An In-Depth Study Of Next Generation Interface For Emerging Non-Volatile Memories

2016 5TH NON-VOLATILE MEMORY SYSTEMS AND APPLICATIONS SYMPOSIUM (NVMSA)(2016)

引用 25|浏览24
暂无评分
摘要
Non-Volatile Memory Express (NVMe) is designed with the goal of unlocking the potential of low-latency, random-access, memory-based storage devices. Specifically, NVMe employs various rich communication and queuing mechanism that can ideally schedule four billion I/O instructions for a single storage device. To explore NVMe with assorted user scenarios, we model diverse interface-level design parameters such as PCI Express, NVMe protocol, and different rich queuing mechanisms by considering a wide spectrum of host-level system configurations. In this work, we also assemble a comprehensive memory stack with different types of emerging NVM technologies, which can give us detailed NVMe related statistics like I/O request lifespans and I/O thread-related parallelism.Our evaluation results reveal that, i) while NVMe handshaking is light-weight for flash memory that uses block-based accesses (Block NVM), it can impose tremendous overheads for memristor technology (DRAM-like NVM), ii) in contrast to the common expectation, the performance of an NVMe-equipped system may not improve in a scalable fashion as the queue depth and the number of queues increase, and iii) more- and deeper-queue systems atop a Block NVM can significantly suffer from tremendous host-side memory requirements, whereas a DRAM-like NVM can cause frequent system stalls due to NVMe's inefficient interrupt service routine.
更多
查看译文
关键词
nonvolatile memory express,low-latency random-access memory-based storage devices,queuing mechanism,I/O instructions,interface-level design parameters,PCI Express,NVMe protocol,host-level system configurations,memory stack,NVM technologies,I/O request lifespans,I/O thread-related parallelism,NVMe handshaking,flash memory,block-based accesses,Block NVM,memristor technology,DRAM-like NVM,NVMe-equipped system,queue depth,interrupt service routine
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要