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Achieving Predictable Performance with On-Chip Shared L2 Caches for Manycore-Based Real-Time Systems

机译:利用基于许多核的实时系统的片上共享L2缓存实现可预测的性能

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Doubling the number of processing cores on a single processor chip with each technology generation has become conventional wisdom. While future manycore processors promise to offer much increased computational throughput under a given power envelope, sharing critical on-chip resources, such as caches and coreto- core interconnects, poses challenges to guaranteeing predictable performance to an application program. This paper focuses on the problem of sharing on-chip caching capacity among multiple programs scheduled together, especially at the L2 cache level. Specifically, two design aspects of a large shared L2 cache are considered: (1) non-uniform cache access latency and (2) cache contention. We observe that both the aspects have to do with where, among many cache slices, a cache block is mapped to, and present an OS-based approach to managing the on-chip L2 cache memory by carefully mapping data to a cache at the page granularity. We show that a reasonable extension to the OS memory management subsystem and simple architectural support enable enforcing high-level policies to achieve application performance isolation and improve program performance predictability thereof.
机译:每种技术生成的单个处理器芯片上的处理核心数加倍,已成为传统智慧。虽然未来的多核处理器承诺在给定的电源信封下提供大量增加的计算吞吐量,但分享关键的片上资源,例如缓存和压制核心互连,构成了保证对应用程序可预测性能的挑战。本文重点介绍在调度的多个程序之间共享片上缓存容量的问题,特别是在L2缓存级别。具体地,考虑了大型共享L2高速缓存的两个设计方面:(1)非统一高速缓存访​​问等待时间和(2)缓存争用。我们观察到,在许多高速缓存切片中,两个方面都必须与之映射到许多高速缓存切片的位置,并映射到基于OS的方法,并通过将数据仔细映射到页面上的缓存来管理片上L2高速缓冲存储器的方法粒度。我们展示了OS内存管理子系统的合理扩展和简单的架构支持,使能实现高级策略以实现应用性能隔离并提高其程序性能可预测性。

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