cupy

I tried to use cupy in two parts of my program, one of them being parallelized with a pool. I managed to reproduce it with a simple example: import cupy import numpy as np from multiprocessing import pool def f(x): return cupy.asnumpy(2*cupy.array(x)) input = np.array([1,2,3,4]) print(cupy.asnumpy(cupy.array(input))) print(np.array(list(map(f, input)))) p = pool.Pool(4) output = p.map(f, input) p.close() p.join() print(output) The output is the following: [1 2 3 4] [2 4 6 8] Exception in thread Thread-3: Traceback (most recent call last): File "/usr/lib/python3.6/threading.py", line 916, in

Objective/Problem In Python, I am looking for a fast way to read/write data from a memory mapped file to a GPU. In a previous SO overflow post [ Cupy OutOfMemoryError when trying to cupy.load larger dimension .npy files in memory map mode, but np.load works fine ] Where it is mentioned this is possible using CUDA pinned "zero-copy" memory. Furthermore, it seems that this method was developed by this person [ cuda - Zero-copy memory, memory-mapped file ] though that person was working in C++. My previous attempts have been with Cupy, but I am open to any cuda methods. What I have tried so far I

I am trying to run chainer with GPU on google colab. This requires cupy installed however I fail to install this properly as it cannot find the cuda environment in my colab vm. Error message as follows... Collecting cupy Downloading cupy-2.4.0.tar.gz (1.7MB) 100% |████████████████████████████████| 1.7MB 740kB/s Complete output from command python setup.py egg_info: cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++ /tmp/tmpds3ikncy/a.cpp:1:10: fatal error: cublas_v2.h: No such file or directory #include ^~~~~~~~~~~~~ compilation terminated. Options: