Jacob Tomlinson

Writing GPU code in Python is easier today than ever!

Summary Writing GPU code in Python is easier today than ever, and in this tutorial, I will share what I’ve learned and how you can get started with accelerating your code.

Writing GPU code in Python is easier today than ever!

Having a brand can help give your open source project some legitimacy, and you don’t need to be a designer to see these benefits.

Both Dask and RAPIDS are Python libraries to scale your workflow and empower you to process more data and leverage more compute resources.

This week was the 2021 Dask Summit and one of the workshops that we ran covered many deployment options for Dask Distributed.

At the Dask Summit I chaired a workshop called Deploying Dask.

At the Dask Summit I chaired a workshop called Deploying Dask.

With our open source project published on GitHub we probably want to allow folks to contribute changes.

Once your open source Python project has users and a community you will likely want to communicate with them in an official capacity.

Now that our open source Python project exists and users can install it we will want to turn our attention to sustainability, reach and ongoing maintenance.

Prometheus is a popular monitoring tool within the cloud community.

In part four of this series we discussed documenting our code as we went along by adding docstrings throughout out project.

RAPIDS is an end to end data science stack built entirely for CUDA GPUs.

In this post we will cover automatically packaging and releasing our project when a new git tag is pushed to GitHub.

In this post we will cover automatically running our tests when we push new code to GitHub, and when contributors raise Pull Requests against our project.

Python objects are synchronous by default.

What is test driven development (TDD)?

In this post we will cover testing our code.

High-throughput (task-based) computing is a flexible approach to parallelization.

This post will cover documenting our code.

Update: This was a fun experiment and I recommend you check out the post for a fun read on setting up reverse shells.

Writing code for GPUs has come a long way over the last few years and it is now easier than ever to get started.

Many open source projects are taking steps to update terminology to be more inclusive.

Hacktoberfest is approaching once again.

Originally published on the Dask blog on August 21st, 2020.

Originally published on the Dask blog on July 23rd, 2020.

A popular tool with streamers and YouTubers is Open Broadcaster Software®️ Studio or OBS for short.

⚠️ This post is no longer valid.

In this post we will cover making our code available to people.

The RAPIDS suite of open source software libraries (https://rapids.ai/) allow you to run data science and analytics pipelines entirely on GPUs, but following familiar Python APIs including Numpy, Pandas and SciKit Learn.

In this post, we will cover a few project hygiene things that we may want to put into place to make our lives easier in the future.

When you build a website you want pages to load as quickly as possible for users.

Have you had a great idea for an open-source Python library that you think people will find useful, but you don’t know where to begin in creating and publishing it?

Introduction It has been a few years since I published a list of technology and media I enjoyed this year, so here we go for 2019.

Applying for internships and entry-level positions can be tricky.

Note: This post is also available in Go flavour.

Note: This post is also available in Python flavour.

In my day to day work I generally access a variety of Jupyter installations.

Helm has become a pervasive tool in the Kubernetes community for packaging, managing, upgrading and distributing applications.

Sometimes when working with a new Kubernetes cluster you will be given a config file to use when authenticating with the cluster.

According to folks who enjoy outdoor activities there are three types of fun.

Choosing a good profile picture will make collaborating with others easier, especially if you haven’t met them yet.

Often when I’m developing or debugging in Python I end up creating throw away conda environments.

Originally published on the RAPIDS AI blog on August 13th, 2019.