1 research outputs found
To Update or Not To Update?: Bandwidth-Efficient Intelligent Replacement Policies for DRAM Caches
This paper investigates intelligent replacement policies for improving the
hit-rate of gigascale DRAM caches. Cache replacement policies are commonly used
to improve the hit-rate of on-chip caches. The most effective replacement
policies often require the cache to track per-line reuse state to inform their
decision. A fundamental challenge on DRAM caches, however, is that stateful
policies would require significant bandwidth to maintain per-line DRAM cache
state. As such, DRAM cache replacement policies have primarily been stateless
policies, such as always-install or probabilistic bypass. Unfortunately, we
find that stateless policies are often too coarse-grain and become ineffective
at the size and associativity of DRAM caches. Ideally, we want a replacement
policy that can obtain the hit-rate benefits of stateful replacement policies,
but keep the bandwidth-efficiency of stateless policies.
In our study, we find that tracking per-line reuse state can enable an
effective replacement policy that can mitigate common thrashing patterns seen
in gigascale caches. We propose a stateful replacement/bypass policy called
RRIP Age-On-Bypass (RRIP-AOB), that tracks reuse state for high-reuse lines,
protects such lines by bypassing other lines, and Ages the state On cache
Bypass. Unfortunately, such a stateful technique requires significant bandwidth
to update state. To this end, we propose Efficient Tracking of Reuse (ETR). ETR
makes state tracking efficient by accurately tracking the state of only one
line from a region, and using the state of that line to guide the replacement
decisions for other lines in that region. ETR reduces the bandwidth for
tracking replacement state by 70%, and makes stateful policies practical for
DRAM caches. Our evaluations with a 2GB DRAM cache, show that our RRIP-AOB and
ETR techniques provide 18% speedup while needing less than 1KB of SRAM