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Building Efficient Key-Value Stores via a Lightweight Compaction Tree

Log-Structure Merge tree (LSM-tree) has been one of the mainstream indexes in key-value systems supporting a variety of write-intensive Internet... (more)

Ouroboros Wear Leveling for NVRAM Using Hierarchical Block Migration

Emerging nonvolatile RAM (NVRAM) technologies have a limit on the number of writes that can be made to any cell, similar to the erasure limits in NAND... (more)

Experience from Two Years of Visualizing Flash with SSDPlayer

Data visualization is a thriving field of computer science, with widespread impact on diverse scientific disciplines, from medicine and meteorology to... (more)

SUPA: A Single Unified Read-Write Buffer and Pattern-Change-Aware FTL for the High Performance of Multi-Channel SSD

To design the write buffer and flash translation layer (FTL) for a solid-state drive (SSD), previous studies have tried to increase overall SSD performance by parallel I/O and garbage collection overhead reduction. Recent works have proposed pattern-based managements, which uses the request size and read- or write-intensiveness to apply different... (more)

Optimal Repair Layering for Erasure-Coded Data Centers: From Theory to Practice

Repair performance in hierarchical data centers is often bottlenecked by cross-rack network transfer. Recent theoretical results show that the... (more)

CosaFS: A Cooperative Shingle-Aware File System

In this article, we design and implement a cooperative shingle-aware file system, called CosaFS, on heterogeneous storage devices that mix solid-state drives (SSDs) and shingled magnetic recording (SMR) technology to improve the overall performance of storage systems. The basic idea of CosaFS is to classify objects as hot or cold objects based on a... (more)

TinyLFU: A Highly Efficient Cache Admission Policy

This article proposes to use a frequency-based cache admission policy in order to boost the effectiveness of caches subject to skewed access distributions. Given a newly accessed item and an eviction candidate from the cache, our scheme decides, based on the recent access history, whether it is worth admitting the new item into the cache at the... (more)

Client-Side Journaling for Durable Shared Storage

Hardware consolidation in the datacenter often leads to scalability bottlenecks from heavy utilization of critical resources, such as the storage and... (more)

GCMix: An Efficient Data Protection Scheme against the Paired Page Interference

In multi-level cell (MLC) NAND flash memory, two logical pages are overlapped on a single physical page. Even after a logical page is programmed, the data can be corrupted if the programming of the coexisting logical page is interrupted. This phenomenon is called paired page interference. This article proposes a novel software technique to deal... (more)

NEWS

  • TOS EiC Professor Sam H. Noh of UNIST named as ACM Distinguished Member
    A complete list of 2017 ACM Distinguished Members can be found here.

  • CFP - Special Issue on NVM and Storage (in detail)

  • TOS Editor-in-Chief featured in "People of ACM"
    Sam H. Noh is Editor-in-Chief of ACM Transactions on Storage (TOS) - featured in the periodic series "People of ACM", full article available here
    November 01, 2016
     

  • ACM Transaction on Storage (TOS) welcomes Sam H. Noh as its new Editor-in-Chief for a 3-year term, effective August 1, 2016.
    Sam H. Noh is a professor and Head of the School of the Electrical and Computer Engineering School at UNIST (Ulsan National Institute of Science and Technology) in Ulsan, Korea and a leader in the use of new memory technology such as flash memory and non-volatile memory in storage.
    - August 01, 2016

Forthcoming Articles

Editor-in Chief Letter

OrcFS: Orchestrated File System for Flash Storage

We develop OrcFS, Orchestrated File System for Flash storage. It vertically integrates the log-structured file system and the Flash-based storage device eliminating all the redundancies across the layers. A few modern file systems adopt sophisticated append-only data structures to manage its space in an effort to optimize the behavior with respect to the append-only nature of the Flash medium. While the benefit of adopting append-only data structure seems to be fairly promising, it makes the stack of software layers full of unnecessary redundancies which leaves substantial room for improvement. The redundancies include (i) redundant levels of indirection (address translation) , (ii) duplicate efforts to reclaim the invalid blocks which is called segment cleaning and garbage collection in the file system layer and in the storage device, respectively, and (iii) excessive over-provisioning, i.e. separate over-provisioning areas in each layer. OrcFS eliminates the redundancies via distributing the address translation, segment cleaning (or garbage collection), bad block management, and wear-leveling across the layers. OrcFS reduces the device mapping table requirement to 1/465 against the page mapping and removes 1/4 of the write volume under heavy random write workload. In varmail, OrcFS achieves 56% performance gain against EXT4.

clfB-tree: Cacheline Friendly Persistent B-tree for NVRAM

Emerging byte-addressable non-volatile memory (NVRAM) is expected to replace block device storages as an alternative low latency persistent storage device. If NVRAM is used as a persistent storage device, a cache line instead of a disk page will be the unit of data transfer, consistency, and durability. In this work, we design and develop clfB-tree - a B-tree structure whose tree node fits in a single cache line. We employ existing write combining store buffer and restricted transactional memory (RTM) to provide a failure-atomic cache line write operation. Using the failure-atomic cache line write operations, we atomically update a clfB-tree node via a single cache line flush instruction without major changes in hardware. However, there exist many processors that do not provide SW interface for transactional memory. For those processors, our proposed clfB-tree achieves atomicity and consistency via in-place update, which requires maximum four cache line flushes. We evaluate the performance of clfB-tree on an NVRAM emulation board with ARM Cortex A-9 processor and a workstation that has Intel Xeon E7-4809 v3 processor. Our experimental results show clfB-tree outperforms wB-tree and CDDS B-tree by a large margin in terms of both insertion and search performance

A Low-cost Disk Solution Enabling LSM-tree to Achieve High Performance for Mixed Read/Write Workloads

