Heap Optimizations for Go Systems & Tools for Cross Compilation @ GoSF Meetup

➤➤ TALK 1 ➤➤ Lightening Talk
Can it compile? Tools for cross compilation

➤➤ SPEAKER BIO➤➤
Miriah Peterson is a Data Reliability Engineer, Conference Organizer, Twitch Coder, and Speaker, and is currently a Member of the Technical Staff at Tailscale. She graduated from Brigham Young University in 2017 with a Bachelor’s degree in Physics. She attended one semester of graduate school at the University of Oklahoma in 2017, but dropped out to start a career as a software engineer. Sharing knowledge and experiences is a focus Miriah’s career. She has given many talks on machine learning, data engineering, and data architecture strategy. Additionally she works in the community as a board member for the Forge Foundation Inc and organizer of GoWest Conference, WomenWhoGo Utah meetup, and Machine Learning Utah meetup.

➤➤ TALK 2 ➤➤
Heap Optimizations for Go Systems
Go programs are susceptible to severe performance regressions at large scale due to garbage collection (GC), resulting in degraded user experience. Learn about how Go GC works, and how to lower its impact on your program’s performance!

This is a tech talk intended to teach developers intermediate-level memory management techniques of large-scale & low latency systems, written in a garbage-collected language like Go. This session focuses on the specifics of the Go language, but the lessons are transferrable to diagnosing performance issues related to memory management in other languages as well. The aim is to teach developers about the internals of garbage collection using some real production examples running on thousands of nodes, how it may impact them, and provide a comprehensive review of modern profiling tools to diagnose and remedy the issue.

➤➤ SPEAKER BIO➤➤

“I am the Engineering Manager for the Ads Serving Platform team at Pinterest. We own the infrastructure used by 100+ engineers across the Monetization org to develop the models, products, and algorithms that power our $3B+/year ad business. I am also on the Go Enterprise Advisory Board, providing feedback directly to the Go team at Google for future improvements and features of the language. Outside of work, I enjoy exploring the Bay Area, discovering new restaurants and bars, and going on the occasional hike. You can find me on LinkedIn and Medium.”
Go programs are susceptible to severe performance regressions at large scale due to garbage collection (GC), resulting in degraded user experience. Learn about how Go GC works, and how to lower its impact on your program’s performance!