diff --git a/pyopencl/array.py b/pyopencl/array.py
index 2d03207962b5fb1c6f5c9c4edb48ad1d3478e231..704c495b4bff7ceed3d4808244a8bdb844f267b5 100644
--- a/pyopencl/array.py
+++ b/pyopencl/array.py
@@ -621,9 +621,10 @@ class Array(object):
stacklevel=2)
if self.size:
- cl.enqueue_copy(queue or self.queue, self.base_data, ary,
+ event1 = cl.enqueue_copy(queue or self.queue, self.base_data, ary,
device_offset=self.offset,
is_blocking=not async_)
+ self.add_event(event1)
def get(self, queue=None, ary=None, async_=None, **kwargs):
"""Transfer the contents of *self* into *ary* or a newly allocated
@@ -687,7 +688,7 @@ class Array(object):
if self.size:
cl.enqueue_copy(queue, ary, self.base_data,
device_offset=self.offset,
- is_blocking=not async_)
+ wait_for=self.events, is_blocking=not async_)
return ary
@@ -712,9 +713,11 @@ class Array(object):
result = result.with_queue(queue)
if self.nbytes:
- cl.enqueue_copy(queue or self.queue,
+ event1 = cl.enqueue_copy(queue or self.queue,
result.base_data, self.base_data,
- src_offset=self.offset, byte_count=self.nbytes)
+ src_offset=self.offset, byte_count=self.nbytes,
+ wait_for=self.events)
+ result.add_event(event1)
return result
@@ -1287,12 +1290,22 @@ class Array(object):
def any(self, queue=None, wait_for=None):
from pyopencl.reduction import get_any_kernel
krnl = get_any_kernel(self.context, self.dtype)
- return krnl(self, queue=queue, wait_for=wait_for)
+ if wait_for is None:
+ wait_for = []
+ result, event1 = krnl(self, queue=queue,
+ wait_for=wait_for + self.events, return_event=True)
+ result.add_event(event1)
+ return result
def all(self, queue=None, wait_for=None):
from pyopencl.reduction import get_all_kernel
krnl = get_all_kernel(self.context, self.dtype)
- return krnl(self, queue=queue, wait_for=wait_for)
+ if wait_for is None:
+ wait_for = []
+ result, event1 = krnl(self, queue=queue,
+ wait_for=wait_for + self.events, return_event=True)
+ result.add_event(event1)
+ return result
@staticmethod
@elwise_kernel_runner
@@ -1673,11 +1686,13 @@ class Array(object):
if flags is None:
flags = cl.map_flags.READ | cl.map_flags.WRITE
+ if wait_for is None:
+ wait_for = []
ary, evt = cl.enqueue_map_buffer(
queue or self.queue, self.base_data, flags, self.offset,
- self.shape, self.dtype, strides=self.strides, wait_for=wait_for,
- is_blocking=is_blocking)
+ self.shape, self.dtype, strides=self.strides,
+ wait_for=wait_for + self.events, is_blocking=is_blocking)
if is_blocking:
return ary
@@ -1796,6 +1811,9 @@ class Array(object):
"""
queue = queue or self.queue or value.queue
+ if wait_for is None:
+ wait_for = []
+ wait_for = wait_for + self.events
if isinstance(subscript, Array):
if subscript.dtype.kind != "i":
@@ -2145,11 +2163,16 @@ def multi_take(arrays, indices, out=None, queue=None):
cl.kernel_work_group_info.WORK_GROUP_SIZE,
queue.device))
- knl(queue, gs, ls,
+ wait_for_this = (indices.events
+ + _builtin_sum((i.events for i in arrays[chunk_slice]), [])
+ + _builtin_sum((o.events for o in out[chunk_slice]), []))
+ evt = knl(queue, gs, ls,
indices.data,
*([o.data for o in out[chunk_slice]]
+ [i.data for i in arrays[chunk_slice]]
- + [indices.size]))
+ + [indices.size]), wait_for=wait_for_this)
+ for o in out[chunk_slice]:
+ o.add_event(evt)
return out
@@ -2219,7 +2242,10 @@ def multi_take_put(arrays, dest_indices, src_indices, dest_shape=None,
queue.device))
from pytools import flatten
- knl(queue, gs, ls,
