Python CUDA Installation & CUPY | GPU Acceleration Basics 01

CUPY is a Numpy-like array implementation for NVIDIA CUDA. In this video, I have walked through the installation process and the basics of CUPY. Python can compile and run NVIDIA CUDA accelerated applications. In this tutorial series learn to use CUDA on Python with cupy and numba. Accelerate your applications by leveraging the parallel processing of a GPU.

This second lecture is about installing CUDA toolkit from NVIDIA and doing our first acceleration using CUPY.

#python #cuda #nvidia #programming #coding #gpu

[taj-ulislam]

Unique information - hard to find. Much appreciate your effort.

[infernophoenix]

Just a quick question, does this method work even with laptops with AMD GPU's or this is only restricted to only NVIDIA GPU-type laptops

[ah_bb]

I wished i had knew about this before. Numpy uses a lot of ram and cpu. I was looking for a way to shift some of the data preprocessing workload onto the GPU. Does tensorflow recognise cupy arrays as valid input data types like numpy arrays? Great video.

[yadongwang]

thanks for sharing. So if I am using M1 Macbook. I can install the cupy in python and use Colab to mimic the GPU?

[gfxemwi]

Thank you! Tell me, can I put a ready-made script code in Python into this shell and run it through the GPU and not the CPU?

[cattnation]

will you help me? i can code but configration always sucks me