Matt Godbolt: Software Testing, Performance Tuning, and Code Handoff for Data Scientists

Data scientists and ML engineers write a lot of code: building
data pipelines, wiring up models, and sometimes translating
concepts from research papers into algorithms.  


Once in a while, that code runs into performance problems. 
These can be painful to debug when you don't come from a formal
software development background.  That's why Formulatedby's
Senior Content Advisor Q McCallum rang up Matt Godbolt to learn
the deep details of software testing, tracing performance bugs,
working with data at scale, and how data scientists can work with
developers to prepare their code for a production handoff.


Matt Godbolt has more than 30 years' experience writing
code.  He's spent most of that time working in the
performance-focused environments of console video games,
high-frequency trading (HFT), and algorithmic trading.  Matt
is the creator of the Compiler Explorer website, and also co-host
of the Two's Complement podcast.


(Note from Q: My audio is a little choppy, but Matt's is
perfect.  And you're here to hear him, anyway...)


 


Matt and Q mentioned a few links during their talk:


Michael Abrash’s Zen of Code Optimization

Brendan Gregg’s Flame Graphs

Matt's blog and videos

Related to the discussion on performance enhancements in
Quake, Matt has a video on “how Wolfenstein worked”

Compiler Explorer