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Episode 58 - Aaron Patterson

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Treść dostarczona przez Drew Bragg. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Drew Bragg lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

Ruby core team member Aaron Patterson (tenderlove) takes us deep into the cutting edge of Ruby's performance frontier in this technical exploration of how one of the world's most beloved programming languages continues to evolve.
At Shopify, Aaron works on two transformative projects: ZJIT, a method-based JIT compiler that builds on YJIT's success by optimizing register allocation to reduce memory spills, and enhanced Ractor support to enable true CPU parallelism in Ruby applications. He explains the fundamental differences between these approaches - ZJIT makes single CPU utilization more efficient, while Ractors allow Ruby code to run across multiple CPUs simultaneously.
The conversation reveals how real business needs drive language development. Shopify's production workloads unpredictably alternate between CPU-bound and IO-bound tasks, creating resource utilization challenges. Aaron's team aims to build auto-scaling web server infrastructure using Ractors that can dynamically adjust to workload characteristics - potentially revolutionizing how Ruby applications handle variable traffic patterns.
For developers interested in contributing to Rails, Aaron offers practical advice: start reading the source code, understand the architecture, and look for ways to improve it. He shares insights on the challenges of making Rails Ractor-safe, particularly around passing lambdas between Ractors while maintaining memory safety.
The episode concludes with a delightful tangent into Aaron's latest hardware project - building a color temperature sensor for camera calibration that combines his photography hobby with his programming expertise. True to form, even his leisure activities inevitably transform into coding projects.
Whether you're a seasoned Ruby developer or simply curious about language design and performance optimization, Aaron's unique blend of deep technical knowledge and playful enthusiasm makes this an engaging journey through Ruby's exciting future.

Send us some love.

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Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.
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Rozdziały

1. Introduction to Aaron Patterson (00:00:00)

2. ZJIT: A New Ruby JIT Compiler (00:03:09)

3. Ractors and Parallelism in Ruby (00:17:46)

4. Rails Core Work and Security (00:35:16)

5. Contributing to Rails (00:41:41)

6. Building a Color Temperature Sensor (00:51:35)

7. Closing Thoughts and Contact Info (01:01:03)

66 odcinków

Artwork
iconUdostępnij
 
Manage episode 506687165 series 3310917
Treść dostarczona przez Drew Bragg. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Drew Bragg lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.

Ruby core team member Aaron Patterson (tenderlove) takes us deep into the cutting edge of Ruby's performance frontier in this technical exploration of how one of the world's most beloved programming languages continues to evolve.
At Shopify, Aaron works on two transformative projects: ZJIT, a method-based JIT compiler that builds on YJIT's success by optimizing register allocation to reduce memory spills, and enhanced Ractor support to enable true CPU parallelism in Ruby applications. He explains the fundamental differences between these approaches - ZJIT makes single CPU utilization more efficient, while Ractors allow Ruby code to run across multiple CPUs simultaneously.
The conversation reveals how real business needs drive language development. Shopify's production workloads unpredictably alternate between CPU-bound and IO-bound tasks, creating resource utilization challenges. Aaron's team aims to build auto-scaling web server infrastructure using Ractors that can dynamically adjust to workload characteristics - potentially revolutionizing how Ruby applications handle variable traffic patterns.
For developers interested in contributing to Rails, Aaron offers practical advice: start reading the source code, understand the architecture, and look for ways to improve it. He shares insights on the challenges of making Rails Ractor-safe, particularly around passing lambdas between Ractors while maintaining memory safety.
The episode concludes with a delightful tangent into Aaron's latest hardware project - building a color temperature sensor for camera calibration that combines his photography hobby with his programming expertise. True to form, even his leisure activities inevitably transform into coding projects.
Whether you're a seasoned Ruby developer or simply curious about language design and performance optimization, Aaron's unique blend of deep technical knowledge and playful enthusiasm makes this an engaging journey through Ruby's exciting future.

Send us some love.

Honeybadger
Honeybadger is an application health monitoring tool built by developers for developers.
Judoscale
Autoscaling that actually works. Take control of your cloud hosting.
Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.
Support the show

  continue reading

Rozdziały

1. Introduction to Aaron Patterson (00:00:00)

2. ZJIT: A New Ruby JIT Compiler (00:03:09)

3. Ractors and Parallelism in Ruby (00:17:46)

4. Rails Core Work and Security (00:35:16)

5. Contributing to Rails (00:41:41)

6. Building a Color Temperature Sensor (00:51:35)

7. Closing Thoughts and Contact Info (01:01:03)

66 odcinków

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