+ wait_for_this = (dest_indices.events + src_indices.events
+ + _builtin_sum((i.events for i in arrays[chunk_slice]), [])
+ + _builtin_sum((o.events for o in out[chunk_slice]), []))
+ evt = knl(queue, gs, ls,
*([o.data for o in out[chunk_slice]]
+ [dest_indices.base_data,
dest_indices.offset,
@@ -2229,7 +2255,9 @@ def multi_take_put(arrays, dest_indices, src_indices, dest_shape=None,
(i.base_data, i.offset)
for i in arrays[chunk_slice]))
+ src_offsets_list[chunk_slice]
- + [src_indices.size]))
+ + [src_indices.size]), wait_for=wait_for_this)
+ for o in out[chunk_slice]:
+ o.add_event(evt)
return out
@@ -2244,6 +2272,9 @@ def multi_put(arrays, dest_indices, dest_shape=None, out=None, queue=None,
a_allocator = arrays[0].allocator
context = dest_indices.context
queue = queue or dest_indices.queue
+ if wait_for is None:
+ wait_for = []
+ wait_for = wait_for + dest_indices.events
vec_count = len(arrays)
@@ -2295,6 +2326,9 @@ def multi_put(arrays, dest_indices, dest_shape=None, out=None, queue=None,
queue.device))
from pytools import flatten
+ wait_for_this = (wait_for
+ + _builtin_sum((i.events for i in arrays[chunk_slice]), [])
+ + _builtin_sum((o.events for o in out[chunk_slice]), []))
evt = knl(queue, gs, ls,
*(
list(flatten(
@@ -2307,9 +2341,7 @@ def multi_put(arrays, dest_indices, dest_shape=None, out=None, queue=None,
+ [use_fill_cla.base_data, use_fill_cla.offset]
+ [array_lengths_cla.base_data, array_lengths_cla.offset]
+ [dest_indices.size]),
- **dict(wait_for=wait_for))
-
- # FIXME should wait on incoming events
+ **dict(wait_for=wait_for_this))
for o in out[chunk_slice]:
o.add_event(evt)
@@ -2387,7 +2419,8 @@ def diff(array, queue=None, allocator=None):
allocator = allocator or array.allocator
result = empty(queue, (n-1,), array.dtype, allocator=allocator)
- _diff(result, array, queue=queue)
+ event1 = _diff(result, array, queue=queue)
+ result.add_event(event1)
return result
@@ -2468,7 +2501,8 @@ def if_positive(criterion, then_, else_, out=None, queue=None):
if out is None:
out = empty_like(then_)
- _if_positive(out, criterion, then_, else_, queue=queue)
+ event1 = _if_positive(out, criterion, then_, else_, queue=queue)
+ out.add_event(event1)
return out
@@ -2501,7 +2535,10 @@ def sum(a, dtype=None, queue=None, slice=None):
"""
from pyopencl.reduction import get_sum_kernel
krnl = get_sum_kernel(a.context, dtype, a.dtype)
- return krnl(a, queue=queue, slice=slice)
+ result, event1 = krnl(a, queue=queue, slice=slice, wait_for=a.events,
+ return_event=True)
+ result.add_event(event1)
+ return result
def dot(a, b, dtype=None, queue=None, slice=None):
@@ -2510,7 +2547,10 @@ def dot(a, b, dtype=None, queue=None, slice=None):
"""
from pyopencl.reduction import get_dot_kernel
krnl = get_dot_kernel(a.context, dtype, a.dtype, b.dtype)
- return krnl(a, b, queue=queue, slice=slice)
+ result, event1 = krnl(a, b, queue=queue, slice=slice,
+ wait_for=a.events + b.events, return_event=True)
+ result.add_event(event1)
+ return result
def vdot(a, b, dtype=None, queue=None, slice=None):
@@ -2521,7 +2561,10 @@ def vdot(a, b, dtype=None, queue=None, slice=None):
from pyopencl.reduction import get_dot_kernel
krnl = get_dot_kernel(a.context, dtype, a.dtype, b.dtype,
conjugate_first=True)
- return krnl(a, b, queue=queue, slice=slice)
+ result, event1 = krnl(a, b, queue=queue, slice=slice,
+ wait_for=a.events + b.events, return_event=True)
+ result.add_event(event1)
+ return result