LSM-tree has been widely used in data management production systems for write-intensive workloads. However, as read and write workloads co-exist under LSM-tree, data accesses can experience long latency and low throughput due to the interferences to buffer caching from the compaction, a major and frequent operation in LSM-tree. After a compaction, the existing data blocks are reorganized and written to other locations on disks. As a result, the related data blocks that have been loaded in the buffer cache are invalidated since their referencing addresses are changed, causing serious performance degradations. In order to re-enable high-speed buffer caching during intensive writes, we propose Log-Structured buffered-Merge tree (simplified as LSbM-tree) by adding a compaction buffer on disks, to minimize the cache invalidations on buffer cache caused by compactions. The compaction buffer efficiently and adaptively maintains the frequently visited data sets. In LSbM, strong locality objects can be effectively kept in the buffer cache with minimum or without harmful invalidations. With the help of a small on-disk compaction buffer, LSbM achieves a high query performance by enabling effective buffer caching, while retaining all the merits of LSM-tree for write-intensive data processing, and providing high bandwidth of disks for range queries.

Characterizing 3D Floating Gate NAND Flash: Observations, Analyses and Implications

Since both NAND flash memory manufacturers and users are turning their attentions from planar architecture towards 3D architecture, it becomes more critical and urgent to have a strong understanding of the characteristics of 3D NAND flash memory. These characteristics, especially those different from planar NAND flash, are the foundations of efficient flash management. In this paper, we characterize a state-of-the-art 3D floating gate NAND flash memory through comprehensive experiments on an FPGA-based 3D NAND flash evaluation platform. Then, we present distinct observations on its performance and reliability, such as operation latencies and various error patterns, and carefully analyze them from physical and circuit-level perspectives. Although 3D NAND flash provides much higher storage densities than planar NAND flash, it faces new performance challenges in garbage collection overhead and program performance variation, and more complicated reliability issues due to e.g., distinct location dependence and value dependence of errors. We also summarize the differences of 3D NAND flash from planar NAND flash and discuss design implications on flash memory management brought by the architecture innovation. We believe that our work will facilitate developing novel 3D NAND flash-oriented designs to achieve better performance and reliability.

Challenges and Solutions for Tracing Storage Systems: A Case Study with Spectrum Scale

IBM Spectrum Scale's parallel file system General Parallel File System (GPFS) has a 20-year development history with over 100 contributing developers. Its ability to support strict POSIX semantics across more than 10K clients leads to a complex design with intricate interactions between the cluster nodes. Tracing has proven to be a vital tool to understand the behavior and the anomalies of such a complex software product. However, the necessary trace information is often buried in hundreds of gigabytes of byproduct trace records. Further, the overhead of tracing can significantly impact running applications and file system performance, limiting the use of tracing in a production system. In this article, we discuss the evolution of the mature and highly scalable GPFS tracing tool and describe the process of designing GPFS' new tracing interface, FlexTrace, which allows developers and users to accurately specify what to trace for the problem they are trying to solve. We evaluate our methodology and prototype, demonstrating that the proposed approach has negligible overhead even under intensive I/O workloads.

A Novel ReRAM-based Processing-in-Memory Architecture for Graph Traversal

Graph algorithms such as graph traversal have been gaining ever-increasing importance in the era of big data. However, graph processing on traditional architectures issues many random and irregular memory accesses, leading to a huge number of data movements and the consumption of very large amounts of energy. To minimize the waste of memory bandwidth, we investigate utilizing processing-in-memory (PIM), combined with non-volatile metal-oxide resistive random access memory (ReRAM), to improve both computation and I/O performance. We propose a new ReRAM-based processing-in-memory architecture called RPBFS, in which graph data can be persistently stored and processed in place. We study the problem of graph traversal, and we design an efficient graph traversal algorithm in RPBFS. Benefiting from low data movement overhead and high bank-level parallel computation, RPBFS shows a significant performance improvement compared with both the CPU-based and the GPU-based BFS implementations. On a suite of real world graphs, our architecture yields a speedup in graph traversal performance of up to 33.8X, and achieves a reduction in energy over conventional systems of up to 142.8X.

HiNFS: A Persistent Memory File System with both Buffering and Direct-Access

Persistent memory provides data persistence at main memory with emerging non-volatile main memories (NVMMs). Recent persistent memory file systems aggressively use direct access, which directly copy data between user buffer and the storage layer, to avoid the double-copy overheads through the OS page cache. However, we observe they all suffer from slow writes due to NVMMs asymmetric read-write performance and much slower performance than DRAM. In this paper, we propose HiNFS, a high performance file system for non-volatile main memory, to combine both buffering and direct access for fine-grained file system operations. HiNFS uses an NVMM-aware Write Buffer to buffer the lazy-persistent file writes in DRAM, while performing direct access to NVMM for eager- persistent file writes. It directly reads file data from both DRAM and NVMM, by ensuring read consistency with a combination of the DRAM Block Index and Cacheline Bitmap to track the latest data between DRAM and NVMM. HiNFS also employs a Buffer Benefit Model to identify the eager-persistent file writes before issuing I/Os. Evaluations show that HiNFS significantly improves throughput by up to 184% and reduces execution time by up to 64% comparing with state-of-the-art persistent memory file systems PMFS and EXT4-DAX.

DudeTX: Durable Decoupled Transaction

Emerging non-volatile memory (NVM) offers non-volatility, byte-addressability and fast access at the same time. It is suggested that programs should access NVM directly through CPU load and store instructions. To guarantee crash consistency, durable transactions become a common choice of applications for accessing persistent memory data. However, existing durable transaction systems employ either undo logging, which requires a fence for every memory write, or redo logging, which requires intercepting all memory reads within transactions. This paper presents DudeTX, a crash-consistent durable transaction system that avoids the drawbacks of both undo and redo logging. DudeTX uses shadow DRAM to decouple the execution of a durable transaction into three fully asynchronous steps. The advantage is that only minimal fences and no memory read instrumentation are required. This design enables an out-of-the-box concurrency control mechanism (transactional memory or fine-grained locks) to be used as an independent component. The evaluation results show that DudeTX adds durability to a software transactional memory system with only 7.4%~24.6% throughput degradation. Compared to the existing systems, DudeTX provides 1.7X to 4.4X higher throughput. Moreover, DudeTX can be implemented with existing hardware transactional memory or lock-based concurrency control, leading to a further 1.7X and 8.2X speedup, respectively.

Workload Characterization for Enterprise Disc Drives

Abstract  The paper presents an analysis of drive workloads from enterprise storage systems. The drive workloads are obtained from field return units from a cross-section of enterprise storage system vendors and thus provides a view of the workload characteristics over a wide spectrum of end-user applications. The workload parameters that have been characterized include transfer lengths, access patterns, locality and throughput. The study shows that reads are the dominant workload accounting for 80% of the accesses to the drive. Writes are dominated by short block random accesses while reads range from random to highly sequential. A trend analysis over the period 2010-2014 shows that the workload has remained fairly constant even as the capacities of the drives shipped has steadily increased. The study shows that the data stored on disk drives is relatively cold  on average less than 4% of the drive capacity is accessed in a given 2 hour interval.

Bidirectional Database Storage and SQL Query Exploiting RRAM-based Process-in-Memory Structure

With the coming of Big Data era, high-energy-efficiency database is demanded for the Internet of things (IoT) application scenarios. The emerging Resistive Random Access Memory (RRAM) has been considered as an energy-efficient replacement of DRAM for next-generation main memory. In this paper, we propose an RRAM-based SQL query unit with process-in-memory (PIM) characteristic. A bidirectional storage structure for a database in RRAM crossbar array is proposed, which avoids redundant data transfer to cache and reduces cache miss rate compared with the storage method in DRAM for in-memory database. The proposed RRAM-based SQL query unit can support a representative subset of SQL queries in memory, and thus further reduce the data transfer cost. The corresponding query optimization method is proposed to fully utilize the PIM characteristics. Simulation results show that the energy efficiency of the proposed RRAM-based SQL query unit is increased by 4 to 6 orders of magnitude compared with the traditional architecture.

SLC-Like Programming Scheme for MLC Flash Memory

Although the Multi-Level-Cell technique is widely adopted by flash-memory vendors to boost the chip density and to lower the cost, it results in serious performance and reliability problems. Different from the past work, a new cell programming method is proposed to not only significantly improve the chip performance but also reduce the potential bit error rate. In particular, a Single-Level-Cell-like programming scheme is proposed to better explore the threshold-voltage relationship to denote different Multi-Level-Cell bit information, which in turn drastically provides a larger window of threshold voltage similar to that found in Single-Level-Cell chips. It could result in less programming iterations and simultaneously a much less reliability problem in programming flash-memory cells. In the experiments, the new programming scheme could accelerate the programming speed up to 742% and even reduce the bit error rate up to 471% for Multi-Level-Cell pages.

UnistorFS: A Union Storage File System Design for Resource Sharing between Memory and Storage on Persistent RAM based Systems

With the advanced technology in persistent random access memory (PRAM), PRAM such as 3D XPoint memory is emerging as a promising candidate for the next-generation medium for both (main) memory and storage. Previous works mainly focus on how to overcome the possible endurance issues of PRAM while both main memory and storage own a partition on the same PRAM device. However, a holistic software-level system design should be proposed to fully exploit the benefit of PRAM. This paper proposes a union storage file system (UnistorFS), which aims to jointly manage the PRAM resource for main memory and storage. It realizes the concept of using the PRAM resource as memory and storage interchangeably, so as to achieve resource sharing while main memory and storage coexist on the same PRAM device with no partition or logical boundary. This approach not only enables PRAM resource sharing but also eliminates unnecessary data movements between main memory and storage since they are already in the same address space and can be accessed directly. A series of experiments was conducted on a modified Linux kernel. The results show that the proposed UnistorFS can eliminate unnecessary memory accesses and outperform other PRAM-based file systems.

An Analysis of Flash Page Reuse with WOM Codes

Coupled with the scaling down of flash technology, the popularity of flash memory motivates the search for methods to increase flash reliability and lifetime. Erasures are the dominant cause of flash cell wear, but reducing them is challenging because flash is a write-once medium---memory cells must be erased prior to writing. An approach that has recently received considerable attention relies on write-once memory (WOM) codes, designed to accommodate additional writes on write-once media. However, the techniques proposed for reusing flash pages with WOM codes are limited in their scope. Many focus on the coding theory alone, while others suggest FTL designs that are application specific, or not applicable due to their complexity, overheads, or specific constraints of MLC flash. This work is the first that addresses all aspects of page reuse within an end-to-end analysis of a general-purpose FTL. We use a hardware evaluation setup to directly measure the short and long-term effects of page reuse on durability and energy consumption, and show that FTL design must take them into account. We provide a detailed analytical model for deriving optimal garbage collection for such FTL designs, and for predicting the benefit from reuse on realistic hardware and workload characteristics.

Persisting RB-Tree into NVM in a Consistency Perspective

The byte-addressable non-volatile memory (NVM) is going to reshape conventional computer systems. With advantages of low latency, byte-addressability and non-volatility, NVM can be directly put on the memory bus to replace DRAM. As a result, both system and application softwares have to be adjusted to perceive the fact that the persistent layer moves up to the memory. However, most of the current in-memory data structures will be problematic with consistency issues if not well tuned with NVM. This paper places emphasizes on an important in-memory structure that is widely used in computer systems, i.e., the Red/Black-tree (RB-tree). Since it has a long and complicated update process, the RB-tree is prone to inconsistency problems with NVM. This paper presents an NVM-compatible consistent RB-tree with a new technique named cascade-versioning. The proposed RB-tree (i) is all-time consistent and scalable, and (ii) needs no recovery procedure after system crashes. Experiment results show that the RB-tree for NVM not only achieves the aim of consistency with insignificant spatial overhead, but also yields comparable performance to an ordinary volatile RB-tree.

