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SynFull: Synthetic Traffic Models Capturing Cache Coherent Behaviour

机译:SynFull:捕获缓存一致性行为的综合流量模型

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摘要

Modern and future many-core systems represent complex architectures. The communication fabrics of these large systems heavily influence their performance and power consumption. Current simulation methodologies for evaluating networks-on-chip (NoCs) are not keeping pace with the increased complexity of our systems; architects often want to explore many different design knobs quickly. Methodologies that capture workload trends with faster simulation times are highly beneficial at early stages of architectural exploration. We propose SynFull, a synthetic traffic generation methodology that captures both application and cache coherence behaviour to rapidly evaluate NoCs. SynFull allows designers to quickly indulge in detailed performance simulations without the cost of long-running full-system simulation. By capturing a full range of application and coherence behaviour, architects can avoid the over or underdesign of the network as may occur when using traditional synthetic traffic patterns such as uniform random. SynFull has errors as low as 0.3% and provides 50× speedup on average overfull-system simulation.
机译:现代和未来的多核系统代表着复杂的体系结构。这些大型系统的通信结构会严重影响其性能和功耗。当前用于评估片上网络(NoC)的仿真方法无法跟上我们系统不断增加的复杂性;建筑师经常希望快速探索许多不同的设计旋钮。在架构探索的早期阶段,以更快的模拟时间捕获工作负载趋势的方法非常有用。我们提出SynFull,这是一种综合的流量生成方法,可捕获应用程序和缓存一致性行为,以快速评估NoC。 SynFull使设计人员可以快速沉迷于详细的性能仿真,而无需花费长时间运行的完整系统仿真。通过捕获全方位的应用程序和一致性行为,架构师可以避免使用传统的综合流量模式(例如统一随机)时可能发生的网络过度设计或设计不足。 SynFull的误差可低至0.3%,平均整个系统仿真速度可提高50倍。

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  • 来源
    《Computer architecture news》 |2014年第3期|109-120|共12页
  • 作者单位

    Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto;

    Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto;

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  • 正文语种 eng
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