Power-reduction techniques for data-center storage systems

T Bostoen, S Mullender, Y Berbers - ACM Computing Surveys (CSUR), 2013 - dl.acm.org
As data-intensive, network-based applications proliferate, the power consumed by the data-
center storage subsystem surges. This survey summarizes, organizes, and integrates a …

Expectation grammars: Leveraging high-level expectations for activity recognition

D Minnen, I Essa, T Starner - 2003 IEEE Computer Society …, 2003 - ieeexplore.ieee.org
Video-based recognition and prediction of a temporally extended activity can benefit from a
detailed description of high-level expectations about the activity. Stochastic grammars allow …

An Evaluation of Different Page Allocation Strategies on High-Speed SSDs.

M Jung, MT Kandemir - HotStorage, 2012 - usenix.org
Exploiting internal parallelism over hundreds NAND flash memory is becoming a key design
issue in high-speed Solid State Disks (SSDs). In this work, we simulated a cycle-accurate …

VSSIM: Virtual machine based SSD simulator

J Yoo, Y Won, J Hwang, S Kang, J Choi… - 2013 IEEE 29th …, 2013 - ieeexplore.ieee.org
In this paper, we present a virtual machine based SSD Simulator, VSSIM (Virtual SSD
Simulator). VSSIM intends to address the issues of the trace driven simulation, eg trace re …

Optimizing the block I/O subsystem for fast storage devices

YJ Yu, DI Shin, W Shin, NY Song, JW Choi… - ACM Transactions on …, 2014 - dl.acm.org
Fast storage devices are an emerging solution to satisfy data-intensive applications. They
provide high transaction rates for DBMS, low response times for Web servers, instant on …

Confzns: A novel emulator for exploring design space of zns ssds

I Song, M Oh, BSJ Kim, S Yoo, J Lee… - Proceedings of the 16th …, 2023 - dl.acm.org
The ZNS (Zoned NameSpace) interface shifts much of the storage maintenance
responsibility to the host from the underlying SSDs (Solid-State Drives). In addition, it opens …

[BOK][B] Flash Memory Integration: Performance and Energy Issues

J Boukhobza, P Olivier - 2017 - books.google.com
4 zettabytes (4 billion terabytes) of data generated in 2013, 44 zettabytes predicted for 2020
and 185 zettabytes for 2025. These figures are staggering and perfectly illustrate this new …

Near-data processing for differentiable machine learning models

H Choe, S Lee, H Nam, S Park, S Kim… - arxiv preprint arxiv …, 2016 - arxiv.org
Near-data processing (NDP) refers to augmenting memory or storage with processing
power. Despite its potential for acceleration computing and reducing power requirements …

Amnesic cache management for non-volatile memory

D Kang, S Baek, J Choi, D Lee… - 2015 31st Symposium …, 2015 - ieeexplore.ieee.org
One characteristic of non-volatile memory (NVM) is that, even though it supports non-
volatility, its retention capability is limited. To handle this issue, previous studies have …

Power, Energy, and Thermal Considerations in {SSD-Based}{I/O} Acceleration

J Zhang, M Shihab, M Jung - 6th USENIX Workshop on Hot Topics in …, 2014 - usenix.org
Solid State Disks (SSDs) have risen to prominence as an I/O accelerator with low power
consumption and high energy efficiency. In this paper, we question some common …