GPU Acceleration in Python

Submission Number: 335
Submission ID: 4947
Submission UUID: 8f5a9ad8-301c-416f-8601-e120b736f980
Submission URI: /form/resource

Created: Thu, 11/21/2024 - 14:05
Completed: Thu, 11/21/2024 - 14:05
Changed: Fri, 03/14/2025 - 11:43

Remote IP address: 174.108.158.163
Submitted by: Joseph Telaak
Language: English

Is draft: No
Yes
GPU Acceleration in Python
Learning
machine-learning, big-data, data-analysis, optimization, parallelization, gpu, cuda, python
Beginner, Intermediate
This tutorial explains how to use Python for GPU acceleration with libraries like CuPy, PyOpenCL, and PyCUDA. It shows how these libraries can speed up tasks like array operations and matrix multiplication by using the GPU. Examples include replacing NumPy with CuPy for large datasets and using PyOpenCL or PyCUDA for more control with custom GPU kernels. It focuses on practical steps to integrate GPU acceleration into Python programs.
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