is this something I do a 'root' ? Or via PyCuda? I am afraid I wont have access to 'root'
On Thu, Dec 3, 2015 at 6:01 PM, Andreas Kloeckner <li...@informa.tiker.net> wrote: > Keith Brown <keith6...@gmail.com> writes: > >> I have several GPUs and I want to distribute my tasks to each GPU. I >> would like to use multiprocessing.Pool() to accomplish it >> >> import random >> import pycuda.gpuarray as gpuarray >> import atexit >> import pycuda.driver as cuda >> import pycuda.autoinit as autoinit >> import time >> import numpy as np >> import skcuda.linalg as linalg >> import skcuda >> import multiprocessing as mp >> import pycuda.driver as drv >> >> def my_proc(n): >> drv.init() >> dev = drv.Device(n) >> ctx = dev.make_context() >> atexit.register(ctx.pop) >> linalg.init() >> a=np.ones((185,185)).astype(np.float32) >> a_gpu = gpuarray.to_gpu(a) >> c_gpu = linalg.dot(a_gpu,a_gpu) >> return c_gpu.get() >> >> r=[] >> Pool=mp.Pool(10) >> for i in range(1000): >> Pool.apply_async(my_proc,(random.randint(0,1),)) >> >> >> I keep getting >> pycuda._driver.LogicError: cuCtxPopCurrent failed: invalid device context >> >> Is there somthing I should be doing? > > If you have the GPUs set to exclusive mode, then PyCUDA should take care > of round-robin device selection on its own. > > Andreas > _______________________________________________ PyCUDA mailing list PyCUDA@tiker.net http://lists.tiker.net/listinfo/pycuda
