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HWP: Hardware Support to Reconcile Cache Energy, Complexity, Performance and WCET Estimates in Multicore Real-Time Systems

机译:HWP:硬件支持,可协调多核实时系统中的缓存能量,复杂性,性能和WCET估计

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High-performance processors have deployed multilevel cache (MLC) systems for decades. In the embedded real-time market, the use of MLC is also on the rise, with processors for future systems in space, railway, avionics and automotive already featuring two or more cache levels. One of the most critical elements for MLC is the write policy that not only affects several key metrics such as performance, WCET estimates, energy/power, and reliability, but also the design of complexity-prone cache coherence protocol and cache reliability solutions. In this paper we make an extensive analysis of existing write policies, namely write-through (WT) and write-back (WB). In the context of the real-time domain, we show that no write policy is superior for all metrics: WT simplifies the design of the coherence and reliability solutions at the cost of performance, WCET, and energy; while WB improves performance and energy results, but complicates cache design. To take the best of each policy, we propose Hybrid Write Policy (HWP) a low-complexity hardware mechanism that reconciles the benefits of WT in terms of simplifying the cache design (e.g. coherence solution) and the benefits of WB in improved average performance and WCET estimates as the pressure on the interconnection network increases. Guaranteed performance results show that HWP scales with core count similar to WB. Likewise, HWP reduces cache energy usage of WT, to levels similar to those of WB. These benefits are obtained while retaining the reduced coherence complexity of WT, in contrast to high coherence costs under WB.
机译:高性能处理器已部署多层缓存(MLC)系统已有数十年了。在嵌入式实时市场中,MLC的使用也在增加,用于太空,铁路,航空电子和汽车未来系统的处理器已经具有两个或两个以上的缓存级别。对于MLC来说,最关键的要素之一是写策略,它不仅会影响性能,WCET估计,能量/功率和可靠性等几个关键指标,而且还会影响易复杂性的缓存一致性协议和缓存可靠性解决方案的设计。在本文中,我们对现有的写策略(即直写(WT)和回写(WB))进行了广泛的分析。在实时域的情况下,我们证明没有写策略对所有指标都具有优越性:WT以性能,WCET和能源为代价简化了一致性和可靠性解决方案的设计; WB可以提高性能和能耗结果,但会使缓存设计复杂化。为了充分利用每种策略,我们提出了一种混合写策略(HWP),它是一种低复杂度的硬件机制,在简化缓存设计(例如,一致性解决方案)以及WB在改善平均性能和增强性能方面的优势方面,兼顾了WT的优势。 WCET估计随着互连网络压力的增加。保证的性能结果表明,HWP的扩展核心数量与WB相似。同样,HWP将WT的缓存能量使用降低到与WB相似的水平。与WB下高相干成本相比,在保持WT降低的相干复杂性的同时获得了这些好处。

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