Tyrone Krieger
I've been writing code since I was 11. Nearly two decades later, I'm still baffled by the fact that most developers spend only 32% of their time actually coding.
My professors used to say this was just the way things were. But instead of accepting it, I decided to push back. One step at a time.
Why? Because we can.
As developers, we build the tools that move entire industries forward. So why not turn that same energy inward and improve our own?
What I Love:
• Diving deep into complex codebases
• Sharing developer knowledge
• Building powerful tools (like CodeGlass)
• Exploring superconductors and the Meissner effect (hoverboards when?)
• I Like Trains
• Lizard Doggo
Sessions
Debugging performance and memory issues in Julia often requires combining multiple tools and correlating their outputs. Participants will learn how to use a runtime-level instrumentation approach to analyze and resolve performance issues in real code, including cases that are difficult to diagnose using existing tools.
Julia aggressively transforms your code during compilation and execution, which can make it difficult to see what actually runs. This can introduce subtle performance and memory costs that are not directly visible in existing tools. In this talk, we show a compiler and runtime instrumentation approach that provides a runtime-level view of program execution, links runtime behavior back to source code, and show how hidden costs can be uncovered and performance assumptions validated.
Julia was created by greedy programmers who wanted it all. What if we are equally greedy about tooling? This session invites discussion on missing capabilities in Julia’s development tools. What tools or workflows still fall short? Where should future efforts be made to improve productivity and insight?