I am using Ubuntu 16.04 and I am trying to execute this code:
import numpy as np
from timeit import default_timer as timer
from numba import vectorize
# This should be a substantially high value. On my test machine, this took
# 33 seconds to run via the CPU and just over 3 seconds on the GPU.
NUM_ELEMENTS = 100000000
# This is the CPU version.
def vector_add_cpu(a, b):
c = np.zeros(NUM_ELEMENTS, dtype=np.float32)
for i in range(NUM_ELEMENTS):
c[i] = a[i] + b[i]
return c
# This is the GPU version. Note the @vectorize decorator. This tells
# numba to turn this into a GPU vectorized function.
@vectorize(["float32(float32, float32)"], target='cuda')
def vector_add_gpu(a, b):
return a + b;
def main():
a_source = np.ones(NUM_ELEMENTS, dtype=np.float32)
b_source = np.ones(NUM_ELEMENTS, dtype=np.float32)
# Time the CPU function
start = timer()
vector_add_cpu(a_source, b_source)
vector_add_cpu_time = timer() - start
# Time the GPU function
start = timer()
vector_add_gpu(a_source, b_source)
vector_add_gpu_time = timer() - start
# Report times
print("CPU function took %f seconds." % vector_add_cpu_time)
print("GPU function took %f seconds." % vector_add_gpu_time)
return 0
if __name__ == "__main__":
main()
I got the error:
libNVVM cannot be found. Do conda install cudatoolkit:
library nvvm not found
I have followed https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#post-installation-actions but it is not working.
Could someone help me?