def _setup_structs_on_device(self):
if self.backend == 'opencl':
import pyopencl as cl
import pyopencl.array # noqa: 401
import pyopencl.tools # noqa: 401
gpu = self._gpu_structs
cpu = self._cpu_structs
for k, v in cpu.items():
if v is None:
gpu[k] = v
else:
g_struct, code = cl.tools.match_dtype_to_c_struct(
self._ctx.devices[0], "dummy", v.dtype)
g_v = v.astype(g_struct)
gpu[k] = cl.array.to_device(self._queue, g_v)
if k in self._equations:
self._equations[k]._gpu = gpu[k]
else:
from pycuda import gpuarray
from compyle.cuda import match_dtype_to_c_struct
gpu = self._gpu_structs
cpu = self._cpu_structs
for k, v in cpu.items():
if v is None:
gpu[k] = v
else:
g_struct, code = match_dtype_to_c_struct(
None, "junk", v.dtype)
g_v = v.astype(g_struct)
gpu[k] = gpuarray.to_gpu(g_v)
if k in self._equations:
self._equations[k]._gpu = gpu[k]
def test_cuda_struct_mapping(self):
from compyle.cuda import match_dtype_to_c_struct
from pycuda import gpuarray
# Given
dtype = np.dtype([('l', np.int64),
('i', np.uint8),
('x', np.float32)])
a = np.empty(1, dtype)
a['l'] = 1.0
a['i'] = 2
a['x'] = 1.23
# When
gs1, code1 = match_dtype_to_c_struct(None, "junk", a.dtype)
a_ga = a.astype(gs1)
ga = gpuarray.to_gpu(a_ga)
# Then
result = ga.get()
np.testing.assert_almost_equal(result.tolist(), a.tolist())
self.assertFalse(a.dtype.fields == gs1.fields)