def test_realign_numpy_array(self):
import numpy
a = numpy.empty(1000, dtype=numpy.float32)
a = cl.realign_array(a, 1056, numpy)
self.assertEqual(a.__array_interface__["data"][0] % 1056, 0)
a = numpy.empty(1024, dtype=numpy.float32)
a = cl.realign_array(a, 4096, numpy)
self.assertEqual(a.__array_interface__["data"][0] % 4096, 0)
def test_realign_numpy_array(self):
import numpy
a = numpy.empty(1000, dtype=numpy.float32)
a = cl.realign_array(a, 1056, numpy)
self.assertEqual(a.__array_interface__["data"][0] % 1056, 0)
a = numpy.empty(1024, dtype=numpy.float32)
a = cl.realign_array(a, 4096, numpy)
self.assertEqual(a.__array_interface__["data"][0] % 4096, 0)
def ocl_realign_mem(self):
"""We are using CL_MEM_USE_HOST_PTR, so memory should be PAGE-aligned.
"""
if isinstance(self.device, NumpyDevice) or \
self.device.device_info.memalign <= 4096:
memalign = 4096
else:
memalign = self.device.device_info.memalign
self.mem = cl.realign_array(self._mem, memalign, numpy)
def ocl_realign_mem(self):
"""We are using CL_MEM_USE_HOST_PTR, so memory should be PAGE-aligned.
"""
if isinstance(self.device, NumpyDevice) or \
self.device.device_info.memalign <= 4096:
memalign = 4096
else:
memalign = self.device.device_info.memalign
self.mem = cl.realign_array(self._mem, memalign, numpy)
def test_realign_numpy_array(self):
try:
import numpy
except ImportError: # for pypy
try:
import numpypy as numpy
except ImportError:
raise ImportError("Could not import numpy")
a = numpy.empty(1000, dtype=numpy.float32)
a = cl.realign_array(a, 1056, numpy)
self.assertEqual(a.__array_interface__["data"][0] % 1056, 0)
def test():
print(os.environ.get("PYOPENCL_CTX"))
os.environ["PYOPENCL_CTX"] = "0:0"
# Create platform, context, program, kernel and queue
platforms = cl.Platforms()
print("OpenCL devices:\n%s" % platforms.dump_devices())
ctx = platforms.create_some_context()
queue = ctx.create_queue(ctx.devices[0], cl.CL_QUEUE_PROFILING_ENABLE)
'''
prg = ctx.create_program(
"""
__kernel void test(
__global float *a,
__global float *b,
const float c)
{
size_t i = get_global_id(0);
a[i] = (a[i] + b[i]) * c;
}
""")
'''
prg = ctx.create_program(testopencl.readoclfile("test.cl"))
krn = prg.get_kernel("test")
# Create arrays with some values for testing
a = np.arange(100000, dtype=np.float32)
b = np.cos(a)
a = np.sin(a)
a_copy = a.copy()
# Prepare arrays for use with map_buffer
a = cl.realign_array(a, queue.device.memalign, np)
b = cl.realign_array(b, queue.device.memalign, np)
c = np.array([0.1], dtype=np.float32)
d = (a + b) * c[0]
# Create buffers
a_ = ctx.create_buffer(cl.CL_MEM_READ_WRITE | cl.CL_MEM_USE_HOST_PTR,
a)
b_ = ctx.create_buffer(cl.CL_MEM_READ_WRITE | cl.CL_MEM_USE_HOST_PTR,
b)
# Set kernel arguments
krn.set_args(a_, b_, c[0:1])
# Execute kernel
global_size = [a.size]
local_size = None
queue.execute_kernel(krn, global_size, local_size, need_event=False)
# Get results back from the device by map_buffer
ev, ptr = queue.map_buffer(a_, cl.CL_MAP_READ, a.nbytes)
del ev
queue.unmap_buffer(a_, ptr).wait()
print(a - d)
aa = np.zeros(a.shape, dtype=a.dtype)
queue.read_buffer(a_, aa)
print(aa - d)
# Refill buffer with stored copy by write_buffer
ev = queue.write_buffer(a_, a_copy, blocking=False, need_event=True)
# Execute kernel
ev = queue.execute_kernel(krn,
global_size,
local_size,
wait_for=(ev, ))
# Get results back from the device by map_buffer
ev, ptr = queue.map_buffer(a_,
cl.CL_MAP_READ,
a.nbytes,
wait_for=(ev, ),
need_event=True)
ev.wait()
queue.unmap_buffer(a_, ptr).wait()
print(a - d)
bb = np.zeros(a.shape, dtype=a.dtype)
queue.read_buffer(a_, bb)
print(bb - d)
del queue
del ctx
del krn
del prg
gc.collect()
def cuda_realign_mem(self):
