EMD: Fair and Efficient Dynamic Memory De-bloating of Transparent Huge Pages

Abstract

Recent processors rely on huge pages to reduce the cost of virtual-to-physical address translation. However, huge pages are notorious for creating memory bloat – a phenomenon wherein the OS ends up allocating more physical memory to an application than its actual requirement. This extra memory can be reclaimed by the OS via de-bloating at runtime. However, we find that current OS-level solutions either lack support for dynamic memory de-bloating, or suffer from performance and fairness pathologies while de-bloating. We address these issues with EMD (Efficient Memory De-bloating). The key insight in EMD is that different regions in an application’s address space exhibit different amounts of memory bloat. Consequently, the tradeoff between memory efficiency and performance varies significantly within a given application e.g., we find that memory bloat is typically concentrated in specific regions, and de-bloating them leads to minimal performance impact. Hinged on this insight, EMD employs a prioritization scheme for fine-grained, efficient, and fair reclamation of memory bloat. EMD improves performance by up to 69% compared to HawkEye — a state-of-the-art OS-based huge page management system. EMD also eliminates fairness concerns associated with dynamic memory de-bloating.