def subset_dot(subset, a, b, dtype=None, queue=None, slice=None):
@@ -2531,14 +2574,20 @@ def subset_dot(subset, a, b, dtype=None, queue=None, slice=None):
from pyopencl.reduction import get_subset_dot_kernel
krnl = get_subset_dot_kernel(
a.context, dtype, subset.dtype, a.dtype, b.dtype)
- return krnl(subset, a, b, queue=queue, slice=slice)
+ result, event1 = krnl(subset, a, b, queue=queue, slice=slice,
+ wait_for=subset.events + a.events + b.events, return_event=True)
+ result.add_event(event1)
+ return result
def _make_minmax_kernel(what):
def f(a, queue=None):
from pyopencl.reduction import get_minmax_kernel
krnl = get_minmax_kernel(a.context, what, a.dtype)
- return krnl(a, queue=queue)
+ result, event1 = krnl(a, queue=queue, wait_for=a.events,
+ return_event=True)
+ result.add_event(event1)
+ return result
return f
@@ -2558,8 +2607,10 @@ def _make_subset_minmax_kernel(what):
def f(subset, a, queue=None, slice=None):
from pyopencl.reduction import get_subset_minmax_kernel
krnl = get_subset_minmax_kernel(a.context, what, a.dtype, subset.dtype)
- return krnl(subset, a, queue=queue, slice=slice)
-
+ result, event1 = krnl(subset, a, queue=queue, slice=slice,
+ wait_for=a.events + subset.events, return_event=True)
+ result.add_event(event1)
+ return result
return f
@@ -2583,12 +2634,15 @@ def cumsum(a, output_dtype=None, queue=None,
if output_dtype is None:
output_dtype = a.dtype
+ if wait_for is None:
+ wait_for = []
result = a._new_like_me(output_dtype)
from pyopencl.scan import get_cumsum_kernel
krnl = get_cumsum_kernel(a.context, a.dtype, output_dtype)
- evt = krnl(a, result, queue=queue, wait_for=wait_for)
+ evt = krnl(a, result, queue=queue, wait_for=wait_for + a.events)
+ result.add_event(evt)
if return_event:
return evt, result
diff --git a/pyopencl/clmath.py b/pyopencl/clmath.py
index 73d390cf850e9a054541209069c322e67adf402a..6d45fe44ceb02fa13c7c6fb4563045e3aecdd87c 100644
--- a/pyopencl/clmath.py
+++ b/pyopencl/clmath.py
@@ -41,7 +41,8 @@ def _make_unary_array_func(name):
def f(array, queue=None):
result = array._new_like_me(queue=queue)
- knl_runner(result, array, queue=queue)
+ event1 = knl_runner(result, array, queue=queue)
+ result.add_event(event1)
return result
return f
@@ -78,7 +79,7 @@ def atan2(y, x, queue=None):
"""
queue = queue or y.queue
result = y._new_like_me(_get_common_dtype(y, x, queue))
- _atan2(result, y, x, queue=queue)
+ result.add_event(_atan2(result, y, x, queue=queue))
return result
@@ -92,7 +93,7 @@ def atan2pi(y, x, queue=None):
"""
queue = queue or y.queue
result = y._new_like_me(_get_common_dtype(y, x, queue))
- _atan2pi(result, y, x, queue=queue)
+ result.add_event(_atan2pi(result, y, x, queue=queue))
return result
@@ -130,7 +131,7 @@ def fmod(arg, mod, queue=None):
for each element in `arg` and `mod`."""
queue = (queue or arg.queue) or mod.queue
result = arg._new_like_me(_get_common_dtype(arg, mod, queue))
- _fmod(result, arg, mod, queue=queue)
+ result.add_event(_fmod(result, arg, mod, queue=queue))
return result
# TODO: fract
@@ -148,7 +149,9 @@ def frexp(arg, queue=None):
"""
sig = arg._new_like_me(queue=queue)
expt = arg._new_like_me(queue=queue, dtype=np.int32)
- _frexp(sig, expt, arg, queue=queue)
+ event1 = _frexp(sig, expt, arg, queue=queue)
+ sig.add_event(event1)
+ expt.add_event(event1)
return sig, expt
# TODO: hypot
@@ -169,7 +172,7 @@ def ldexp(significand, exponent, queue=None):
`result = significand * 2**exponent`.
