Ruby 3.5 introduces a new object allocation mechanism called "layered compaction," which significantly speeds up object creation. Instead of relying solely on malloc for memory, Ruby now utilizes a multi-layered heap consisting of TLSF (Two-Level Segregated Fit) allocators within larger mmap'd regions. This approach reduces system calls, minimizes fragmentation, and improves cache locality, resulting in performance gains, especially in multi-threaded scenarios. The layered compaction mechanism manages these TLSF heaps, compacting them when necessary to reclaim fragmented memory and ensure efficient object allocation. This improvement translates to faster application performance and reduced memory usage.
The blog post "Fast Allocations in Ruby 3.5" by Aaron Patterson on Rails at Scale details performance improvements related to object allocation in Ruby 3.5, focusing on the introduction of a new allocation system called "malloc_trim." The author begins by establishing the context of Ruby's memory management, explaining that Ruby uses system malloc for memory allocation and that frequent calls to malloc can lead to performance bottlenecks, especially in memory-intensive applications like Rails.
The post then delves into the problems associated with fragmentation in memory management. Fragmentation occurs when free memory becomes divided into small, non-contiguous chunks, making it difficult to allocate larger objects despite having sufficient total free memory. This leads to increased system calls to obtain more memory from the operating system, further hindering performance. The traditional solution to this problem has been calling malloc_trim, a function that releases unused memory back to the operating system. However, indiscriminately calling malloc_trim can also be detrimental, as it introduces overhead.
Patterson describes the new dynamic malloc_trim strategy implemented in Ruby 3.5. Instead of relying on a fixed or periodic approach, Ruby 3.5 intelligently decides when to call malloc_trim based on the amount of free memory available within Ruby's heap. This adaptive approach aims to minimize both fragmentation and the overhead of unnecessary malloc_trim calls. Specifically, the new algorithm calls malloc_trim when the amount of free memory exceeds a certain threshold, dynamically adjusted based on the maximum amount of memory ever allocated. This ensures malloc_trim is invoked only when there's a significant amount of potentially wasted memory.
The blog post then presents benchmark results demonstrating the effectiveness of the new allocation system. These benchmarks involve creating and destroying many small objects, a scenario prone to fragmentation. The results show significant performance improvements in Ruby 3.5 compared to older Ruby versions, particularly under memory-intensive workloads. The benchmarks demonstrate substantial reductions in both the number of calls to malloc and the overall execution time.
Finally, Patterson concludes by highlighting the potential benefits of these improvements for Rails applications and other Ruby programs that perform frequent object allocations. The dynamic malloc_trim strategy in Ruby 3.5 promises to reduce memory usage and improve performance, especially in environments where memory resources are constrained or where allocation patterns lead to significant fragmentation. This ultimately contributes to a more efficient and responsive Ruby runtime.
Summary of Comments ( 61 )
https://news.ycombinator.com/item?id=44062160
Hacker News users generally praised the Ruby 3.5 allocation improvements, with many noting the impressive performance gains demonstrated in the benchmarks. Some commenters pointed out that while the micro-benchmarks are promising, real-world application performance improvements would be the ultimate test. A few questioned the methodology of the benchmarks and suggested alternative scenarios to consider. There was also discussion about the tradeoffs of different memory allocation strategies and their impact on garbage collection. Several commenters expressed excitement about the future of Ruby performance and its potential to compete with other languages. One user highlighted the importance of these optimizations for Rails applications, given Rails' historical reputation for memory consumption.
The Hacker News post titled "Fast Allocations in Ruby 3.5" linking to a Rails at Scale article has generated several comments discussing the performance improvements and their implications.
One commenter expresses excitement about the potential of these improvements to reduce object allocation overhead in Ruby, a common performance bottleneck. They specifically highlight the benefit for workloads involving many small objects.
Another commenter delves deeper into the technical details of the improvements, mentioning the reduced reliance on the garbage collector and the implications for memory fragmentation. They also compare Ruby's approach to memory management with other languages like Java and discuss the tradeoffs.
A further comment thread discusses the historical context of memory management in Ruby and the various optimization efforts made over the years. This includes mentions of previous techniques like object pooling and how the changes in 3.5 build upon or replace those methods.
Some skepticism is expressed regarding the real-world impact of these optimizations. One commenter questions whether the benchmarks presented accurately reflect typical Ruby application workloads, and suggests more comprehensive benchmarking is needed. They propose testing with different object sizes and lifespans to get a more complete picture of the performance gains.
Another commenter raises the point that while allocation speed is improved, garbage collection times might still be a concern. They suggest focusing on reducing overall object creation as a more effective strategy for performance optimization.
The discussion also touches on the trade-offs between raw performance and developer experience. One commenter argues that while these optimizations are beneficial, the complexity of Ruby's memory management might be a barrier for some developers. They suggest focusing on tools and techniques that simplify memory management for the average Ruby developer.
Finally, a few commenters express anticipation for further advancements in Ruby's performance, and speculate on future directions for optimization efforts. They mention potential improvements in areas like concurrency and just-in-time compilation.