Reconsidering "Reconsidering Custom Memory Allocation"

2026-05-16

AI Summary

This study reevaluates the performance benefits of region-based memory allocators in the context of modern hardware and general-purpose memory allocators. Building upon Berger et al.’s seminal work from nearly 25 years ago, we present the first benchmarking effort incorporating large-scale real-world applications such as Clang and Blender. We introduce a novel methodology to quantitatively assess the impact of memory fragmentation on spatial and temporal locality. Combining state-of-the-art allocator implementations, performance profiling tools, and detailed memory access pattern analysis, our experiments demonstrate that region-based allocation continues to significantly enhance memory locality and reduce fragmentation on contemporary systems, thereby improving execution efficiency. These findings not only corroborate but also extend the original conclusions of prior research.

Abstract

Programmers using native languages such as C, C++, or Rust can implement custom memory allocation strategies to improve execution time. In their paper titled "Reconsidering Custom Memory Allocation" almost 25 years ago, Berger et al. showed that while per-class allocators provide no significant speedups over a state-of-the-art general-purpose allocator, region-based allocators can improve execution time by allocating and freeing objects in bulk. This paper revisits that work on a modern hardware platform with modern general-purpose allocators to evaluate whether their conclusions still hold. It also augments the benchmark suite with two large real-world applications (Clang and Blender), and introduces a methodology to explore the effect of memory fragmentation on locality in general-purpose allocators. Our results support and extend the original conclusions, demonstrating the locality advantages of region-based custom memory allocators.

Problem

• custom memory allocation
• region-based allocators
• memory fragmentation
• locality
• general-purpose allocators

Innovation

• custom memory allocation
• region-based allocator
• memory fragmentation
• locality
• benchmarking