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    基于持久化内存的索引设计重新思考与优化

    Rethinking Index Design Based on Persistent Memory Device

    • 摘要: 非易失性内存(non-volatile memory, NVM)是近几年来出现的一种新型存储介质.一方面,同传统的易失性内存一样,它有着低访问延迟、可字节寻址的特性;另一方面,与易失性内存不同的是,掉电后它存储的数据不会丢失,此外它还有着更高的密度以及更低的能耗开销.这些特性使得非易失性内存有望被大规模应用在未来的计算机系统中.非易失性内存的出现为构建高效的持久化索引提供了新的思路.由于非易失性硬件还处于研究阶段,因此大多数面向非易失性内存的索引研究工作基于模拟环境开展.在2019年4月英特尔发布了基于3D-XPoint技术的非易失性内存硬件apache pass (AEP),这使得研究人员可以基于真实的硬件环境去进行相关研究工作.首先评测了真实的非易失性内存器件,结果显示AEP的写延迟接近DRAM,而读延迟是DRAM的3~4倍.基于对硬件的实际评测结果,研究发现过去很多工作对非易失性内存的性能假设存在偏差,这使得过去的一些工作大多只针对写性能进行优化,并没有针对读性能进行优化.因此,重新审视了之前研究工作,针对过去的混合索引工作进行了读优化.此外,还提出了一种基于混合内存的异步缓存方法.实验结果表明,经过异步缓存方法优化后的混合索引读性能是优化前的1.8倍,此外,经过异步缓存优化后的持久化索引最多可以降低50%的读延迟.

       

      Abstract: NVM (non-volatile memory) is a new type of storage medium that has emerged in recent years. On the one hand, similar to DRAM (Dynamic RAM), NVM has low access latency and byte-addressable characteristics; on the other hand, it does not lose data after a power failure. Moreover, it has higher density and lower power consumption. The emergence of NVM provides new opportunities for improving indexing efficiency, and thus many works focus on building NVM-based indexing. However, these works are conducted based on simulated NVM devices. In April 2019, Intel released real NVM hardware AEP (apache pass) based on 3D-XPoint technology. The actual AEP devices are evaluated, and the results show that the write latency of AEP is close to that of DRAM, while the read latency is 3~4 times that of DRAM. Based on actual NVM hardware performance, we find that many past works have biased performance assumptions about NVM, which leaves some past works open to optimizing space. We then revisit previous persistent indexing works. We propose a read-optimized hybrid index (HybridIndex\++) and a hybrid-memory-based asynchronous caching approach for persistent index. Experimental results show that the read performance of HybridIndex\++ is 1.8 times that of existing hybrid index. The asynchronous cache-optimized indexes can reduce latency by up to 50%.

       

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