# We expect numpy array with continuous memory layout, so realign it.
# PAGE-boundary alignment may increase speed also.
self.mem = cl.realign_array(self._mem, 4096, numpy)
def test_create_sub_buffer(self):
import numpy
# Create platform, context, program, kernel and queue
platforms = cl.Platforms()
ctx = platforms.create_some_context()
prg = ctx.create_program(self.src_test, self.include_dirs)
krn = prg.get_kernel("test")
queue = ctx.create_queue(ctx.devices[0])
# Create arrays with some values for testing
a = numpy.arange(100000, dtype=numpy.float32)
b = numpy.cos(a)
a = numpy.sin(a)
# Prepare arrays for use with map_buffer
a = cl.realign_array(a, queue.device.memalign, numpy)
b = cl.realign_array(b, queue.device.memalign, numpy)
c = numpy.array([1.2345], dtype=numpy.float32)
d = a[1024:1024 + 4096] + b[2048:2048 + 4096] * c[0]
# Create buffers
a_parent_ = ctx.create_buffer(
cl.CL_MEM_READ_WRITE | cl.CL_MEM_USE_HOST_PTR, a)
self.assertEqual(a_parent_._n_refs, 1)
a_ = a_parent_.create_sub_buffer(4096, 16384)
self.assertEqual(a_parent_._n_refs, 2)
self.assertEqual(a_._n_refs, 1)
b_parent_ = ctx.create_buffer(
cl.CL_MEM_READ_WRITE | cl.CL_MEM_USE_HOST_PTR, b)
self.assertEqual(b_parent_._n_refs, 1)
b_ = b_parent_.create_sub_buffer(8192, 16384)
self.assertEqual(b_parent_._n_refs, 2)
self.assertEqual(b_._n_refs, 1)
# Set kernel arguments
krn.set_args(a_, b_, c[0:1])
# Execute kernel
global_size = [4096]
local_size = None
queue.execute_kernel(krn, global_size, local_size, need_event=False)
# Get results back from the device by map_buffer
ev, ptr = queue.map_buffer(a_, cl.CL_MAP_READ, a_.size)
del ev
queue.unmap_buffer(a_, ptr).wait()
self.assertLess(
numpy.fabs(a[1024:1024 + 4096] - d).max(), 0.0001,
"Incorrect result after map_buffer")
# Get results back from the device by read_buffer
aa = numpy.zeros(4096, dtype=numpy.float32)
queue.read_buffer(a_, aa)
self.assertLess(
numpy.fabs(aa - d).max(), 0.0001,
"Incorrect result after read_buffer")
del b_
self.assertIn(b_parent_._n_refs, (1, 2))
logging.info(
"test_create_sub_buffer: "
"b_parent_._n_refs = %d (expected 1 or 2)", b_parent_._n_refs)
del a_
self.assertIn(a_parent_._n_refs, (1, 2))
logging.info(
"test_create_sub_buffer: "
"a_parent_._n_refs = %d (expected 1 or 2)", a_parent_._n_refs)
def test_api_numpy(self):
import numpy
# Create platform, context, program, kernel and queue
platforms = cl.Platforms()
ctx = platforms.create_some_context()
prg = ctx.create_program(self.src_test, self.include_dirs)
krn = prg.get_kernel("test")
queue = ctx.create_queue(ctx.devices[0])
# Create arrays with some values for testing
a = numpy.arange(100000, dtype=numpy.float32)
b = numpy.cos(a)
a = numpy.sin(a)
a_copy = a.copy()
# Prepare arrays for use with map_buffer
a = cl.realign_array(a, queue.device.memalign, numpy)
b = cl.realign_array(b, queue.device.memalign, numpy)
c = numpy.array([1.2345], dtype=numpy.float32)
d = a + b * c[0]
# Create buffers
a_ = ctx.create_buffer(cl.CL_MEM_READ_WRITE | cl.CL_MEM_USE_HOST_PTR,
a)
b_ = ctx.create_buffer(cl.CL_MEM_READ_WRITE | cl.CL_MEM_USE_HOST_PTR,
b)
# Set kernel arguments
krn.set_args(a_, b_, c[0:1])
# Execute kernel
global_size = [a.size]
local_size = None
