Autonomic tool for optimal cache-sharing using evolutionary techniques

Chip multiprocessors are subject to performance degradation due to inefficient cache management. Conventional cache distribution schemes treat all cores equally, leading to cache-contention issues caused by thrashing behaviors. This paper presents an automation tool that ensures optimal cache-sharing amongst cores executing workloads concurrently and competing for cache resources. We demonstrate that dynamic cache partitioning among selected cores improves overall performance. Our automation tool uses CPU performance counters that feed into a genetic algorithm to ensure optimal cache distribution. This scheme minimizes the overall LLC miss rate by 12.879% and increases the overall IPC by 2.426% over the conventional cache partitioning.