Abstract
The storage device based on Nonvolatile Memory (NVM devices) has high read/write speed and embedded processor. It is a useful way to improve the efficiency of Key-Value (KV) application. However it still has some limitations such as limited capacity, poorer computing power compared with CPU, and complex I/O system software. Thus it is not an effective way to construct KV storage system with NVM devices directly. We analyze the characteristics of NVM devices and demands of KV application to design the matrix KV storage system based on NVM Devices. The group collaboration management based on Bloomfilter, intragroup optimization based on competition, embedded KV management based on B+-tree, and the new interface of KV storage system are presented. Then, the embedded processor in the NVM device and CPU can be comprehensively utilized to construct a matrix KV pair management system. It can improve the storage and management efficiency of massive KV pairs, and it can also support the efficient execution of KV applications. A prototype is implemented named MKVS (the matrix KV storage system based on NVM devices) to test with YCSB (Yahoo! Cloud System Benchmark) and to compare with the current in-memory KV store. The results show that MKVS can improve the throughput by 5.98 times, and reduce the 99.7% read latency and 77.2% write latency.
Highlights
The disk and flash-based solid-state device (SSD) cannot provide high random I/O performance
The current I/O system software stack was designed for low-speed storage devices, which becomes an important factor affecting the performance of the NVM storage system
We modified the structure of the current KV store and I/O system software stack to design a new matrix KV storage system based on NVM Devices named MKVS
Summary
The disk and flash-based solid-state device (SSD) cannot provide high random I/O performance. The NVM device has the embedded processor and it can share some management task for storage system or application. Compared with CPU, the embedded processor of NVM device has limited computing power, and it is difficult to index and management of a large number of KV pairs independently. The CPU completes the KV pair distribution task with high computational overhead, and the embedded processor separately indexes part of the KV pair stored in the NVM device. Thereby it can improve the efficiency of mass KV storage and management, and improve the efficiency of the KV applications. Several system calls are added to encapsulate the KV management operations of matrix KV storage system; this can ensure the compatibility of existing applications and avoid numerous modifications to current KV applications
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