queue.execute_kernel(krn, global_size, local_size, need_event=False)
# Get results back from the device by map_buffer
ev, ptr = queue.map_buffer(a_, cl.CL_MAP_READ, a.nbytes)
del ev
queue.unmap_buffer(a_, ptr).wait()
self.assertLess(
numpy.fabs(a - d).max(), 0.0001,
"Incorrect result after map_buffer")
# Get results back from the device by read_buffer
aa = numpy.zeros(a.shape, dtype=a.dtype)
queue.read_buffer(a_, aa)
self.assertLess(
numpy.fabs(aa - d).max(), 0.0001,
"Incorrect result after read_buffer")
# Refill buffer with stored copy by map_buffer with event
ev, ptr = queue.map_buffer(
a_,
cl.CL_MAP_WRITE if queue.device.version < 1.1999 else
cl.CL_MAP_WRITE_INVALIDATE_REGION,
a.nbytes,
blocking=False,
need_event=True)
ev.wait()
a[:] = a_copy[:]
ev = queue.unmap_buffer(a_, ptr)
# Execute kernel
ev = queue.execute_kernel(krn,
global_size,
local_size,
wait_for=(ev, ))
# Get results back from the device by map_buffer
ev, ptr = queue.map_buffer(a_,
cl.CL_MAP_READ,
a.nbytes,
wait_for=(ev, ),
need_event=True)
ev.wait()
queue.unmap_buffer(a_, ptr).wait()
self.assertLess(
numpy.fabs(a - d).max(), 0.0001,
"Incorrect result after map_buffer")
# Refill buffer with stored copy by write_buffer
ev = queue.write_buffer(a_, a_copy, blocking=False, need_event=True)
# Execute kernel
ev = queue.execute_kernel(krn,
global_size,
local_size,
wait_for=(ev, ))
# Get results back from the device by map_buffer
ev, ptr = queue.map_buffer(a_,
cl.CL_MAP_READ,
a.nbytes,
wait_for=(ev, ),
need_event=True)
ev.wait()
queue.unmap_buffer(a_, ptr).wait()
self.assertLess(
numpy.fabs(a - d).max(), 0.0001,
"Incorrect result after map_buffer")
def test_create_sub_buffer(self):
import numpy
# Create platform, context, program, kernel and queue
platforms = cl.Platforms()
ctx = platforms.create_some_context()
prg = ctx.create_program(self.src_test, self.include_dirs)
krn = prg.get_kernel("test")
queue = ctx.create_queue(ctx.devices[0])
# Create arrays with some values for testing
a = numpy.arange(100000, dtype=numpy.float32)
b = numpy.cos(a)
a = numpy.sin(a)
# Prepare arrays for use with map_buffer
a = cl.realign_array(a, queue.device.memalign, numpy)
b = cl.realign_array(b, queue.device.memalign, numpy)
c = numpy.array([1.2345], dtype=numpy.float32)
d = a[1024:1024 + 4096] + b[2048:2048 + 4096] * c[0]
# Create buffers
a_parent_ = ctx.create_buffer(
cl.CL_MEM_READ_WRITE | cl.CL_MEM_USE_HOST_PTR, a)
self.assertEqual(a_parent_._n_refs, 1)
a_ = a_parent_.create_sub_buffer(4096, 16384)
self.assertEqual(a_parent_._n_refs, 2)
self.assertEqual(a_._n_refs, 1)
b_parent_ = ctx.create_buffer(
cl.CL_MEM_READ_WRITE | cl.CL_MEM_USE_HOST_PTR, b)
self.assertEqual(b_parent_._n_refs, 1)
b_ = b_parent_.create_sub_buffer(8192, 16384)
self.assertEqual(b_parent_._n_refs, 2)
self.assertEqual(b_._n_refs, 1)
# Set kernel arguments
krn.set_args(a_, b_, c[0:1])
# Execute kernel
global_size = [4096]
local_size = None
queue.execute_kernel(krn, global_size, local_size, need_event=False)
# Get results back from the device by map_buffer
ev, ptr = queue.map_buffer(a_, cl.CL_MAP_READ, a_.size)
del ev
queue.unmap_buffer(a_, ptr).wait()
self.assertLess(numpy.fabs(a[1024:1024 + 4096] - d).max(), 0.0001,
"Incorrect result after map_buffer")
