Abstract
The role of the operating system (OS) in managing shared resources such as CPU time, memory, peripherals, and even energy is well motivated and understood [22]. Unfortu- nately, one key resource|lower-level shared cache in chip multi-processors|is commonly managed purely in hardware by rudimentary replacement policies such as least-recently- used (LRU). The rigid nature of the hardware cache manage- ment policy poses a serious problem since there is no single best cache management policy across all sharing scenarios. For example, the cache management policy for a scenario where applications from a single organization are running under \best effort" performance expectation is likely to be different from the policy for a scenario where applications from competing business entities (say, at a third party data center) are running under a minimum service level expecta- tion. When it comes to managing shared caches, there is an inherent tension between exibility and performance. On one hand, managing the shared cache in the OS offers immense policy exibility since it may be implemented in soft- ware. Unfortunately, it is prohibitively expensive in terms of performance for the OS to be involved in managing tempo- rally fine-grain events such as cache allocation. On the other hand, sophisticated hardware-only cache management tech- niques to achieve fair sharing or throughput maximization have been proposed. But they offer no policy exibility. This paper addresses this problem by designing architec- tural support for OS to effciently manage shared caches with a wide variety of policies. Our scheme consists of a hard- ware cache quota management mechanism, an OS interface and a set of OS level quota orchestration policies. The hard- ware mechanism guarantees that OS-specifed quotas are en- forced in shared caches, thus eliminating the need for (and the performance penalty of) temporally fine-grained OS in- tervention. The OS retains policy exibility since it can tune the quotas during regularly scheduled OS interventions. We demonstrate that our scheme can support a wide range of policies including policies that provide (a) passive per- formance differentiation, (b) reactive fairness by miss-rate equalization and (c) reactive performance differentiation.
Date of this Version
July 2006