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Elastic Cooperative Caching: An Autonomous Dynamically Adaptive Memory Hierarchy for Chip Multiprocessors

机译:弹性协作缓存:芯片多处理器的自主动态自适应内存层级

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Next generation tiled microarchitectures are going to be limited by off-chip misses and by on-chip network usage. Furthermore, these platforms will run an heterogeneous mix of applications with very different memory needs, leading to significant optimization opportunities. Existing adaptive memory hierarchies use either centralized structures that limit the scalability or software based resource allocation that increases programming complexity. We propose Elastic Cooperative Caching, a dynamic and scalable memory hierarchy that adapts automatically and autonomously to application behavior for each node. Our configuration uses elastic shared/private caches with fully autonomous and distributed repartitioning units for better scalability. Furthermore, we have extended our elastic configuration with an Adaptive Spilling mechanism to use the shared cache space only when it can produce a performance improvement. Elastic caches allow both the creation of big local private caches for threads with high reuse of private data and the creation of big shared spaces from unused caches. Local data allocation in private regions allows to reduce network usage and efficient cache partitioning allows to reduce off-chip misses. The proposed scheme outperforms previous proposals by a minimum of 12% (on average across the benchmarks) and reduces the number of offchip misses by 16%. Plus, the dynamic and autonomous management of cache resources avoids the reallocation of cache blocks without reuse which results in an increase in energy efficiency of 24%.
机译:下一代瓷砖微架构将受到片外未命中的限制,并通过片上网络使用。此外,这些平台将运行具有非常不同的内存需求的应用程序的异构组合,导致显着的优化机会。现有的自适应存储器层次结构使用集中式结构,限制基于可伸缩性或基于软件的资源分配,从而提高了编程复杂性。我们提出了弹性协作缓存,动态和可伸缩的内存层次结构,可自动且自主地适应每个节点的应用程序行为。我们的配置使用具有完全自主和分布式重新分区单元的弹性共享/私人缓存,以获得更好的可扩展性。此外,我们已经通过自适应溢出机制扩展了我们的弹性配置,仅在可以产生性能改进时使用共享高速缓存空间。 Elasic Caches允许创建大型本地私人高速缓存的线程,重用私有数据以及未使用缓存的大共享空间的创建。私有区域中的本地数据分配允许降低网络使用率,高效的缓存分区允许减少片外未命中。该方案以前的建议优于至少12%(平均基准),并减少离职失误的数量16%。此外,高速缓存资源的动态和自主管理避免了高速缓存块的重新定位而无需重用,这导致能量效率的增加24%。

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