Submission information
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
Webform: Knowledge Base Resources
| Approved | Yes |
|---|---|
| Title | GPU Acceleration in Python |
| Category | Learning |
| Tags | machine-learning, big-data, data-analysis, optimization, parallelization, gpu, cuda, python |
| Skill Level | Beginner, Intermediate |
| Description | 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. |
| Link to Resource | |
| Domain | ACCESS CSSN, Campus Champions, CAREERS, CCMNet, Great Plains, Kentucky, Northeast |