Memory Matters: Load-Time Deduplication for Unikernels
Year: 2025
Type: conference-paper
Abstract: Unikernels offer strong isolation and performance benefits over traditional virtual machines, but their specialized, statically linked design complicates memory deduplication—particularly in multi-tenant environments. Traditional approaches like Kernel Samepage Merging (KSM) struggle with convergence delays, high CPU usage, and unpredictable memory savings. Dynamic linking improves memory reuse but compromises performance, simplicity, and security. We present Spacer-SLT, a novel load time deduplication mechanism that eliminates the need for memory scanners. Spacer-SLT extracts common libraries into a shared pool and uses a custom Firecracker-based loader to enable instant, deterministic memory deduplication at launch time. Unlike KSM, it introduces no runtime overhead and maintains the benefits of static linking, including performance and reduced attack surface.
Institution: University of Liège
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7123527419