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Foreign.
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Good afternoon, and thank you for coming to my presentation.
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Today, I will talk about the Ractor system, or simply put, Ractor.
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We introduced Ractors in Ruby 3.0.
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I want to review the current status and introduce our recent achievements and future work.
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Honestly speaking, the Ractor system is not used widely.
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There are some barriers, difficulties, and issues that I would like to discuss in this presentation.
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I believe that to solve these issues, we first need to improve the performance of the interpreter.
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In recent years, I have continued to work on improving this performance.
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Today, I want to show the current status of these improvements.
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Basically, I have been working on Ruby core, focusing on the virtual machine, garbage collector, and the memory management system for the Ractor system.
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I am also the author of the debug gem and a member of the Ruby BBS Association.
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There are great sponsors at the sponsoring area, so please stop by our sponsor booths.
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I won't be attending RubyKaigi tomorrow because I need to return home tonight, but please feel free to approach me during the next break if you have any questions.
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So, this is the basic idea: Ractors were introduced in Ruby 3.0 to enable parallel computing.
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However, there is a Global VM Lock (GVL) that prevents threads from executing in parallel, which limits concurrent computing capabilities.
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Ractor enables parallel programming on Ruby and can lead to faster Ruby applications.
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Moreover, Ractors support robust concurrent programming, which is essential because managing shared mutable states between concurrent entities is challenging.
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To avoid issues related to shared mutable states, we need to handle the Ractor system carefully to enjoy bug-free parallel programming.
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While Ractor programming looks promising, its adoption has been slow due to several challenges.
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Some difficulties stem from the programming model; Ractor requires additional knowledge that is not mature or widely understood.
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Additionally, the current implementation quality could be improved.
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So, I want to discuss these challenges today.
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In summary, Ractor provides a way to avoid bugs common in concurrent programming by isolating object spaces, where most objects are unshareable.
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If an object belongs to one Ractor, other Ractors cannot access it, which helps avoid concurrent bugs.
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However, to maintain this isolation, we might need to introduce some limitations in the Ruby language.
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To achieve compatibility with Ractors, there are some complex memory model constraints and limitations.
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The message passing API in Ractor has two types: the traditional actor system, which uses send and receive, and a more advanced style that requires both sender and receiver to communicate simultaneously.
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The latter style, while powerful, introduces complexity, particularly when integrating with multiple Ractors.
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To maintain object isolation, we must ensure that message passing avoids unintended sharing of mutable states.
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While Ractor offers benefits for concurrent programming, the current implementation quality may hinder its widespread usage.
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Maintaining Ractor systems can lead to performance degradation, especially during garbage collection, where we need to stop all Ractors to reclaim memory.
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This can introduce considerable overhead and latency, making it challenging to maintain efficient performance.
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To improve performance, I am focusing on various projects to enhance Ractor, including better garbage collection mechanisms and more efficient usage of native threads.
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In conclusion, while Ractor systems may currently face challenges, there are opportunities to improve their implementation and performance in the future.
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Moving forward, collaboration and contributions from the community will be vital for enhancing Ractor systems.
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Thank you for your attention, and I look forward to your questions.
