@inproceedings{b7480dceccb2423c90e6603803df8e8a,
title = "RHIK: Re-configurable Hash-based Indexing for KVSSD",
abstract = "Key-Value Solid State Drive (KV-SSD), a key addressable SSD technology, promises to simplify storage management for unstructured data and improve system performance with minimal host-side intervention. However, we find that the current state-of-the-art KV-SSD exhibits indexing peculiarities that limit their widespread adoption. Through experiments, we observe that the performance degrades as more data are stored, and the KV-SSD can only store a limited number of key-value pairs even though the amount of data stored on the device is significantly lower than its capacity. We introduce RHIK, a reconfigurable hash-bashed indexing for KV-SSD, for high performance and high occupancy. We implement our proposed indexing scheme on the open-source KV-SSD emulator that is validated against a real KV-SSD, and demonstrate its effectiveness using real workload traces and synthetic microbenchmarks.",
keywords = "KV indexing, data storage, key-value SSD",
author = "Saha, {Manoj P.} and Kim, {Bryan S.} and Gunawi, {Haryadi S.} and Janki Bhimani",
note = "Publisher Copyright: {\textcopyright} 2023 Owner/Author.; 32nd International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2023 ; Conference date: 16-06-2023 Through 23-06-2023",
year = "2023",
month = aug,
day = "7",
doi = "10.1145/3588195.3595945",
language = "English (US)",
series = "HPDC 2023 - Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing",
publisher = "Association for Computing Machinery, Inc",
pages = "319--320",
booktitle = "HPDC 2023 - Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing",
}