Nexus: A New Approach to Replication in Distributed Shared Caches

Abstract

Last-level caches are increasingly distributed, consisting of many small banks. To perform well, most accesses must be served by banks near requesting cores. An attractive approach is to replicate read-only data so that a copy is available nearby. But replication introduces a delicate tradeoff between capacity and latency: too little replication forces cores to access faraway banks, while too much replication wastes cache space and causes excessive off-chip misses. Workloads vary widely in their desired amount of replication, demanding an adaptive approach. Prior adaptive replication techniques only replicate data in each tile's local bank, so they focus on selecting which data to replicate. Unfortunately, data that is not replicated still incurs a full network traversal, limiting the performance of these techniques.We argue that a better strategy is to let cores share replicas and that adaptive schemes should focus on selecting how much to replicate (i.e., how many replicas to have across the chip). This idea fully exploits the latency-capacity tradeoff, achieving qualitatively higher performance than prior adaptive replication techniques. It can be applied to many prior cache organizations, and we demonstrate it on two: Nexus-R extends R-NUCA, and Nexus-J extends Jigsaw. We evaluate Nexus on HPC and server workloads running on a 144-core chip, where it outperforms prior adaptive replication schemes and improves performance by up to 90% and by 23% on average across all workloads sensitive to replication.