"""
result = significand._new_like_me(queue=queue)
- _ldexp(result, significand, exponent)
+ result.add_event(_ldexp(result, significand, exponent))
return result
@@ -199,7 +202,9 @@ def modf(arg, queue=None):
"""
intpart = arg._new_like_me(queue=queue)
fracpart = arg._new_like_me(queue=queue)
- _modf(intpart, fracpart, arg, queue=queue)
+ event1 = _modf(intpart, fracpart, arg, queue=queue)
+ fracpart.add_event(event1)
+ intpart.add_event(event1)
return fracpart, intpart
@@ -254,18 +259,20 @@ def _hankel_01(h0, h1, x):
def bessel_jn(n, x, queue=None):
result = x._new_like_me(queue=queue)
- _bessel_jn(result, n, x, queue=queue)
+ result.add_event(_bessel_jn(result, n, x, queue=queue))
return result
def bessel_yn(n, x, queue=None):
result = x._new_like_me(queue=queue)
- _bessel_yn(result, n, x, queue=queue)
+ result.add_event(_bessel_yn(result, n, x, queue=queue))
return result
def hankel_01(x, queue=None):
h0 = x._new_like_me(queue=queue)
h1 = x._new_like_me(queue=queue)
- _hankel_01(h0, h1, x, queue=queue)
+ event1 = _hankel_01(h0, h1, x, queue=queue)
+ h0.add_event(event1)
+ h1.add_event(event1)
return h0, h1
diff --git a/test/test_algorithm.py b/test/test_algorithm.py
index b7b296ce959f2f9d92c290196e0a8f28b6043dc7..5264767c4094806fe43fdfea6056237aed20ade4 100644
--- a/test/test_algorithm.py
+++ b/test/test_algorithm.py
@@ -961,8 +961,14 @@ def test_bitonic_sort(ctx_factory, size, dtype):
from pyopencl.bitonic_sort import BitonicSort
s = clrandom.rand(queue, (2, size, 3,), dtype, luxury=None, a=0, b=239482333)
+ sgs = s.copy()
+ # enqueue_marker crashes under CL 1.1 pocl if there is anything to wait for
+ # (no clEnqueueWaitForEvents) https://github.com/inducer/pyopencl/pull/237
+ if (dev.platform.name == "Portable Computing Language"
+ and cl.get_cl_header_version() < (1, 2)):
+ sgs.finish()
sorter = BitonicSort(ctx)
- sgs, evt = sorter(s.copy(), axis=1)
+ sgs, evt = sorter(sgs, axis=1)
assert np.array_equal(np.sort(s.get(), axis=1), sgs.get())
@@ -1014,7 +1020,14 @@ def test_bitonic_argsort(ctx_factory, size, dtype):
sorterm = BitonicSort(ctx)
- ms, evt = sorterm(m.copy(), idx=index, axis=0)
+ ms = m.copy()
+ # enqueue_marker crashes under CL 1.1 pocl if there is anything to wait for
+ # (no clEnqueueWaitForEvents) https://github.com/inducer/pyopencl/pull/237
+ if (dev.platform.name == "Portable Computing Language"
+ and cl.get_cl_header_version() < (1, 2)):
+ ms.finish()
+ index.finish()
+ ms, evt = sorterm(ms, idx=index, axis=0)
assert np.array_equal(np.sort(m.get()), ms.get())
diff --git a/test/test_array.py b/test/test_array.py
index bca78f5ccbeebf1d86f9ec03a25ded6050bc4097..05008c169ae782a49b5b985c7a79780e337c5770 100644
--- a/test/test_array.py
+++ b/test/test_array.py
@@ -1213,6 +1213,79 @@ def test_multi_put(ctx_factory):
assert np.all(np.all(out_compare[i] == out_arrays[i].get()) for i in range(9))
+def test_outoforderqueue_get(ctx_factory):
+ context = ctx_factory()
+ try:
+ queue = cl.CommandQueue(context,
+ properties=cl.command_queue_properties.OUT_OF_ORDER_EXEC_MODE_ENABLE)
+ except Exception:
+ pytest.skip("out-of-order queue not available")
