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
Skill Level:
Beginner (304), Intermediate (305)
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:
- GPU Acceleration in Python (https://docs.google.com/presentation/d/1iDLIcQ4lrKW1j3us6d7i2nILerep_BVx/edit?usp=sharing&ouid=103384712802153156527&rtpof=true&sd=true)
Tags:
machine-learning (272), big-data (4), data-analysis (422), optimization (509), parallelization (223), gpu (80), cuda (222), python (69)
Domain:
ACCESS CSSN (780), Campus Champions (572), CAREERS (323), CCMNet (835), Great Plains (311), Kentucky (322), Northeast (308)
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