Free resources
GPU and parallel computing
Vectors, worker processes and a GPU kernel launch simulated in Python.
NumPy, worker processes and a GPU kernel launch simulated in Python in a JupyterLab. There is no GPU in the lab: you learn the model a GPU is built on.
Hands-on labs
Hands-on lessons
Every lesson here is worked in a hands-on lab: a real environment with a terminal beside it, nothing to install. A free account runs every lab, with enough free credit each month to follow most lessons, and is given the basic lessons on Home; with no account you can run the Git lab and the SQL lab.
Hands-on lesson · container lab
Parallel Computing Basics
Work through this lesson in a real lab, with a terminal beside it, not just by reading.
A private JupyterLab for each student with six short scripts on parallel computing and the model a GPU is built on. There is no GPU. Code on GitHub.
How it works · Source on GitHub · Create a free account to run it
Basic lessons are given to every free account, on Home, and to every college. Full course lessons are for colleges. Labs marked as an Ubuntu VM lab are set by a teacher in a module, and their lessons start the VM for you.
Run these yourself
A free personal account runs every lab here and its lesson, with enough free credit each month to follow most lessons. Teaching a class? Start a college and set them for your students.
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