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Design of Last-Level On-Chip Cache Using Spin-Torque Transfer RAM (STT RAM)

机译:使用自旋扭矩传输RAM(STT RAM)设计最后一级的片上缓存

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Because of its high storage density with superior scalability, low integration cost and reasonably high access speed, spin-torque transfer random access memory (STT RAM) appears to have a promising potential to replace SRAM as last-level on-chip cache (e.g., L2 or L3 cache) for microprocessors. Due to unique operational characteristics of its storage device magnetic tunneling junction (MTJ), STT RAM is inherently subject to a write latency versus read latency tradeoff that is determined by the memory cell size. This paper first quantitatively studies how different memory cell sizing may impact the overall computing system performance, and shows that different computing workloads may have conflicting expectations on memory cell sizing. Leveraging MTJ device switching characteristics, we further propose an STT RAM architecture design method that can make STT RAM cache with relatively small memory cell size perform well over a wide spectrum of computing benchmarks. This has been well demonstrated using CACTI-based memory modeling and computing system performance simulations using SimpleScalar. Moreover, we show that this design method can also reduce STT RAM cache energy consumption by up to 30% over a variety of benchmarks.
机译:由于其高存储密度,出色的可扩展性,较低的集成成本和相当高的访问速度,自旋扭矩传输随机存取存储器(STT RAM)似乎有潜力取代SRAM作为最后一级的片上高速缓存(例如, L2或L3缓存)。由于其存储设备磁隧道结(MTJ)的独特操作特性,STT RAM本质上要经受由存储单元大小决定的写延迟与读延迟之间的权衡。本文首先定量研究了不同的存储单元大小可能会如何影响整个计算系统的性能,并显示出不同的计算工作负载可能对存储单元大小有冲突的期望。利用MTJ设备的切换特性,我们进一步提出了一种STT RAM体系结构设计方法,该方法可以使具有相对较小存储单元大小的STT RAM缓存在各种计算基准上表现良好。使用基于CACTI的内存建模和使用SimpleScalar的计算系统性能仿真已充分证明了这一点。此外,我们证明,在各种基准测试中,这种设计方法还可以将STT RAM缓存能耗降低多达30%。

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