Editorial: 14.1

Bibliometrics

Publication Years 2005-2017
Publication Count 244
Citation Count 1673
Available for Download 244
Downloads (6 weeks) 1585
Downloads (12 Months) 14123
Downloads (cumulative) 151791
Average downloads per article 622
Average citations per article 7
First Name Last Name Award
Sarita Adve ACM Fellows (2010)
Emery David Berger ACM Senior Member (2010)
Surendar Chandra ACM Senior Member (2009)
Alok Choudhary ACM Fellows (2009)
Deborah Estrin ACM Athena Lecturer Award (2006)
ACM Fellows (2000)
Jason Flinn ACM Fellows (2016)
Armando Fox ACM Karl V. Karlstrom Outstanding Educator Award (2015)
ACM Distinguished Member (2011)
ACM Senior Member (2009)
Gregory Ganger ACM Distinguished Member (2007)
Garth A Gibson ACM Fellows (2012)
ACM Doctoral Dissertation Award
Series Winner (1991)
Ramesh Govindan ACM Fellows (2011)
Haryadi S Gunawi ACM Doctoral Dissertation Award
Honorable Mention (2009) ACM Doctoral Dissertation Award
Honorable Mention (2009)
Ragib Hasan ACM Senior Member (2015)
John Heidemann ACM Senior Member (2007)
Tei-Wei Kuo ACM Fellows (2015)
Kai Li ACM Fellows (1998)
Ming Li ACM Fellows (2006)
Dahlia Malkhi ACM Fellows (2011)
Ethan L Miller ACM Distinguished Member (2013)
SAM H. NOH ACM Distinguished Member (2017)
Walid Najjar ACM Distinguished Member (2015)
ACM Senior Member (2014)
Michael Reiter ACM Fellows (2008)
Stefan Savage ACM Prize in Computing (2015)
ACM Fellows (2010)
Steven Scott ACM Fellows (2012)
Kenneth C Sevcik ACM Fellows (1997)
Anand Sivasubramaniam ACM Fellows (2017)
ACM Distinguished Member (2010)
ACM Senior Member (2009)
Chandramohan A Thekkath ACM Fellows (2009)
Gene Tsudik ACM Fellows (2014)
ACM Senior Member (2013)
Amin Vahdat ACM Fellows (2011)
Geoffrey M Voelker ACM Fellows (2017)
David Wagner ACM Doctoral Dissertation Award
Honorable Mention (2001) ACM Doctoral Dissertation Award
Honorable Mention (2001)
Randy Wang ACM Eugene L. Lawler Award for Humanitarian Contributions within Computer Science and Informatics (2007)
Marianne Winslett ACM Fellows (2006)
Tao Xie ACM Distinguished Member (2015)
ACM Senior Member (2011)
Philip S Yu ACM Fellows (1997)
Demetris Zeinalipour ACM Senior Member (2016)
Yuanyuan Zhou ACM Fellows (2013)
ACM Distinguished Member (2011)
Roger Zimmermann ACM Distinguished Member (2017)

