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What does really happen when we call a method? How do the different Ruby implementations actually figure out what code to execute? What plumbing is going on under the hood to get a speedy dispatch? In this talk we will have a look at the internals of the the major Ruby implementations, focusing on their dispatch. From look-up tables and call site caches, to inlining and what on earth is invokedynamic? Fear not, all will be explained! Help us caption & translate this video! http://amara.org/v/FGfe/
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In the video titled "Message in a Bottle," Konstantin Haase delves into the internals of Ruby programming language implementations, analyzing how method dispatch is executed and optimized across different versions. The talk, presented at Aloha RubyConf 2012, seeks to demystify the operations that occur under the hood when methods are called in Ruby, ultimately uncovering strategies for enhancing performance. Key points discussed in the presentation include: - **Performance Overview**: Ruby versions 1.8 and 1.9 are interpreted languages, leading to inherent slowness. The focus shifts to Ruby 1.9 and the upcoming Ruby 2.0, as well as JRuby and Rubinus, to explore their dispatch mechanisms. - **Method Dispatch**: The majority of Ruby's performance concerns arise from method dispatch. Haase explains how each implementation utilizes different methods of caching, such as call-site caches and inline caches, to improve speed. - **Bytecode Representation**: Understanding the bytecode produced by each implementation is vital. Haase contrasts MRI’s and Rubinus's bytecode representations, demonstrating how they reflect the underlying operations. - **Optimizing Dispatch**: Strategies such as using inline caches and reducing CPU instructions can streamline method lookups. Haase illustrates how the method search process navigates through class inheritance to locate methods efficiently. - **Rubinus Features**: Rubinus's unique capabilities allow for runtime modifications of bytecode and method specialization, enhancing its performance via JIT compilation and LLVM (Low-Level Virtual Machine). - **JRuby Overview**: Haase briefly introduces JRuby's innovative use of "invoke dynamic" to enhance method dispatch efficiency by simplifying lookup processes in the JVM. The use of invoke dynamic eliminates the deep lookup overhead present in traditional method calls, optimizing overall execution. The talk concludes with actionable insights for developers looking to implement Ruby interpreters or seeking to optimize their Ruby code performance: prioritize minimizing CPU instructions, enhance method lookup speeds, and properly leverage available optimizations. Overall, effectiveness in Ruby execution hinges on foundational concepts of method dispatch and caching strategies.
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