def join(self, hdl):
# TODO - do something better to differentiate
if len(hdl) == 2:
# Join a kernel execution
(th, prgm) = hdl
cal_exec.join_stream(th)
for arr in prgm._remote_bindings_data.values():
binding = prgm._bindings[key]
if isinstance(arr, extarray.extarray):
arr.set_memory(bindings[1], arr.data_len * arr.itemsize)
elif isinstance(arr, numpy.ndarray) and HAS_NUMPY:
cal_exec.set_ndarray_ptr(arr, bindings[1])
elif len(hdl) == 3:
cal_exec.join_copy(self.ctx, hdl)
return
class Processor(spe.Processor):
exec_module = cal_exec
def __init__(self, device):
spe.Processor.__init__(self)
if device < 0 or device > N_GPUS:
raise Exception("Invalid device number %d" % device)
self.device = device
return
def execute(self, code, domain=None, async=False):
code.cache_code()
if domain is None:
try:
input = code.get_remote_binding("i0")
except KeyError:
raise Exception(
"No domain specified and no remote i0 register bound")
domain = (0, 0, input.gpu_width, len(input) / input.gpu_width)
if async:
th = cal_exec.run_stream_async(code.render_code, self.device,
domain, code._local_bindings,
code._remote_bindings,
code._copy_bindings)
return (th, code)
else:
cal_exec.run_stream(code.render_code, self.device, domain,
code._local_bindings, code._remote_bindings,
code._copy_bindings)
try:
import numpy
for (key, arr) in code._remote_bindings_data.items():
if isinstance(arr, extarray.extarray):
arr.set_memory(arr.gpu_mem_handle[0],
arr.data_len * arr.itemsize)
elif isinstance(arr, numpy.ndarray):
cal_exec.set_ndarray_ptr(arr,
code._remote_bindings[key][0])
for (key, arr) in code._copy_bindings_data.items():
if isinstance(arr, extarray.extarray):
arr.set_memory(arr.gpu_mem_handle[0],
arr.data_len * arr.itemsize)
elif isinstance(arr, numpy.ndarray):
cal_exec.set_ndarray_ptr(arr,
code._remote_bindings[key][0])
except ImportError:
for arr in code._remote_bindings_data.values():
arr.set_memory(arr.gpu_mem_handle[0],
arr.data_len * arr.itemsize)
for arr in code._copy_bindings_data.values():
arr.set_memory(arr.gpu_mem_handle[0],
arr.data_len * arr.itemsize)
return
if async:
th = cal_exec.run_stream_async(prgm.render_code,
self.ctx, domain, prgm._bindings)
return (th, prgm)
else:
cal_exec.run_stream(prgm.render_code, self.ctx, domain, prgm._bindings)
# Go through the bindings and re-set all the pointers
# When a kernel is executed, remote memory has to be unmapped and
# remapped, meaning the memory location can change.
for (key, arr) in prgm._bindings_data.items():
binding = prgm._bindings[key]
if isinstance(arr, extarray.extarray):
arr.set_memory(binding[1], arr.data_len * arr.itemsize)
elif isinstance(arr, numpy.ndarray) and HAS_NUMPY:
cal_exec.set_ndarray_ptr(arr, binding[1])
return
def join(self, hdl):
# TODO - do something better to differentiate
if len(hdl) == 2:
# Join a kernel execution
(th, prgm) = hdl
cal_exec.join_stream(th)
for arr in prgm._remote_bindings_data.values():
binding = prgm._bindings[key]
if isinstance(arr, extarray.extarray):
arr.set_memory(bindings[1], arr.data_len * arr.itemsize)
elif isinstance(arr, numpy.ndarray) and HAS_NUMPY:
