并行分段:扩展系统级数据结构

Qi Wang, Tim Stamler, Gabriel Parmer
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引用次数: 16

摘要

随着系统不断增加缓存一致性域中的核心数量,在数据结构上实现并行计算的传统技术越来越紧张。单个争用缓存线在不同缓存之间的弹跳可能会阻止额外核心的持续性能提升。需要新的抽象和机制来重新评估如何提供数据结构一致性,同时保持稳定的每核访问延迟。本文提出了并行段(ParSec)抽象,用于中介对共享数据结构的访问。该方法的基础是一种新的可扩展内存回收形式,它利用快速本地访问实时到全局顺序系统事件。这种方法尝试最小化一致性流量,同时利用共享读取(主要是缓存)行的优势。我们展示了可伸缩内存回收、内存分配、锁定和名称空间管理的共同管理支持可伸缩的系统服务实现。我们将ParSec应用于微内核中的memcached和虚拟内存管理,发现在4个套接字、40个核心的机器上,性能有了数量级的提高,虚拟内存管理的第99百分位延迟降低了30倍。
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Parallel sections: scaling system-level data-structures
As systems continue to increase the number of cores within cache coherency domains, traditional techniques for enabling parallel computation on data-structures are increasingly strained. A single contended cache-line bouncing between different caches can prohibit continued performance gains with additional cores. New abstractions and mechanisms are required to reassess how data-structure consistency can be provided, while maintaining stable per-core access latencies. This paper presents the Parallel Sections (ParSec) abstraction for mediating access to shared data-structures. Fundamental to the approach is a new form of scalable memory reclamation that leverages fast local access to real-time to globally order system events. This approach attempts to minimize coherency-traffic, while harnessing the benefit of shared read-mostly cache-lines. We show that the co-management of scalable memory reclamation, memory allocation, locking, and namespace management enables scalable system service implementation. We apply ParSec to both memcached, and virtual memory management in a microkernel, and find order-of magnitude performance increases on a four socket, 40 core machine, and 30x lower 99th percentile latencies for virtual memory management.
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