Getting a Handle on Unmanaged Memory

TL;DR

This paper introduces ALASKA, a compiler and runtime system that enables unmanaged languages to use heap object movement via handles, effectively reducing fragmentation and memory usage without requiring code modifications.

Contribution

ALASKA provides a novel handle-based approach with compiler and runtime support to enable heap compaction in unmanaged languages, bridging the gap with managed language memory management.

Findings

ALASKA reduces memory fragmentation and usage by up to 40% in Redis.

Handles enable seamless heap object movement in unmanaged languages.

ALASKA incurs manageable overheads on large benchmarks.

Abstract

The inability to relocate objects in unmanaged languages brings with it a menagerie of problems. Perhaps the most impactful is memory fragmentation, which has long plagued applications such as databases and web servers. These issues either fester or require Herculean programmer effort to address on a per-application basis because, in general, heap objects cannot be moved in unmanaged languages. In contrast, managed languages like C# cleanly address fragmentation through the use of compacting garbage collection techniques built upon heap object movement. In this work, we bridge this gap between unmanaged and managed languages through the use of handles, a level of indirection allowing heap object movement. Handles open the door to seamlessly employ runtime features from managed languages in existing, unmodified code written in unmanaged languages. We describe a new compiler and runtime system, ALASKA, that acts as a drop-in replacement for malloc. Without any programmer effort, the ALASKA compiler transforms pointer-based code to utilize handles, with optimizations to reduce performance impact. A codesigned runtime system manages this level of indirection and exploits heap object movement via an extensible service interface. We investigate the overheads of ALASKA on large benchmarks and applications spanning multiple domains. To show the power and extensibility of handles, we use ALASKA to eliminate fragmentation on the heap through compaction, reducing memory usage by up to 40% in Redis.