# Get results back from the device by read_buffer
aa = numpy.zeros(4096, dtype=numpy.float32)
queue.read_buffer(a_, aa)
self.assertLess(numpy.fabs(aa - d).max(), 0.0001,
"Incorrect result after read_buffer")
del b_
self.assertIn(b_parent_._n_refs, (1, 2))
logging.info("test_create_sub_buffer: "
"b_parent_._n_refs = %d (expected 1 or 2)",
b_parent_._n_refs)
del a_
self.assertIn(a_parent_._n_refs, (1, 2))
logging.info("test_create_sub_buffer: "
"a_parent_._n_refs = %d (expected 1 or 2)",
a_parent_._n_refs)
def test_api_numpy(self):
import numpy
# Create platform, context, program, kernel and queue
platforms = cl.Platforms()
ctx = platforms.create_some_context()
prg = ctx.create_program(self.src_test, self.include_dirs)
krn = prg.get_kernel("test")
queue = ctx.create_queue(ctx.devices[0])
# Create arrays with some values for testing
a = numpy.arange(100000, dtype=numpy.float32)
b = numpy.cos(a)
a = numpy.sin(a)
a_copy = a.copy()
# Prepare arrays for use with map_buffer
a = cl.realign_array(a, queue.device.memalign, numpy)
b = cl.realign_array(b, queue.device.memalign, numpy)
c = numpy.array([1.2345], dtype=numpy.float32)
d = a + b * c[0]
# Create buffers
a_ = ctx.create_buffer(cl.CL_MEM_READ_WRITE | cl.CL_MEM_USE_HOST_PTR,
a)
b_ = ctx.create_buffer(cl.CL_MEM_READ_WRITE | cl.CL_MEM_USE_HOST_PTR,
b)
# Set kernel arguments
krn.set_args(a_, b_, c[0:1])
# Execute kernel
global_size = [a.size]
local_size = None
queue.execute_kernel(krn, global_size, local_size, need_event=False)
# Get results back from the device by map_buffer
ev, ptr = queue.map_buffer(a_, cl.CL_MAP_READ, a.nbytes)
del ev
queue.unmap_buffer(a_, ptr).wait()
self.assertLess(numpy.fabs(a - d).max(), 0.0001,
"Incorrect result after map_buffer")
# Get results back from the device by read_buffer
aa = numpy.zeros(a.shape, dtype=a.dtype)
queue.read_buffer(a_, aa)
self.assertLess(numpy.fabs(aa - d).max(), 0.0001,
"Incorrect result after read_buffer")
# Refill buffer with stored copy by map_buffer with event
ev, ptr = queue.map_buffer(
a_, cl.CL_MAP_WRITE if queue.device.version < 1.1999
else cl.CL_MAP_WRITE_INVALIDATE_REGION, a.nbytes,
blocking=False, need_event=True)
ev.wait()
a[:] = a_copy[:]
ev = queue.unmap_buffer(a_, ptr)
# Execute kernel
ev = queue.execute_kernel(krn, global_size, local_size, wait_for=(ev,))
# Get results back from the device by map_buffer
ev, ptr = queue.map_buffer(a_, cl.CL_MAP_READ, a.nbytes,
wait_for=(ev,), need_event=True)
ev.wait()
queue.unmap_buffer(a_, ptr).wait()
self.assertLess(numpy.fabs(a - d).max(), 0.0001,
"Incorrect result after map_buffer")
# Refill buffer with stored copy by write_buffer
ev = queue.write_buffer(a_, a_copy, blocking=False, need_event=True)
# Execute kernel
ev = queue.execute_kernel(krn, global_size, local_size, wait_for=(ev,))
# Get results back from the device by map_buffer
ev, ptr = queue.map_buffer(a_, cl.CL_MAP_READ, a.nbytes,
wait_for=(ev,), need_event=True)
ev.wait()
queue.unmap_buffer(a_, ptr).wait()
self.assertLess(numpy.fabs(a - d).max(), 0.0001,
"Incorrect result after map_buffer")
def cuda_realign_mem(self):
# We expect numpy array with continuous memory layout, so realign it.
# PAGE-boundary alignment may increase speed also.
self.mem = cl.realign_array(self._mem, 4096, numpy)