Leveraging on-chip networks for data cache migration in chip multiprocessors

Noel Eisley, L. Peh, L. Shang
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引用次数: 37

Abstract

Recently, chip multiprocessors (CMPs) have arisen as the de facto design for modern high-performance processors, with increasing core counts. An important property of CMPs is that remote, but on-chip, L2 cache accesses are less costly than off-chip accesses; this is in contrast to earlier chip-to-chip or board-to-board multiprocessors, where an access to a remote node is just as costly if not more so than a main memory access. This motivates on-chip cache migration as a means to retain more data on-chip. However, previously proposed techniques do not scale to high core counts: they do not leverage the on-chip caches of all cores nor have a scalable migration mechanism. In this paper we propose ascalable in-network migration technique which uses hints embedded within the router microarchitecture to steer L2 cache evictions towards free/invalid cache slots in any on-chip core cache, rather than evicting it off-chip. We show that our technique can provide an average of a 19% reduction in the number of off-chip memory accesses over the state-of-the-art, beating the performance of a pseudo-optimal migration technique. This can be done with negligible area overhead and a manageable traffic overhead of 13.4%.
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在芯片多处理器中利用片上网络进行数据缓存迁移
最近,随着核心数量的增加,芯片多处理器(cmp)已经成为现代高性能处理器的实际设计。cmp的一个重要特性是,远程但片上的L2缓存访问比片外访问成本更低;这与早期的芯片对芯片或板对板多处理器形成对比,在这些处理器中,访问远程节点的成本与访问主内存的成本一样高。这促使片上缓存迁移作为在片上保留更多数据的一种手段。然而,以前提出的技术不能扩展到高核数:它们不能利用所有核的片上缓存,也没有可扩展的迁移机制。在本文中,我们提出了可扩展的网络内迁移技术,该技术使用嵌入在路由器微架构中的提示来引导L2缓存驱逐到任何片上核心缓存中的空闲/无效缓存插槽,而不是将其驱逐到片外。我们表明,与最先进的技术相比,我们的技术可以使片外存储器访问的数量平均减少19%,优于伪最佳迁移技术的性能。这可以用微不足道的面积开销和可管理的13.4%的流量开销来完成。
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Meeting points: Using thread criticality to adapt multicore hardware to parallel regions COMIC: A coherent shared memory interface for cell BE Pangaea: A tightly-coupled IA32 heterogeneous chip multiprocessor Multi-mode energy management for multi-tier server clusters MCAMP: Communication optimization on Massively Parallel Machines with hierarchical scratch-pad memory
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