First Name Last Name Paper Counts
Andrea Arpaci-Dusseau 12
Remzi Arpaci-Dusseau 8
Dan Feng 8
Erez Zadok 7
Youjip Won 6
Teiwei Kuo 6
Ethan Miller 6
Changsheng XIE 5
Bianca Schroeder 5
Hong Jiang 5
Geoff Kuenning 5
Hyokyung Bahn 5
Cheng Chen 4
Raju Rangaswami 4
Remzi Arpaci-Dusseau 4
Stergios Anastasiadis 4
Jiwu Shu 4
Feng Chen 4
Qingsong Wei 4
Charles Wright 4
Randal Burns 4
Ilias Iliadis 4
Heonyoung Yeom 4
Xubin He 4
Narasimha Reddy 4
Weimin Zheng 4
Patrick Lee 4
Xiao Qin 4
Lidong Zhou 3
Hyeonsang Eom 3
Eunji Lee 3
Youngjin Yu 3
Darrell Long 3
Suzhen Wu 3
Lanyue Lu 3
Yuanhao Chang 3
Jenwei Hsieh 3
Song Jiang 3
Fred Douglis 3
James Cipar 3
Vijayan Prabhakaran 3
Guangyan Zhang 3
An Wang 3
Lipin Chang 3
Samhyuk Noh 3
Yuanyuan Zhou 3
Jianxi Chen 3
Peter Desnoyers 3
Binbing Hou 3
Nitin Agrawal 3
Ohad Rodeh 3
Bo Mao 3
Gene Tsudik 2
Anand Sivasubramaniam 2
Xiaoning Ding 2
Yuehai Xu 2
Darrell Long 2
Chris Dragga 2
Sudhanva Gurumurthi 2
Thomas Schwarz 2
Mingdi Xue 2
Ali Tosun 2
Xiaojun Ruan 2
Jongmin Gim 2
Peter Reiher 2
Eitan Bachmat 2
William Jannen 2
Amogh Akshintala 2
Zhenmin Li 2
John MacCormick 2
Grant Wallace 2
Philip Shilane 2
Ramnatthan Alagappan 2
Kyuho Park 2
Jun Yang 2
Andromachi Hatzieleftheriou 2
André Brinkmann 2
Ming Chen 2
Swaminathan Sundararaman 2
Sriram Subramanian 2
Leif Walsh 2
Martín Farach-Colton 2
Prashant Pandey 2
Vinodh Venkatesan 2
Dongin Shin 2
Lei Tian 2
Gregory Ganger 2
Jun Yuan 2
Roger Zimmermann 2
Qing Liu 2
Tao Xie 2
Mahesh Balakrishnan 2
Erik Riedel 2
Ahmed Amer 2
Abutalib Aghayev 2
Michael Bender 2
Taeho Hwang 2
Jaemin Jung 2
Yuchong Hu 2
Jeffrey Chase 2
Fei Wu 2
Ping Huang 2
Eno Thereska 2
Scott Brandt 2
Wei Xue 2
Kiran Muniswamy-Reddy 2
Bradley Kuszmaul 2
Xiaoyu Hu 2
Evangelos Eleftheriou 2
Dan Feng 2
Nikolai Joukov 2
Chinhsien Wu 2
Mansour Shafaei 2
Yang Zhan 2
Mark Storer 2
Kaladhar Voruganti 2
Ashvin Goel 2
Shu Yin 2
Michael Swift 2
Gopalan Sivathanu 2
Alma Riska 2
Mahmut Kandemir 2
Arkady Kanevsky 2
Rob Johnson 2
Donald Porter 2
Thanumalayan Pillai 2
Zhan Shi 2
Daniel Fryer 2
Angela Brown 2
Jayanta Basak 2
Jiguang Wan 2
Mario Blaum 2
Adam Manzanares 2
William Bolosky 2
Bo Hong 2
Sangsoo Park 1
Zachary Peterson 1
Kai Li 1
Samuel Lang 1
Xianghong Luo 1
Mark Shaw 1
Hyungju Cho 1
Taesun Chung 1
Yan Li 1
Mary Baker 1
Abhishek Rajimwale 1
Kai Li 1
Priya Sehgal 1
Joseph Murray 1
Armando Fox 1
Andrew Huang 1
Rahat Mahmood 1
Lawrence Chiu 1
Lianghong Xu 1
Shan Lu 1
Jianwen Zhu 1
Benlong Zhang 1
Jinpeng Huai 1
Ming Wu 1
Matthew Curry 1
Wenguang Chen 1
Mohammed Alghamdi 1
Maithili Narasimha 1
Yang Wang 1
Vincent Freeh 1
Nandan Tammineedi 1
Chris Mason 1
Youyou Lu 1
Long Sun 1
Marianne Winslett 1
James Lentini 1
Guanlin Lu 1
Rick Coulson 1
Kuoyi Huang 1
Tsungtai Yeh 1
Eunki Kim 1
Angelos Bilas 1
Kevin Bowers 1
Ben Eckart 1
Guanying Wu 1
Sajib Kundu 1
Christos Karamanolis 1
Magnus Karlsson 1
Harikesavan Krishnan 1
Haibo Chen 1
Heng Zhang 1
Mingkai Dong 1
Myoungsoo Jung 1
Yihua Zhang 1
Edward Chang 1
Jian Zhou 1
Michael Mesnier 1
Ioan Stefanovici 1
Zardosht Kasheff 1
Ning Li 1
Hakim Weatherspoon 1
Hariharan Gopalakrishnan 1
Nitin Garg 1
Anxiao(Andrew) Jiang 1
Robert Latham 1
Robert Ross 1
John Lui 1
Yuxing Peng 1
Xuechen Zhang 1
Garth Gibson 1
Bruno Quaresma 1
Dushyanth Narayanan 1
Jason Flinn 1
TingHao Cheng 1
Garth Gibson 1
Emery Berger 1
Jacob Lorch 1
Mathew Oldham 1
Alexey Tumanov 1
Jack Sun 1
Ertem Esiner 1
Christopher Meyers 1
Rubao Lee 1
Wei Wang 1
Qingyue Liu 1
Dongjin Kim 1
Weiping He 1
Roy Friedman 1
Alexander Thomasian 1
Ivan Popov 1
Zhiwei Sun 1
Ji Zhang 1
Ying Lin 1
Masaaki Tanaka 1
Tyler Simon 1
Jaemin Ryu 1
Yongdai Kim 1
Gerald Popek 1
Demetrios Zeinalipour-Yazti 1
Song Lin 1
Xiaojian Wu 1
Assaf Natanzon 1
Rachel Traylor 1
Surendar Chandra 1
John Garrison 1
Knut Grimsrud 1
Deborah Estrin 1
Byeonggil Jeon 1
Thanos Makatos 1
Kaushik Dutta 1
Xiaoyun Zhu 1
Jay Dave 1
Tianfeng Jiao 1
Paolo Viotti 1
Shiqin Yan 1
Swaminatahan Sundararaman 1
Andrew Chien 1
Sai Huang 1
Avani Wildani 1
Yongchiang Tay 1
David Essary 1
Seungho Lim 1
Bradley Vander Zanden 1
Minghua Chen 1
Min Fu 1
You Zhou 1
Gang Wang 1
Jingwei Ma 1
Zhifeng Chen 1
Michael Abd-El-Malek 1
Michael Reiter 1
Garth Goodson 1
William Josephson 1
Sotirios Damouras 1
Brian Noble 1
James Megquier 1
Kuei Sun 1
Aydan Yumerefendi 1
Luis Bathen 1
Binny Gill 1
Cristian Ungureanu 1
Hyojun Kim 1
Nitin Gupta 1
João Paulo 1
Kushal Wadhwani 1
Abhinav Sharma 1
Peter Varman 1
P Nagesh 1
Pan Zhou 1
Ben Manes 1
Alberto Miranda 1
Sascha Effert 1
Mohit Saxena 1
Youshan Miao 1
Vana Kalogeraki 1
Rekha Pitchumani 1
Thomas Talpey 1
Ankur Mittal 1
Phaneendra Reddy 1
Stefano Paraboschi 1
Di Ma 1
Deepak Ganesan 1
Ramesh Govindan 1
Haim Helman 1
David Chambliss 1
Yannis Klonatos 1
Alina Oprea 1
Manolis Marazakis 1
Jianqiang Luo 1
Lihao Xu 1
Marcus Jager 1
Ryan Peterson 1
Kenneth Sevcik 1
Feng Wang 1
Yubin Xia 1
Mohammad Zubair 1
Marko Vukolić 1
Ram Kesavan 1
Shuwen Gao 1
David Donofrio 1
KK Rao 1
Anthony Tung 1
Richard Spillane 1
Chihyuan Huang 1
Hong Jiang 1
Yinjin Fu 1
Qin Xin 1
Peter Trifonov 1
James Plank 1
Yusik Kim 1
PingYi Hsu 1
Jingning Liu 1
Muthian Sivathanu 1
Sumeet Sobti 1