+ a = np.random.rand(10**6).astype(np.dtype('float32'))
+ a_gpu = cl_array.to_device(queue, a)
+ b_gpu = a_gpu + a_gpu**5 + 1
+ b1 = b_gpu.get() # testing that this waits for events
+ b = a + a**5 + 1
+ assert np.abs(b1 - b).mean() < 1e-5
+
+
+def test_outoforderqueue_copy(ctx_factory):
+ context = ctx_factory()
+ try:
+ queue = cl.CommandQueue(context,
+ properties=cl.command_queue_properties.OUT_OF_ORDER_EXEC_MODE_ENABLE)
+ except Exception:
+ pytest.skip("out-of-order queue not available")
+ a = np.random.rand(10**6).astype(np.dtype('float32'))
+ a_gpu = cl_array.to_device(queue, a)
+ c_gpu = a_gpu**2 - 7
+ b_gpu = c_gpu.copy() # testing that this waits for and creates events
+ b_gpu *= 10
+ queue.finish()
+ b1 = b_gpu.get()
+ b = 10 * (a**2 - 7)
+ assert np.abs(b1 - b).mean() < 1e-5
+
+
+def test_outoforderqueue_indexing(ctx_factory):
+ context = ctx_factory()
+ try:
+ queue = cl.CommandQueue(context,
+ properties=cl.command_queue_properties.OUT_OF_ORDER_EXEC_MODE_ENABLE)
+ except Exception:
+ pytest.skip("out-of-order queue not available")
+ a = np.random.rand(10**6).astype(np.dtype('float32'))
+ i = (8e5 + 1e5 * np.random.rand(10**5)).astype(np.dtype('int32'))
+ a_gpu = cl_array.to_device(queue, a)
+ i_gpu = cl_array.to_device(queue, i)
+ c_gpu = (a_gpu**2)[i_gpu - 10000]
+ b_gpu = 10 - a_gpu
+ b_gpu[:] = 8 * a_gpu
+ b_gpu[i_gpu + 10000] = c_gpu - 10
+ queue.finish()
+ b1 = b_gpu.get()
+ c = (a**2)[i - 10000]
+ b = 8 * a
+ b[i + 10000] = c - 10
+ assert np.abs(b1 - b).mean() < 1e-5
+
+
+def test_outoforderqueue_reductions(ctx_factory):
+ context = ctx_factory()
+ try:
+ queue = cl.CommandQueue(context,
+ properties=cl.command_queue_properties.OUT_OF_ORDER_EXEC_MODE_ENABLE)
+ except Exception:
+ pytest.skip("out-of-order queue not available")
+ # 0/1 values to avoid accumulated rounding error
+ a = (np.random.rand(10**6) > 0.5).astype(np.dtype('float32'))
+ a[800000] = 10 # all<5 looks true until near the end
+ a_gpu = cl_array.to_device(queue, a)
+ b1 = cl_array.sum(a_gpu).get()
+ b2 = cl_array.dot(a_gpu, 3 - a_gpu).get()
+ b3 = (a_gpu < 5).all().get()
+ assert b1 == a.sum() and b2 == a.dot(3 - a) and b3 == 0
+
+
if __name__ == "__main__":
# make sure that import failures get reported, instead of skipping the
# tests.
diff --git a/test/test_clmath.py b/test/test_clmath.py
index 553ed7a6f6ad4f93abde9e46b0bc5fb60a9066f0..beebc2a8c0ad717e7139c340bff14a07fb77b60c 100644
--- a/test/test_clmath.py
+++ b/test/test_clmath.py
@@ -447,6 +447,23 @@ def test_hankel_01_complex(ctx_factory, ref_src):
pt.show()
+def test_outoforderqueue_clmath(ctx_factory):
+ context = ctx_factory()
+ try:
+ queue = cl.CommandQueue(context,
+ properties=cl.command_queue_properties.OUT_OF_ORDER_EXEC_MODE_ENABLE)
+ except Exception:
+ pytest.skip("out-of-order queue not available")
+ a = np.random.rand(10**6).astype(np.dtype('float32'))
+ a_gpu = cl_array.to_device(queue, a)
+ # testing that clmath functions wait for and create events
+ b_gpu = clmath.fabs(clmath.sin(a_gpu * 5))
+ queue.finish()
+ b1 = b_gpu.get()
+ b = np.abs(np.sin(a * 5))
+ assert np.abs(b1 - b).mean() < 1e-5
+
+
if __name__ == "__main__":
import sys
if len(sys.argv) > 1: