Spandex: A Flexible Interface for Efficient Heterogeneous Coherence.

ISCA(2018)

引用 54|浏览105
暂无评分
摘要
Recent heterogeneous architectures have trended toward tighter integration and shared memory largely due to the efficient communication and programmability enabled by this shift. However, such integration is complex, because accelerators have widely disparate methods for accessing and keeping data coherent. Some processors use caches backed by hardware coherence protocols like MESI, while others prefer lightweight software coherence protocols or use specialized memories like scratchpads with differing state and communication granularities. Modern solutions tend to build interfaces that extend existing MESI-style CPU coherence protocols, often by adding hierarchical indirection through intermediate shared caches. Although functionally correct, these strategies lack flexibility and generally suffer from performance limitations that make them sub-optimal for some emerging accelerators and workloads. Instead, we need a flexible interface that can efficiently integrate existing and future devices - without requiring intrusive changes to their memory structure. We introduce Spandex, an improved coherence interface based on the simple and scalable DeNovo coherence protocol. Spandex (which takes its name from the flexible material commonly used in one-size-fits-all textiles) directly interfaces devices with diverse coherence properties and memory demands, enabling each device to communicate in a manner appropriate for its specific access properties. We demonstrate the importance of this flexibility by comparing this strategy against a more conventional MESI-based hierarchical solution for a diverse range of heterogeneous applications. On average for the applications studied, Spandex reduces execution time by 16% (max 29%) and network traffic by 27% (max 58%) relative to the MESI-based hierarchical solution.
更多
查看译文
关键词
coherence,heterogeneous architectures,consistency,memory systems
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要