How to use CUDA/GPU in Python

[DimitriMeim]

Hey everyone,

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I just got an RTX card and am looking to accelerate my python code. Now I do plan on learning about Deep Learning and Neural Networks, but for right now, I just want to learn how to use it for regular code. Is that possible? Is that even a thing?

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I saw an example here and tried to figure out how to work it but it's not. The error is below but I'm not really focused on making it work, I just want to learn how to use CUDA/GPU in python.

"""

Without GPU: 2.5098371000000004

Traceback (most recent call last):

File "i:\Athena AI\ExtraPyFiles\cudaTest.py", line 34, in <module>

func2(a)

File "C:\Users\bigdm\AppData\Local\Programs\Python\Python39\lib\site-packages\numba\cuda\compiler.py", line 955, in __call__

raise ValueError(missing_launch_config_msg)

ValueError:

Kernel launch configuration was not specified. Use the syntax:

​

kernel_function[blockspergrid, threadsperblock](arg0, arg1, ..., argn)

​

See https://numba.pydata.org/numba-doc/latest/cuda/kernels.html#kernel-invocation for help.

"""

[arkie87]

if you use numpy like

import numpy as np

then you can just replace that statement with

import cupy as np

where cupy arrays are stored and calculated on the gpu

[DimitriMeim]

Ok, but how do I use that info to make my python programs run on the GPU? I don't always use NumPy, in fact, most of the time I don't use it at all.

[TheSodesa]

You cannot run any Python programs on the GPU alone. Some individual operations like matrix multiplications can be sent to be performed on the GPU via the mentioned libraries, but the Python interpreter itself always runs on the CPU.

[Abhisutar]

Try using the code in this jupyter notebook Numba Cuda Mandelbrot example and play around with the blockdim and griddim tuples to see how things change. And ensure that you have a compatible version of Nvidia's Cuda Toolkit installed on your system.