Python 3.8.2 : The numba python package - part 001 .

The development of this python package comes with this short intro:
Numba is a just-in-time compiler for Python that works best on code that uses NumPy arrays and functions and loops. The most common way to use Numba is through its collection of decorators that can be applied to your functions to instruct Numba to compile them. When a call is made to a Numba decorated function it is compiled to machine code “just-in-time” for execution and all or part of your code can subsequently run at native machine code speed!
I installed this python package on my folder Python38:

D:\Python38>pip3 install numba
Collecting numba
...
Successfully installed numba-0.50.1
D:\Python38>python.exe
Python 3.8.2 (tags/v3.8.2:7b3ab59, Feb 25 2020, 22:45:29) [MSC v.1916 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import numba
>>> numba.__version__
'0.50.1'

This package did not work with python install on the folder Python38_64:

D:\Python38_64>pip3 install numba
Collecting numba
...
Installing collected packages: numpy, llvmlite, numba
Successfully installed llvmlite-0.33.0 numba-0.50.1 numpy-1.19.1
WARNING: You are using pip version 20.1; however, version 20.1.1 is available.
...
D:\Python38_64>python.exe
Python 3.8.4 (tags/v3.8.4:dfa645a, Jul 13 2020, 16:46:45) [MSC v.1924 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import numba
Traceback (most recent call last):
...
ModuleNotFoundError: No module named 'numba'

You can write standard Python functions and run them on a CUDA-capable GPU.
First, I need to enable this feature:

D:\Python38>SET NUMBA_ENABLE_CUDASIM=1

D:\Python38>python
Python 3.8.2 (tags/v3.8.2:7b3ab59, Feb 25 2020, 22:45:29) [MSC v.1916 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> from numba import cuda
>>> print(cuda.gpus)
...Managed Device 0...

Let's test with a simple example to create a data and use it:

D:\Python38>python
Python 3.8.2 (tags/v3.8.2:7b3ab59, Feb 25 2020, 22:45:29) [MSC v.1916 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import time
>>> import numpy as np
>>> from numba import cuda
>>>
>>> @cuda.jit
... def create(data):
...     data[cuda.blockIdx.x, cuda.threadIdx.x] = cuda.blockIdx.x
...
>>> numBlocks = 4
>>> threadsPerBlock = 6
>>>
>>> data = np.ones((numBlocks, threadsPerBlock), dtype=np.uint8)
>>> create[numBlocks, threadsPerBlock](data)
>>> print(data)
[[0 0 0 0 0 0]
 [1 1 1 1 1 1]
 [2 2 2 2 2 2]
 [3 3 3 3 3 3]]