Junwen Lai 1
Arvind Krishnamurthy 1
Yinlong Xu 1
Qian Chang 1
Fenghao Zhang 1
Nihat Altiparmak 1
Kushagra Vaid 1
Sejin Kwon 1
Tomer Hertz 1
David Flynn 1
Elie Krevat 1
Mike Qin 1
Kahwai Lee 1
Sarah Diesburg 1
Naeyoung Song 1
Yongseok Son 1
Junyao Li 1
Jihong Kim 1
Kyuho Park 1
Roman Shor 1
Xiaoyang Zhang 1
Jerry Fredin 1
Lingfang Zeng 1
Kenneth Kent 1
Wentao Han 1
Amanpreet Mukker 1
Xunfei Jiang 1
Yupu Zhang 1
Dutch Meyer 1
Sudharshan Vazhkudai 1
Qian Wang 1
Alok Choudhary 1
Mais Nijim 1
Stefan Savage 1
John Esmet 1
Sabrina Vimercati 1
Darren Sawyer 1
Changhyun Park 1
Jaehyuk Cha 1
Ben Greenstein 1
Beomjoo Seo 1
Akshat Verma 1
Taokai Lam 1
Geetika Bangera 1
Huaicheng Li 1
Yuvraj Patel 1
Marina Blanton 1
Jai Menon 1
Rajiv Wickremesinghe 1
Udi Wieder 1
Qi Zhang 1
Kevin Greenan 1
Yankit Li 1
Medha Bhadkamkar 1
Fernando Farfán 1
Adam Buchsbaum 1
Jens Jelitto 1
Yuxiang Ma 1
Sunjin Lee 1
Vesna Pavlović 1
Robert Haas 1
Kristal Pollack 1
Hyeongseog Kim 1
Kanchan Chandnani 1
Linjun Mei 1
Nan Su 1
Yongsoo Joo 1
Jehoshua Bruck 1
Feng Zheng 1
Liping Xiang 1
Matthew Wachs 1
Karan Sanghi 1
Fernando André 1
Paulo Sousa 1
Antony Rowstron 1
Gordon Hughes 1
Daniel Ellard 1
Mark Corner 1
John Douceur 1
Nitin Agrawal 1
Charles Weddle 1
Mingqiang Li 1
Sangeetha Seshadri 1
Mark Stanovich 1
José Pereira 1
Xiaolan Chen 1
Hyuck Han 1
Marshall McKusick 1
Peng Xu 1
Ye Zhai 1
Junbin Kang 1
Mohammad Hajkazemi 1
Aleatha Parker-Wood 1
Gala Yadgar 1
Xiaolu Li 1
Mi Zhang 1
Gil Einziger 1
Leo Arulraj 1
Einar Mykletun 1
Weikeng Liao 1
Josef Bacik 1
Deepak Bobbarjung 1
Walid Najjar 1
Lars Nagel 1
Radu Sion 1
Mark Chamness 1
Ao Ma 1
Seokhei Cho 1
Sooyong Kang 1
John Heidemann 1
Pieter Hartel 1
Xiaodong Li 1
Lingfang Zeng 1
Chandramohan Thekkath 1
Kirsten Hildrum 1
Philip YU 1
Seonho Kim 1
Ron Arnan 1
Zhaoguo Wang 1
Haibing Guan 1
Binyu Zang 1
Henry Nelson 1
Carl Waldspurger 1
Haryadi Gunawi 1
Venugopalan Ramasubramanian 1
Jin Li 1
Jingui Wang 1
Junjie Ren 1
Veljko Milutinović 1
Kanchi Gopinath 1
Tudor Marian 1
Zhen Huang 1
Xiao Qin 1
Nguyen Tran 1
Frank Chiang 1
Yulai Xie 1
David Wagner 1
Dilma Silva 1
Lakshmi Bairavasundaram 1
Kimberly Keeton 1
Phillipa Gill 1
Kaushik Veeraraghavan 1
Ricardo Koller 1
Haifeng Yu 1
Windsor Hsu 1
Hyojun Kim 1
Robert Hall 1
Adilet Kachkeev 1
Samuel Braunfeld 1
Alptekin Küpçü 1
Öznur Özkasap 1
James Plank 1
Tao Xie 1
Tianyu Wo 1
Ting Yao 1
David Du 1
Sanghoon Kim 1
Kaiwei Li 1
Asim Kadav 1
Xiaosong Ma 1
Stephen Scott 1
Hyungkyu Chang 1
Sukwoo Kang 1
Sheng Qiu 1
Christina Strong 1
Soyoon Lee 1
Krishna Kant 1
Sanjeev Trika 1
Debra Hensgen 1
Tsansheng Hsu 1
Weikuan Shih 1
Picheng Hsiu 1
Pochun Huang 1
Rohit Jain 1
Joel Wolf 1
Dan Dobre 1
Vijay Chidambaram 1
Michaelhao Tong 1
Phung Huynh 1
Junfeng Yang 1
Jaewoo Choi 1
Aichun Pang 1
Hyunjin Choi 1
Ningfang Mi 1
Vagelis Hristidis 1
Cheng Huang 1
Gaewon You 1
Xiaoguang Liu 1
Chundong Wang 1
Jaka Sodnik 1
Jasna Milovanovic 1
Sara Stancin 1
Chuan Qin 1
Jiyong Shin 1
Kevin Harms 1
William Allcock 1
Yubiao Pan 1
Ernst Biersack 1
Jianzhong Huang 1
Jiwu Shu 1
Jinyang Li 1
Weihang Jiang 1
Changxun Wu 1
Vasily Tarasov 1
Edmund Nightingale 1
Amin Vahdat 1
Mark Huang 1
Clement Dickey 1
Jibin Wang 1
Sungjin Lee 1
Chunming Hu 1
Chanhyun Youn 1
Jinsoo Kim 1
Jinhyuk Lee 1
Zehao Zhang 1
Yang Wang 1
Lee Ward 1
Fan Yang 1
Weishinn Ku 1
Dahlia Malkhi 1
Jianhong Lin 1
Jonathan Strickland 1
Junseok Shim 1
Gokhan Memik 1
Cezary Dubnicki 1
Kei Davis 1
Stephanie Jones 1
David Holland 1
Michael Vrable 1
Geoffrey Voelker 1
Douglas Santry 1
Ragib Hasan 1
Alexandros Batsakis 1
Gerardo Pelosi 1
Sungroh Yoon 1
Avishay Traeger 1
Tsengyi Chen 1
Ian Adams 1
Chunghsien Wu 1
Geming Chiu 1
Kristof Roomp 1
Lisa Fleischer 1
Hong Zhu 1
Ruben Michel 1
Dean Hildebrand 1
Wonil Choi 1
Aishwarya Ganesan 1
Ajay Dholakia 1
Zoran Dimitrijević 1
Klaus Schauser 1
Nick Murphy 1
Dongin Shin 1
Evgenia Smirni 1
Chunho Ng 1
Zhonghong Ou 1
Rebecca Stones 1
Yungfeng Lu 1
Sašo Tomažič 1
Randolph Wang 1
Charles Bacon 1
Philip Carns 1
Runhui Li 1
Sriram Sankar 1
Keqin Li 1
Alysson Bessani 1
Miguel Correia 1
Dan Tsafrir 1
Chongfeng Hu 1
Austin Donnelly 1
Lars Bongo 1
Shaun Benjamin 1
Jin Qian 1
Michael Kozuch 1
Hong Jiang 1
Ao Ma 1
Yue Yang 1
Sangwhan Moon 1
Dongkun Shin 1
Youngjin Kim 1
Yuchong Hu 1
Alireza Haghdoost 1
Yao Sun 1
Yangwook Kang 1
Tom Friedetzky 1
Toni Cortes 1
Anthony Skjellum 1
Enhong Chen 1
Zhichao Li 1
Sugata Ghosal 1
Rakesh Iyer 1
Satoshi Sugahara 1
Jian Zhang 1
Suresh Jagannathan 1
Dimitrios Gunopulos 1
Matthias Grawinkel 1
Yizheng Jiao 1
Sara Foresti 1
Pierangela Samarati 1
Windsor Hsu 1
Jeanna Matthews 1
Jongmoo Choi 1
Hsinwen Wei 1
Hyungjong Shin 1
Mohammed Khatib 1
Sarita Adve 1
Michail Flouris 1
Chengkang Hsieh 1
Akshay Katta 1
Michael Stumm 1
David Quigley 1
Puja Gupta 1
Cheng Li 1
Farhaan Jalia 1
Mingzhe Hao 1
John Shalf 1
Rohit Singh 1
Travis Grusecki 1
Ellis Wilson 1
Dinh Tran 1
Ming Li 1
Jon Elerath 1
Jiri Schindler 1
Lei Tian 1
Gyudong Shim 1
Youngwoo Park 1
Qiang Cao 1
Min Xu 1
Seungwon Hwang 1
Navendu Jain 1
Ren Wang 1
Slavisa Sarafijanovic 1
Julie Kim 1
Andrej Kos 1
Lawrence You 1
Greg O'Shea 1
Pooja Deo 1
Shigui Qi 1
Jingwei Li 1

Affiliation Paper Counts
Dankook University 1
Chungbuk National University 1
University of Bergamo 1
University of Electronic Science and Technology of China 1
Dongduk Women's University 1
Los Alamos National Laboratory 1
Kookmin University 1
Universitat Politecnica de Catalunya 1
Harvard University 1
The University of British Columbia 1
Apple Computer 1
Dartmouth College 1
Qualcomm Incorporated 1
University of Texas at Austin 1
Earlham College 1
Indian Institute of Science, Bangalore 1
AT&T Inc. 1
Sun Microsystems 1
Imperial College London 1
University of Southern California, Information Sciences Institute 1
University of Denver 1
University of Washington, Seattle 1
The University of Tennessee System 1
Yonsei University 1
Beijing University of Posts and Telecommunications 1
University of New Brunswick 1
Peter the Great St. Petersburg Polytechnic University 1
Tamkang University 1
University of Durham 1
New Jersey Institute of Technology 1
Politecnico di Milano 1
Dickinson College, Pittsburgh 1
University of California, Berkeley 1
IBM Haifa Labs 1
Virginia Tech 1
Complutense University of Madrid 1
Oracle Corporation 1
Inha University, Incheon 1
University of California, Santa Barbara 1
University of Northern Iowa 1
Salk Institute for Biological Studies 1
University of Cyprus 1
Amazon.com, Inc. 1
Symantec Corporation 1
Barcelona Supercomputing Center 1
Shenzhen Institute of Advanced Technology 1
Ulsan National Institute of Science and Technology 1
VMware, Inc 1
Al Baha University 1
IBM, Netherlands 1
National Taichung University of Science and Technology 1
Facebook, Inc. 1
NetApp, Germany 1
University of Texas at Arlington 2
Rice University 2
Lawrence Berkeley National Laboratory 2
Cornell University 2
Sandia National Laboratories, New Mexico 2
Santa Clara University 2
National Taipei University of Technology 2
Stanford University 2
University of Pittsburgh 2
The College of William and Mary 2
Hongik University 2
National Tsing Hua University 2
University of Minho 2
University of Twente 2
IBM, USA 2
University of Notre Dame 2
University of Virginia 2
Massachusetts Institute of Technology 2
University of Tokyo 2
University of Alabama at Birmingham 2
Ben-Gurion University of the Negev 2
New Mexico Institute of Mining and Technology 2
Rutgers, The State University of New Jersey 2
California Institute of Technology 2
Pohang University of Science and Technology 2
University of Belgrade 2
Harvard School of Engineering and Applied Sciences 2
NetApp, India 2
Virginia Commonwealth University 3
University of Texas at San Antonio 3
IBM India Research Laboratory 3
Ohio State University 3
Yale University 3
University of Minnesota System 3
Google Inc. 3
Northwestern University 3
Sungkyunkwan University 3
Duke University 3
Purdue University 3
National Chiao Tung University Taiwan 3
University of Tennessee, Knoxville 3
National University of Singapore 3
Technion - Israel Institute of Technology 3
Oak Ridge National Laboratory 3
National University of Defense Technology China 3
University Michigan Ann Arbor 3
University of Milan 3
Microsoft Research Asia 3
Harvey Mudd College 4
Ewha Women's University 4
Ajou University 4
Samsung Electronics Co. Ltd. 4
North Carolina State University 4
Seagate Research 4
HP Labs 4
University of Massachusetts Amherst 4
Academia Sinica Taiwan 4
San Diego State University 4
New York University 4
The University of North Carolina at Chapel Hill 4
University of Southern California 4
University of California, Riverside 4
University of Ljubljana 4
Koc University 5
NEC Laboratories America, Inc. 5
Foundation for Research and Technology-Hellas 5
University of California, Los Angeles 5
National Taiwan University of Science and Technology 5
Temple University 5
Johannes Gutenberg University Mainz 5
Microsoft Research Cambridge 5
Universidade de Lisboa 5
University of Ioannina 6
Johns Hopkins University 6
University of California, Irvine 6
Louisiana State University 6
Beihang University 6
Xiamen University 6
Microsoft Corporation 6
University of Chicago 6
University of California, San Diego 6
Korea Advanced Institute of Science & Technology 6
Pennsylvania State University 7
Nankai University 7
University of Science and Technology of China 7
Shanghai Jiaotong University 7
Argonne National Laboratory 7
Northeastern University 7
EMC Corporation 7
Florida State University 8
Wayne State University 8
University of Nebraska - Lincoln 8
Princeton University 9
Intel Corporation 9
IBM Almaden Research Center 9
IBM Thomas J. Watson Research Center 10
Florida International University 10
Texas A and M University 10
NetApp, USA 11
University of Illinois at Urbana-Champaign 12
Auburn University 12
National Taiwan University 13
Chinese University of Hong Kong 13
Date Storage Institute, A-Star, Singapore 13
IBM Zurich Research Laboratory 14
Wuhan National Laboratory for Optoelectronics 16
Carnegie Mellon University 17
Hanyang University 17
Seoul National University 21
Microsoft Research 22
University of Toronto 22
Tsinghua University 23
University of California, Santa Cruz 25
Huazhong University of Science and Technology 36
Stony Brook University 43
University of Wisconsin Madison 51

