Blog
This is my blog! It has a bunch of posts!
Versioning Code at Scale, Part 2: Changing
In the last section, we discussed growing and breaking of software. Although these types of changes may encompass some plurality of the work done on any piece of software, we have left uncovered a majority of software work: changing.
ROCm Across Different Architectures: A Step-by-Step Guide
As an intrepid hacker of things I don't understand, I'm excited to share a straightforward approach to running ROCm workloads across multiple quasi-supported GPUs with different architectures. In this article, I'll walk you through the necessary steps and provide examples to get you started.
Versioning Code at Scale, Part 1: Growing & Breaking
Forty components, hundreds of consumers, fully hot-deployed. In this series, I'll explain how I made it work at Chatham without inciting our devs to pillory me.
Software Performance on Prospective E-Waste
I proudly still use my 2012-era i5 and spacious 120GB SSD. These parts have been through a lot, including falling down a few flights of stairs, but they're still ticking thanks to a bit of creative usage and clever engineering. The most important thing, though, is that they have not yet become e-waste.
Efficient Status Bars with Rust
AKA "How I sped up my desktop by 100x using Rust 🔥 🚀 ", AKA "How I learned to stop context switching and love the (fork) bomb"
Faster Progress Report 2
It's raining code! 0.4.0 is faster's biggest, most useful release yet.
Faster Progress Report 1
It's been a busy few weeks with faster! Faster has a test suite, "just works" on (almost) all architectures and CPUs, and has many more intrinsics and functions available.
Fast Rust in 2018
Rust is already a fast language, but there are still many opportunities to make it /the/ fast language. While many people will rightfully focus on usability, tooling, and community goals for 2018, I will focus on some exciting changes which will make Rust the star of HPC.
Emacs Lisp Profiling
Emacs lisp is /slow/. Like, really slow. Python can sum 1,000,000 numbers in less than a tenth of a second, while Emacs Lisp takes an order of magnitude longer.
Fast Math With Faster
What if I told you your numerical computations, encoders, and string operations could be up to 64x faster? What if we could make them that much faster without uglifying your code or touching more than one core, and without sacrificing portability?