Open Source Summit India 2026

Modern CPUs rely on spatial locality when fetching fixed-size cache lines, but kernel structures are often laid out without reflecting runtime access patterns. Frequency-based reordering groups hot fields together but misses a key insight: two high-frequency fields accessed at different times can still waste cache capacity through eviction between accesses. We propose access-affinity-based reordering fields accessed close together in time should be placed close together in memory.

We trace field-level accesses on struct rq, compute co-access frequencies within a short time window, and build an access-affinity graph where edge weights reflect temporal co-access. Hierarchical clustering derives reorderings that collocate temporally correlated fields within cache lines. Evaluated on waitstressor, cache misses dropped from 36.2B (13.9%) to 25.1B (9.4%), with idle_cpu() misses falling from 6.40% to 3.11%. Tool automates this analysis across kernel structures. We explore HTM-based tracing and MemFriend for scalable profiling. Key discussion areas: workload selection per structure, 64B vs 128B line layouts, false-sharing avoidance, and extending this methodology beyond struct rq.