Is it possible to call __host__ functions in pyCUDA like you can __global__ functions? I noticed in the documentation that pycuda.driver.Function creates a handle to a __global__ function. __device__ functions can be called from a __global__ function, but __host__ code cannot. I'm aware that using a __host__ function pretty much defeats the purpose of pyCUDA, but there are some already made functions that I'd like to import and call as a proof of concept.
As a note, whenever I try to import the __host__ function, I get:
pycuda._driver.LogicError: cuModuleGetFunction failed: named symbol not found
No it is not possible.
This isn't a limitation of PyCUDA, per se, but of CUDA itself. The __host__ decorator just decays away to plain host code, and the CUDA APIs don't and cannot handle them in the same way that device code can be handled (note the the APIs also don't handle __device__ either, which is the true equivalent of __host__).
If you want to call/use __host__ functions from Python, you will need to use one of the standard C++/Python interoperability mechanisms, like ctypes or SWIG or boost python, etc.
Below, I'm providing a sample code to call CUDA APIs in pyCUDA. The code generates uniformly distributed random numbers and may serve as a reference to include already made functions (as the poster says and like CUDA APIs) in a pyCUDA code.
import numpy as np
import ctypes
import pycuda.driver as drv
import pycuda.gpuarray as gpuarray
import pycuda.autoinit
curand = CDLL("/usr/local/cuda/lib64/libcurand.so")
# --- Number of elements to generate
N = 10
# --- cuRAND enums
CURAND_RNG_PSEUDO_DEFAULT = 100
# --- Query the cuRAND version
i = c_ulonglong()
curand.curandGetVersion(byref(i))
print("curand version: ", i.value)
# --- Allocate space for generation
d_x = gpuarray.empty(N, dtype = np.float32)
# --- Create random number generator
gen = c_ulonglong()
curand.curandCreateGenerator(byref(gen), CURAND_RNG_PSEUDO_DEFAULT)
# --- Generate random numbers
curand.curandGenerateUniform(gen, ctypes.cast(d_x.ptr, POINTER(c_float)), N)
print(d_x)
