Doctoral Thesis: Implementing accelerated key-value store: From SSDs to datacenter servers
32-G882
Chanwoo Chung
Abstract:
Efficient management of storage is a primary concern in all systems dealing with Big Data. In the modern era, flash-based solid-state drives (SSDs) are widely adopted in computer systems, slowly replacing hard disk drives. As many kinds of data generated and collected these days are not well-structured, a key-value store has become one of the most important building blocks widely used in datacenters thanks to its simple interface. Key-value stores are often used as an internal engine for other databases. This talk explores whether a modern flash-based solid-state drive (SSD) augmented with near-storage computations can be re-designed to provide a cheaper and power-efficient solution to maintaining various key-value services in the cloud. The talk introduces a new type of storage device, called a key-value SSD (KV-SSD), that exposes a key-value interface instead of the legacy block interface to the host machine. The two alternative solutions that can replace existing KVS components are based on KV-SSDs, LightStore and PinK. LightStore is a new storage architecture based on a group of network-attached KV-SSDs without storage host servers. LightStore aims to primarily support large-sized objects and emulates other types of data stores using application-side adapters. Compared to existing storage server-based solutions, LightStore is up to 2.3X space- and 7.4X energy efficient. PinK is a novel design of an LSM-tree for KV-SSDs with software and hardware techniques that provides bounded tail latency and design flexibility. The PinK prototype improves the read and 99th percentile latency by 22% and read throughput by 44% compared to LightStore. The PinK prototype showed 42-73% better latency and 37% better throughput compared to commercial hash-based prototype. Another alternative solution, smartLSM, based on smart SSDs, a block-based SSD with an accelerator, shows how the smart SSDs can help existing software KVS on hosts. We believe these alternatives to running various types of key-value stores in datacenters would reduce storage management cost drastically.
Details
- Date: Thursday, November 17
- Time: 10:00 am - 11:30 am
- Category: Thesis Defense
- Location: 32-G882
Additional Location Details:
Thesis Supervisor: Prof. Arvind
To attend via zoom, please contact the doctoral candidate at cwchung@mit.edu