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Reed-Solomon (RS) codes have been increasingly adopted by distributed storage systems in place of replication,because they provide the same level of availability with much lower storage overhead. However, a key drawback of those RS-coded…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-21 Tian Xie , Juntao Fang , Shenggang wan , Changsheng Xie , Xubin He

A large-scale content-centric mobile ad hoc network employing subpacketization is studied in which each mobile node having finite-size cache moves according to the reshuffling mobility model and requests a content object from the library…

Information Theory · Computer Science 2018-04-23 Adeel Malik , Sung Hoon Lim , Won-Yong Shin

Iterative methods are commonly used approaches to solve large, sparse linear systems, which are fundamental operations for many modern scientific simulations. When the large-scale iterative methods are running with a large number of ranks…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-05-30 Dingwen Tao , Sheng Di , Xin Liang , Zizhong Chen , Franck Cappello

RAID proposal advocated replacing large disks with arrays of PC disks, but as the capacity of small disks increased 100-fold in 1990s the production of large disks was discontinued. Storage dependability is increased via replication or…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-09 Alexander Thomasian

Previous research addressed the potential problems of the hard-disk oriented design of DBMSs of flashSSDs. In this paper, we focus on exploiting potential benefits of flashSSDs. First, we examine the internal parallelism issues of flashSSDs…

Databases · Computer Science 2012-01-04 Hongchan Roh , Sanghyun Park , Sungho Kim , Mincheol Shin , Sang-Won Lee

Depth-adaptive neural networks can dynamically adjust depths according to the hardness of input words, and thus improve efficiency. The main challenge is how to measure such hardness and decide the required depths (i.e., layers) to conduct.…

Computation and Language · Computer Science 2020-12-17 Yijin Liu , Fandong Meng , Jie Zhou , Yufeng Chen , Jinan Xu

In cross-device Federated Learning (FL), clients with low computational power train a common\linebreak[4] machine model by exchanging parameters via updates instead of potentially private data. Federated Dropout (FD) is a technique that…

Machine Learning · Computer Science 2022-09-16 Giacomo Verardo , Daniel Barreira , Marco Chiesa , Dejan Kostic , Gerald Q. Maguire

In the current landscape of big data, the reliability and performance of storage systems are essential to the success of various applications and services. as data volumes continue to grow exponentially, the complexity and scale of the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-02-06 Joshua Ludolf , Yesmin Reyna-Hernandez , Matthew Trevino

Recent literature including our past work provide analysis and solutions for using (i) erasure coding, (ii) parallelism, or (iii) variable slicing/chunking (i.e., dividing an object of a specific size into a variable number of smaller…

Networking and Internet Architecture · Computer Science 2014-03-21 Guanfeng Liang , Ulas C. Kozat

Large-scale systems with arrays of solid state disks (SSDs) have become increasingly common in many computing segments. To make such systems resilient, we can adopt erasure coding such as Reed-Solomon (RS) code as an alternative to…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-09-20 Sungjoon Koh , Jie Zhang , Miryeong Kwon , Jungyeon Yoon , David Donofrio , Namsung Kim , Myoungsoo Jung

This paper studies the costs and trade-offs of providing transactional consistent reads in a distributed storage system. We identify the following dimensions: read consistency, read delay (latency), and data freshness. We show that there is…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-10-04 Alejandro Z. Tomsic , Manuel Bravo , Marc Shapiro

As capacity and complexity of on-chip cache memory hierarchy increases, the service cost to the critical loads from Last Level Cache (LLC), which are frequently repeated, has become a major concern. The processor may stall for a…

Hardware Architecture · Computer Science 2016-08-09 Navid Khoshavi , Xunchao Chen , Jun Wang , Ronald F. DeMara

Sub-sequence splitting (SSS) has been demonstrated as an effective approach to mitigate data sparsity in sequential recommendation (SR) by splitting a raw user interaction sequence into multiple sub-sequences. Previous studies have…

Information Retrieval · Computer Science 2026-04-08 Yizhou Dang , Yifan Wu , Minhan Huang , Chuang Zhao , Lianbo Ma , Guibing Guo , Xingwei Wang , Zhu Sun

Data compression is widely adopted for modern solid-state drives (SSDs) to mitigate both storage capacity and SSD lifetime issues. Researchers have proposed compression schemes at different system layers, including device-side solutions…

Performance · Computer Science 2025-09-09 Dingcui Yu , Yunpeng Song , Yiyang Huang , Yumiao Zhao , Yina Lv , Chundong Wang , Youtao Zhang , Liang Shi

With low latency, high throughput and enterprise-grade reliability, SSDs have become the de-facto choice for storage in the data center. As a result, SSDs are used in all online data stores in LinkedIn. These apps persist and serve critical…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-26 Nikhil Khatri , Shirshendu Chakrabarti

Millions of sensors, mobile applications and machines now generate billions of events. Specialized many-core key-value stores (KVSs) can ingest and index these events at high rates (over 100 Mops/s on one machine) if events are generated on…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-04-29 Chinmay Kulkarni , Badrish Chandramouli , Ryan Stutsman

Recently, 3D SSDs are widely adopted in PCs, data centers, and cloud storage systems. To increase capacity, high bit-density cells, such as Triple-Level Cell (TLC), are utilized within 3D SSDs. However, due to the inferior performance of…

Hardware Architecture · Computer Science 2024-10-15 Xufeng Yang , Zhengjian Cong , Congming Gao

Vector searches on large-scale datasets are critical to modern online services like web search and RAG, which necessity storing the datasets and their index on the secondary storage like SSD. In this paper, we are the first to characterize…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-08 Rongxin Cheng , Yifan Peng , Xingda Wei , Hongrui Xie , Rong Chen , Sijie Shen , Haibo Chen

It has been experimentally observed that distributed implementations of mini-batch stochastic gradient descent (SGD) algorithms exhibit speedup saturation and decaying generalization ability beyond a particular batch-size. In this work, we…

Machine Learning · Computer Science 2018-01-09 Dong Yin , Ashwin Pananjady , Max Lam , Dimitris Papailiopoulos , Kannan Ramchandran , Peter Bartlett

Today, flash memory are strongly used in the embedded system domain. NAND flash memories are the building block of main secondary storage systems. Such memories present many benefits in terms of data density, I/O performance, shock…

Operating Systems · Computer Science 2012-09-03 Pierre Olivier , Jalil Boukhobza , Eric Senn