arXiv:2605.26168v1 Announce Type: cross Abstract: Linux is the foundation of the digital age, accounting for the majority of the cloud and mobile OS markets. Any device that runs Linux uses the Linux page cache, a central pillar in OS and application performance, serving to reduce extraneous disk access. Many page cache eviction policies have been developed but remain bound by the rigidity of heuristics. The rise of AI-driven tools in recent years, melded with the ever-increasing variety of workloads for Linux devices, sets the stage for machine-learning-driven cache eviction policies. Promisi
The increasing complexity and variety of workloads for Linux devices, coupled with advancements in AI, make machine-learning-driven cache eviction policies both necessary and feasible.
Improving the fundamental performance of the Linux page cache, which underpins the majority of cloud and mobile OS markets, has widespread implications for computing efficiency and resource utilization.
Traditional heuristic-based cache eviction policies in Linux systems can now be augmented or replaced by adaptive, AI-driven approaches, potentially leading to more efficient resource management.
- · Cloud providers
- · Linux-based OS developers
- · AI/ML developers applying models to system-level problems
- · Users of Linux-powered devices
- · Developers of rigid, heuristic-based caching algorithms
System performance and energy efficiency for Linux-based infrastructure improves across the board.
This methodology could extend to other OS-level resource management challenges, fostering a broader trend of AI-optimized operating systems.
Increased compute efficiency could indirectly reduce infrastructure costs for large-scale operations, impacting the overall economics of digital services.
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Read at arXiv cs.LG