基于分布式合作cache的私有cache划分方法

当片上多处理器系统上运行多个不同程序时,如何给这些不同的应用程序分配适当的cache空间成为一个难题。Cache划分就是解决这一难题的有效方法,目前大部分的划分方法都是针对最后一级共享cache设计的。私有cache划分(private cache partitioning,PCP)方法采用一个分布式一致性引擎(DCE)把多个私有cache组织在一起,最后通过硬件信息提取单元获得多个程序在不同cache路上的命中分布情况,用于指导划分算法的执行,最后由每个DCE根据划分算法运行的结果对cache空间进行划分。实验结果表明PCP方法降低了失效率,提高了程序执行性能。

Private cache partitioning based on distributed cooperative cache in chip-multiprocessors

When there are several application running on chip-multiprocessors(CMPs), it is a problem to allocate the on-chip cache capacities between these competing applications. Cache partitioning is commonly used to solve this problem. Existing cache partitioning schemes either dedicate to the shared design or partition the last level cache depending on limited memory information. This paper presented private cache partitioning, a low-overhead, runtime mechanism that partitioned all of the private low level caches which were organized as a large shared cache by a distributed directory. The experiment results show that PCP reduces the overall missrate of competing applications and improves the throughput as well as the weighted speedup.