[LSF/MM/BPF TOPIC] AutoNUMA enhancements to optimize Tiered Memory

[LSF/MM/BPF TOPIC] AutoNUMA enhancements to optimize Tiered Memory

[Huang, Ying]

Topic: AutoNUMA enhancements to optimize Tiered Memory

Traditionally, all RAM is DRAM.  Some DRAM might be closer/faster than
others, but a byte of media has about the same cost whether it is close
or far.  But, with new memory tiers such as High-Bandwidth Memory or
Persistent Memory, there is a choice between fast/expensive and
slow/cheap.

The existing reclaim mechanisms work wonderfully for moving cold data
out of fast/expensive tiers.  However, reclaim does not work well for
moving hot data which might be stuck in a slow tier since the pages near
the top of the LRU are the most recently accessed only if there’s
regular memory pressure on the slow/cheap tiers.

Fortunately, AutoNUMA *can* find recently-accessed pages regardless of
memory pressure.  We have repurposed it from being used for
location-based optimization to being used for tier-based optimization.
We have also optimized it for better hot data identification, such as to
find frequently-accessed pages instead of recently-accessed pages, etc.
We will show our findings so far, and discuss the remaining problems,
potential solutions, and alternatives.