Workshop: CuPY - calculating on GPUs made easy
ZOOM
Description: Scientific computing increasingly relies on GPU acceleration to handle large datasets and complex numerical tasks. While traditional CPU-based workflows remain essential, modern research benefits greatly from learning how to harness GPUs in an accessible way through Python. CuPY provides a NumPy-like interface that enables users to offload array computations to the GPU with minimal code changes.
On Day 1, we will cover the motivation for GPU computing, discuss what GPUs are best suited for, and set up a self-contained environment. Participants will learn to use conda/mamba for environment management, install and configure a GPU-ready CuPY setup, and verify its functionality. On Day 2, we will focus on the CuPY library itself. We will explore its syntax and functionality, emphasizing similarities and differences with NumPy. Through a series of simple examples, and culminating in a more involved case study, participants will gain the skills to confidently integrate GPU acceleration into their Python workflows.
Difficulty: Beginner
Date & Time:
Day 1: 26. 11. 2025 from 13.00 to 17.00
Day 2: 27. 11. 2025 from 13.00 to 17.00
Language: English
Prerequisite knowledge: Basic knowledge of Linux, the Terminal and some Python
Target audience: The workshop is intended for beginners and others interested in using GPUs with python.
Virtual location: ZOOM (only registered participants will see ZOOM link)
Workflow: The training is live over zoom, in the afternoon. The workshop will combine lecture and practical parts, where your own laptop suffices is needed to gain access to the ARNES gpu cluster.
Organizer:
Lecturer:
| Name: | Luka Leskovec |
| Description: | Scientist and educationalist involved in theoretical physics and supercomputing |
| E-mail: | luka.leskovec@fmf.uni-lj.si |
