论文标题

proteus:基于规则的光子NOC自动适应激光和性能的共同管理

PROTEUS: Rule-Based Self-Adaptation in Photonic NoCs for Loss-Aware Co-Management of Laser Power and Performance

论文作者

Vatsavai, Sairam Sri, Karempudi, Venkata Sai Praneeth, Thakkar, Ishan

论文摘要

使用传统电子NOC的最先进的多核处理器中片上通信的性能已经变得严重受到了能源约束。为此,新兴的光子NOC(PNOC)被视为提高芯片交流的能源效率(每瓦的性能)的解决方案。但是,由于其出色的激光功耗,现有的PNOC设计无法实现其全部潜力。试图提高PNOC激光功率效率的先前工作并不考虑影响PNOC激光功率需求的所有关键因素。因此,它们无法在PNOC中的激光功率降低,实现性能和能源效率之间产生所需的平衡。在本文中,我们提出了Proteus框架,该框架采用了基于规则的PNOC中的自我适应。我们的方法不仅降低了激光功耗,而且还通过机会来提高PNOC的通信数据速率,从而最大程度地减少了平均数据包延迟,从而在PNOC中产生了激光功率重新传输,性能和能源效率之间所需的平衡。我们对PARSEC基准的评估表明,与先前的另一种激光电源管理技术相比,我们的Proteus框架的激光功率消耗率最高可减少24.5%,平均数据包潜伏期降低31%,每位能量减少20%。

The performance of on-chip communication in the state-of-the-art multi-core processors that use the traditional electron-ic NoCs has already become severely energy-constrained. To that end, emerging photonic NoCs (PNoC) are seen as a po-tential solution to improve the energy-efficiency (performance per watt) of on-chip communication. However, existing PNoC designs cannot realize their full potential due to their exces-sive laser power consumption. Prior works that attempt to improve laser power efficiency in PNoCs do not consider all key factors that affect the laser power requirement of PNoCs. Therefore, they cannot yield the desired balance between the reduction in laser power, achieved performance and energy-efficiency in PNoCs. In this paper, we present PROTEUS framework that employs rule-based self-adaptation in PNoCs. Our approach not only reduces the laser power consumption, but also minimizes the average packet latency by opportunis-tically increasing the communication data rate in PNoCs, and thus, yields the desired balance between the laser power re-duction, performance, and energy-efficiency in PNoCs. Our evaluation with PARSEC benchmarks shows that our PROTEUS framework can achieve up to 24.5% less laser power consumption, up to 31% less average packet latency, and up to 20% less energy-per-bit, compared to another laser power management technique from prior work.

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