Thermosiphon: A thermal aware NUCA architecture for write energy reduction of the STT-MRAM based LLCs

Bi Wu, Yuanqing Cheng, Pengcheng Dai, Jianlei Yang, Youguang Zhang, Dijun Liu, Y. Wang, Weisheng Zhao
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引用次数: 2

Abstract

As the speed gap of the modern processor and the off-chip main memory enlarges, on-chip cache capacity increases to sustain the performance scaling. As a result, the cache power occupies a large portion of the total power budget. STT-MRAM (Spin Transfer Torque Magnetic Memory) is proposed as a promising solution for the low power cache design due to its high integration density and ultra-low leakage. Nevertheless, the high write power and latency of STT-MRAM become new barriers for the commercialization of this emerging technology. In this paper, we investigate the thermal effect on the access performance of STT-MRAM and observe that the temperature can affect the write delay and energy significantly. Then, we explore the NUCA (Non-Uniform Cache Access) design of the CMPs (Chip-Multi-Processors)with STT-MRAM based LLC (Last Level Cache). A thermal aware data migration policy, called “Thermosiphon”, which takes advantage of the thermal property of STT-MRAM, is proposed to reduce the LLC write energy. This policy splits the LLC into different regions based on the thermal distribution and adaptively migrate write intensive data considering the temperature gradient among different thermal regions. Compared to the conventional NUCA design, our proposed design can save 22.5% write energy with negligible hardware overhead.
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热虹吸:用于减少STT-MRAM有限责任公司写入能量的热感知NUCA架构
随着现代处理器和片外主存储器的速度差距的扩大,片上缓存容量增加以维持性能扩展。因此,缓存功率占用了总功率预算的很大一部分。STT-MRAM (Spin Transfer Torque Magnetic Memory,自旋传递转矩磁记忆体)由于其高集成度和超低泄漏,被认为是低功耗高速缓存设计的一个很有前途的解决方案。然而,STT-MRAM的高写入功率和延迟成为这一新兴技术商业化的新障碍。本文研究了热效应对STT-MRAM存取性能的影响,发现温度会显著影响写入延迟和能量。然后,我们探讨了基于STT-MRAM的LLC(最后一级缓存)的cmp (Chip-Multi-Processors)的NUCA (Non-Uniform Cache Access)设计。利用STT-MRAM的热特性,提出了一种热感知数据迁移策略,称为“热虹吸”,以降低LLC写入能量。该策略根据热分布将LLC划分为不同的区域,并考虑不同热区域之间的温度梯度自适应迁移写密集型数据。与传统的NUCA设计相比,我们提出的设计可以节省22.5%的写入能量,而硬件开销可以忽略不计。
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