论文标题
间歇性动力系统的基于STT-RAM的混合L1缓存的有效放置和迁移策略
Efficient Placement and Migration Policies for an STT-RAM based Hybrid L1 Cache for Intermittently Powered Systems
论文作者
论文摘要
由于在各个字段中广泛使用具有IOT的节点的广泛使用,因此电池供电的设备的数量正在迅速增加。有助于嵌入式设备的能源收割机是更换电池供电设备的可行替代方法。在电容器中,能量收割机存储足够的能量来为嵌入式设备供电并计算任务。这种类型的计算称为间歇性计算。能源收割机无法为嵌入式设备提供连续的功率。常规处理器中的所有寄存器和缓存都是波动的。我们需要基于非易失性存储器(NVM)的非挥发处理器(NVP),该处理器(NVP)可以在功率故障期间存储寄存器和缓存内容。 基于NVM的缓存比基于SRAM的缓存降低了系统性能并消耗更多的能量。本文提出了用于使用SRAM和STT-RAM在第一层高速缓存的混合缓存架构的有效放置和迁移策略。提出的架构包括缓存块的放置和迁移策略,以减少写入stt-ram的数量。在功率故障期间,备份策略将关键块从SRAM识别并迁移到SRAM到STT-RAM。与基线体系结构相比,拟议的体系结构将STT-RAM从63.35%降低到35.93%,导致绩效增长32.85%,能源消耗降低了23.42%。与基线相比,我们的备份策略将备份时间减少了34.46%。
The number of battery-powered devices is rapidly increasing due to the widespread use of IoT-enabled nodes in various fields. Energy harvesters, which help to power embedded devices, are a feasible alternative to replacing battery-powered devices. In a capacitor, the energy harvester stores enough energy to power up the embedded device and compute the task. This type of computation is referred to as intermittent computing. Energy harvesters are unable to supply continuous power to embedded devices. All registers and cache in conventional processors are volatile. We require a Non-Volatile Memory (NVM)-based Non-Volatile Processor (NVP) that can store registers and cache contents during a power failure. NVM-based caches reduce system performance and consume more energy than SRAM-based caches. This paper proposes Efficient Placement and Migration policies for hybrid cache architecture that uses SRAM and STT-RAM at the first level cache. The proposed architecture includes cache block placement and migration policies to reduce the number of writes to STT-RAM. During a power failure, the backup strategy identifies and migrates the critical blocks from SRAM to STT-RAM. When compared to the baseline architecture, the proposed architecture reduces STT-RAM writes from 63.35% to 35.93%, resulting in a 32.85% performance gain and a 23.42% reduction in energy consumption. Our backup strategy reduces backup time by 34.46% when compared to the baseline.