Presentation
Cache Where It Counts: Towards Workload-Aware I/O Coordination for NUMA Storage Systems
DescriptionModern Non-Uniform Memory Access (NUMA) servers equipped with distributed Non-Volatile Memory Express (NVMe) storage present new challenges for I/O coordination. First, conventional page cache allocators ignore storage topology, resulting in inefficient cross-node cache placement and performance issues. Second, CPU schedulers overlook cache and storage locality, causing frequent cross-node cache accesses and further degrading performance. Third, the OS page cache employs a rigid eviction policy that fails to adapt to diverse application workloads, while even programmable alternatives often require complex manual tuning. To address these challenges, we propose Laelaps, a workload-aware I/O coordination framework for NUMA storage systems. Laelaps introduces three key techniques: (1) storage-topology-aware page cache placement, co-locating cache pages with their backing NVMe devices; (2) storage-topology-aware I/O thread scheduling that aligns thread placement with cache distribution to minimize cross-node accesses; and (3) workload-aware adaptive page caching that automatically selects eviction policies based on observed application access patterns. Evaluation shows that Laelaps achieves 1.41× geometric mean throughput improvement with 3.5% runtime overhead.
Event Type
Research Manuscript
TimeTuesday, July 281:55pm - 2:08pm PDT
LocationMtg Room 203C