
1769
1770
1771
1772
1773
1774
1775
1776
1777
1778
1779
1780
1781
1782
1783
1784
1785
1786
1787
1788
1789
1790
1791
1792
1793
1794
1795
1796
1797
1798
1799
1800
1801
1802
1803
1804
1805
1806
1807
1808
1809
1810
1811
1812
1813
1814
1815
1816
1817
1818
1819
1820
1821
1822
1823
1824
1825
1826
1827
def test_global_barrier(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(
"{[i,itrip]: 0<=i<n and 0<=itrip<ntrips}",
"""
for i
for itrip
... gbarrier {id=top}
<> z[i] = z[i+1] + z[i] {id=wr_z,dep=top}
<> v[i] = 11 {id=wr_v,dep=top}
... gbarrier {dep=wr_z:wr_v,id=yoink}
z[i] = z[i] - z[i+1] + v[i] {id=iupd}
end
... gbarrier {dep=iupd,id=postloop}
z[i] = z[i] - z[i+1] + v[i] {dep=postloop}
end
""")
knl = lp.fix_parameters(knl, ntrips=3)
knl = lp.add_and_infer_dtypes(knl, {"z": np.float64})
ref_knl = knl
ref_knl = lp.set_temporary_scope(ref_knl, "z", "global")
ref_knl = lp.set_temporary_scope(ref_knl, "v", "global")
knl = lp.split_iname(knl, "i", 256, outer_tag="g.0", inner_tag="l.0")
print(knl)
knl = lp.preprocess_kernel(knl)
assert knl.temporary_variables["z"].scope == lp.temp_var_scope.GLOBAL
assert knl.temporary_variables["v"].scope == lp.temp_var_scope.GLOBAL
print(knl)
lp.auto_test_vs_ref(ref_knl, ctx, knl, parameters=dict(ntrips=5, n=10))
def test_missing_global_barrier():
knl = lp.make_kernel(
"{[i,itrip]: 0<=i<n and 0<=itrip<ntrips}",
"""
for i
for itrip
... gbarrier {id=yoink}
<> z[i] = z[i] - z[i+1] {id=iupd,dep=yoink}
end
# This is where the barrier should be
z[i] = z[i] - z[i+1] + v[i] {dep=iupd}
end
""")
knl = lp.set_temporary_scope(knl, "z", "global")
knl = lp.split_iname(knl, "i", 256, outer_tag="g.0")
knl = lp.preprocess_kernel(knl)
from loopy.diagnostic import MissingBarrierError
with pytest.raises(MissingBarrierError):
lp.get_one_scheduled_kernel(knl)
def test_index_cse(ctx_factory):
knl = lp.make_kernel(["{[i,j,k,l,m]:0<=i,j,k,l,m<n}"],
"""
for i
for j
c[i,j,m] = sum((k,l), a[i,j,l]*b[i,j,k,l])
end
end
""")
knl = lp.tag_inames(knl, "l:unr")
knl = lp.prioritize_loops(knl, "i,j,k,l")
1839
1840
1841
1842
1843
1844
1845
1846
1847
1848
1849
1850
1851
1852
1853
1854
1855
1856
1857
1858
1859
1860
1861
1862
1863
1864
1865
knl = lp.add_and_infer_dtypes(knl, {"a": np.float32, "b": np.float32})
knl = lp.fix_parameters(knl, n=5)
print(lp.generate_code_v2(knl).device_code())
def test_ilp_and_conditionals(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel('{[k]: 0<=k<n}}',
"""
for k
<> Tcond = T[k] < 0.5
if Tcond
cp[k] = 2 * T[k] + Tcond
end
end
""")
knl = lp.fix_parameters(knl, n=200)
knl = lp.add_and_infer_dtypes(knl, {"T": np.float32})
ref_knl = knl
knl = lp.split_iname(knl, 'k', 2, inner_tag='ilp')
lp.auto_test_vs_ref(ref_knl, ctx, knl)
1867
1868
1869
1870
1871
1872
1873
1874
1875
1876
1877
1878
1879
1880
1881
1882
1883
1884
1885
1886
1887
def test_unr_and_conditionals(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel('{[k]: 0<=k<n}}',
"""
for k
<> Tcond[k] = T[k] < 0.5
if Tcond[k]
cp[k] = 2 * T[k] + Tcond[k]
end
end
""")
knl = lp.fix_parameters(knl, n=200)
knl = lp.add_and_infer_dtypes(knl, {"T": np.float32})
ref_knl = knl
knl = lp.split_iname(knl, 'k', 2, inner_tag='unr')
lp.auto_test_vs_ref(ref_knl, ctx, knl)
def test_constant_array_args(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel('{[k]: 0<=k<n}}',
"""
for k
<> Tcond[k] = T[k] < 0.5
if Tcond[k]
cp[k] = 2 * T[k] + Tcond[k]
end
end
""",
[lp.ConstantArg('T', shape=(200,), dtype=np.float32),
'...'])
knl = lp.fix_parameters(knl, n=200)
@pytest.mark.parametrize("src_order", ["C"])
@pytest.mark.parametrize("tmp_order", ["C", "F"])
def test_temp_initializer(ctx_factory, src_order, tmp_order):
a = np.random.randn(3, 3).copy(order=src_order)
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(
"{[i,j]: 0<=i,j<n}",
"out[i,j] = tmp[i,j]",
[
lp.TemporaryVariable("tmp",
initializer=a,
shape=lp.auto,
scope=lp.temp_var_scope.PRIVATE,
read_only=True,
order=tmp_order),
"..."
])
knl = lp.set_options(knl, write_cl=True, highlight_cl=True)
knl = lp.fix_parameters(knl, n=a.shape[0])
evt, (a2,) = knl(queue, out_host=True)
assert np.array_equal(a, a2)
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
def test_const_temp_with_initializer_not_saved():
knl = lp.make_kernel(
"{[i]: 0<=i<10}",
"""
... gbarrier
out[i] = tmp[i]
""",
[
lp.TemporaryVariable("tmp",
initializer=np.arange(10),
shape=lp.auto,
scope=lp.temp_var_scope.PRIVATE,
read_only=True),
"..."
],
seq_dependencies=True)
knl = lp.preprocess_kernel(knl)
knl = lp.get_one_scheduled_kernel(knl)
knl = lp.save_and_reload_temporaries(knl)
# This ensures no save slot was added.
assert len(knl.temporary_variables) == 1
def test_header_extract():
knl = lp.make_kernel('{[k]: 0<=k<n}}',
"""
for k
T[k] = k**2
end
""",
[lp.GlobalArg('T', shape=(200,), dtype=np.float32),
'...'])
knl = lp.fix_parameters(knl, n=200)
#test C
cknl = knl.copy(target=lp.CTarget())
assert str(lp.generate_header(cknl)[0]) == (
'void loopy_kernel(float *__restrict__ T);')
cuknl = knl.copy(target=lp.CudaTarget())
assert str(lp.generate_header(cuknl)[0]) == (
'extern "C" __global__ void __launch_bounds__(1) '
'loopy_kernel(float *__restrict__ T);')
oclknl = knl.copy(target=lp.PyOpenCLTarget())
assert str(lp.generate_header(oclknl)[0]) == (
'__kernel void __attribute__ ((reqd_work_group_size(1, 1, 1))) '
'loopy_kernel(__global float *__restrict__ T);')
def test_scalars_with_base_storage(ctx_factory):
""" Regression test for !50 """
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(
"{ [i]: 0<=i<1}",