Optimizing Guile Scheme
David Thompson discusses optimizing Guile Scheme, highlighting strategies like minimizing memory allocation, using monomorphic functions, and employing profiling tools to enhance performance in game development and demanding applications.
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David Thompson discusses optimizing Guile Scheme, a niche programming language he appreciates. Guile, a Scheme dialect, includes an optimizing bytecode compiler and a JIT compiler, which can enhance performance, especially in game development. Thompson shares insights from his experience with Chickadee, a game programming library, emphasizing that while Scheme is dynamic and limits compile-time optimizations, developers can still improve performance by following specific rules. Key strategies include minimizing memory allocation and preferring monomorphic functions over polymorphic ones to reduce runtime overhead. He explains that avoiding unnecessary allocations can significantly enhance throughput, particularly in performance-critical sections of code, such as graphics rendering. Thompson also highlights the importance of using tools like profiling and bytecode disassembly to identify and address performance bottlenecks. He provides examples, such as optimizing a variadic function to handle a limited number of arguments efficiently, which can drastically reduce garbage collection time and improve execution speed. By applying these techniques, developers can achieve better performance in their Guile applications, making it a more viable option for real-time graphics and other demanding tasks.
- Guile Scheme features an optimizing bytecode compiler and JIT compiler for performance enhancement.
- Minimizing memory allocation and using monomorphic functions can significantly improve execution speed.
- Profiling and bytecode disassembly are essential tools for identifying performance issues.
- Optimizing variadic functions can reduce garbage collection time and improve efficiency.
- Thompson's insights are particularly relevant for game development and performance-sensitive applications.
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- There are mixed feelings about dynamically typed languages, with some users appreciating their simplicity while others express frustration over performance issues.
- Several commenters highlight the importance of inlining and optimization techniques, with requests for more detailed explanations of the optimizer's algorithms.
- Some users advocate for the use of more performant alternatives to Guile, such as Common Lisp or Chicken Scheme, citing known performance issues.
- There is a general appreciation for the resources and blogs available on optimizing Guile Scheme, particularly those by Andy Wingo.
- Concerns are raised about the need for high-level languages to abstract away performance details, suggesting that users should choose tools that meet their performance needs.
12 commentsAt the same time, they inevitably seem to lead to user stories like this where a user really does know exactly what types they're working with and wants the language to know that too (for performance or correctness), and they end up jumping through all sorts of insane hoops to get the optimizer to do exactly what they want.
Andy Wingo is the maintainer and I get a kick out of everything he posts.
Common Lisp/SBCL is usually sufficiently smart. I know not everyone likes Common Lisp, but at least I would have tested it with something more performant that Guile, like Chicken Scheme (my favorite!), Chez Scheme, etc.
I like Guile and its purpose as a universal scripting language. However, its performance issues are well known. Even compared to other scripting-first languages (Lua, Perl, Python etc).
On SICP, Guile badly needs a module for the picture language from the book (and srfi-203 + srfi-216).
Edit: nevermind, that's also dynamic dispatch. You'd have to add static dispatch via macros or some external transpilation step.
Has anyone had a positive experience?
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