@inproceedings{9dd9af51643746f08987a47ad6415bfc,
title = "A joint management middleware to improve training performance of deep recommendation systems with SSDs",
abstract = "As the sizes and variety of training data scale over time, data preprocessing is becoming an important performance bottleneck for training deep recommendation systems. This challenge becomes more serious when training data is stored in Solid-State Drives (SSDs). Due to the access behavior gap between recommendation systems and SSDs, unused training data may be read and filtered out during preprocessing. This work advocates a joint management middleware to avoid reading unused data by bridging the access behavior gap. The evaluation results show that our middleware can effectively improve the performance of the data preprocessing phase so as to boost training performance.",
keywords = "data arranger, data preprocessing, deep recommendation systems, hardware/software co-design, log-structured merge (LSM), solid-state drives (SSDs), training performance",
author = "Wu, {Chun Feng} and Wu, {Carole Jean} and Wei, {Gu Yeon} and David Brooks",
note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 59th ACM/IEEE Design Automation Conference, DAC 2022 ; Conference date: 10-07-2022 Through 14-07-2022",
year = "2022",
month = jul,
day = "10",
doi = "10.1145/3489517.3530426",
language = "English",
series = "Proceedings - Design Automation Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "157--162",
booktitle = "Proceedings of the 59th ACM/IEEE Design Automation Conference, DAC 2022",
address = "United States",
}