Adaptive Capacity Sharing through Probabilistic Controlled Placement

Abstract

As capacity demands vary among simultaneously executed threads in chip multiprocessors, dynamically managing cache resources according to the run-time demands is effective to improve L2 cache performance. Differed from existing dynamic cache management schemes based on LRU replacement policy, we propose an adaptive capacity sharing mechanism based on a global reuse replacement policy. This mechanism adopts decoupled tag and data arrays, and partitions the data arrays into private and shared regions. Capacity sharing is accomplished by determining whether to place the incoming data into the private data region or into the shared data region, which is controlled by probabilities. Our mechanism includes: (1) A VMON monitor to predict run-time capacity demands. (2) A PCS algorithm to determine the probabilities. (3) A probabilistic controlled placement scheme to enforce capacity sharing. We evaluated our mechanism with a full system simulation of an 8-core CMP and used parallel programs from PARSEC benchmark suite. We found that with the same total L2 cache capacity, our mechanism exceeds the conventional private cache managed by LRU policy, the private cache without sharing managed by reuse replacement policy, and an existing adaptive sharing scheme based on LRU policy.