draft.py

__author__ = "hervemarie-nelly"
import pycuda
import pycuda.driver as cuda
from pycuda.compiler import SourceModule
import multiprocessing
import numpy


class GPUProcess(multiprocessing.Process):
    def __init__(self, number, some_array):
        multiprocessing.Process.__init__(self)
        self.number = number
        self.some_array = some_array

    def run(self):
        cuda.init()  # INITIALISE HERE
        self.dev = cuda.Device(self.number)
        self.ctx = self.dev.make_context()

        self.array_gpu = cuda.mem_alloc(some_array.nbytes)
        cuda.memcpy_htod(self.array_gpu, some_array)

        test_kernel(self.array_gpu)
        print("successful exit from thread %d" % self.number)
        self.ctx.pop()

        del self.array_gpu
        del self.ctx


def test_kernel(input_array_gpu):
    mod = SourceModule(
        """
         __global__ void f(float * out, float * in)
        {
             int idx = threadIdx.x;
             out[idx] = in[idx] + 6;
         }
         """
    )
    func = mod.get_function("f")
    output_array = numpy.zeros((1, 512))
    output_array_gpu = cuda.mem_alloc(output_array.nbytes)
    func(output_array_gpu, input_array_gpu, block=(512, 1, 1))
    cuda.memcpy_dtoh(output_array, output_array_gpu)
    return output_array


# cuda.init() #COMMENT HERE
some_array = numpy.ones((1, 512), dtype=numpy.float32)
# num = cuda.Device.count() #COMMENT HERE
num = 2

gpu_process_list = []
for i in range(num):
    gpu_process = GPUProcess(i, some_array)
    gpu_process.start()
    gpu_process_list.append(gpu_process)