ACM Transactions on Storage (TOS) - Special Issue on MSST 2017 and Regular Papers
Archive


2017
Volume 13 Issue 4, December 2017 Special Issue on MSST 2017 and Regular Papers
Volume 13 Issue 3, October 2017 Special Issue on FAST 2017 and Regular Papers
Volume 13 Issue 2, June 2017 Special Issue on MSST 2016 and Regular Papers
Volume 13 Issue 1, March 2017 Special Issue on USENIX FAST 2016 and Regular Papers

2016
Volume 12 Issue 4, August 2016
Volume 12 Issue 3, June 2016
Volume 12 Issue 2, February 2016
Volume 12 Issue 1, February 2016 Special Issue on Massive Storage Systems and Technologies (MSST 2015)

2015
Volume 11 Issue 4, November 2015 Special Issue USENIX FAST 2015
Volume 11 Issue 3, July 2015
Volume 11 Issue 2, March 2015
Volume 11 Issue 1, February 2015

2014
Volume 10 Issue 4, October 2014 Special Issue on Usenix Fast 2014
Volume 10 Issue 3, July 2014
Volume 10 Issue 2, March 2014
Volume 10 Issue 1, January 2014

2013
Volume 9 Issue 4, November 2013
Volume 9 Issue 3, August 2013
Volume 9 Issue 2, July 2013
Volume 9 Issue 1, March 2013

2012
Volume 8 Issue 4, November 2012
Volume 8 Issue 3, September 2012
Volume 8 Issue 2, May 2012
Volume 8 Issue 1, February 2012
Volume 7 Issue 4, January 2012

2011
Volume 7 Issue 3, October 2011
Volume 7 Issue 2, July 2011
Volume 7 Issue 1, June 2011
Volume 6 Issue 4, May 2011

2010
Volume 6 Issue 3, September 2010
Volume 6 Issue 2, July 2010
Volume 6 Issue 1, March 2010

2009
Volume 5 Issue 4, December 2009
Volume 5 Issue 3, November 2009
Volume 5 Issue 2, June 2009
Volume 5 Issue 1, March 2009
Volume 4 Issue 4, January 2009

2008
Volume 4 Issue 3, November 2008
Volume 4 Issue 2, May 2008
Volume 4 Issue 1, May 2008
Volume 3 Issue 4, February 2008

2007
Volume 3 Issue 3, October 2007
Volume 3 Issue 2, June 2007
Volume 3 Issue 1, March 2007

2006
Volume 2 Issue 4, November 2006
Volume 2 Issue 3, August 2006
Volume 2 Issue 2, May 2006
Volume 2 Issue 1, February 2006

2005
Volume 1 Issue 4, November 2005
Volume 1 Issue 3, August 2005
Volume 1 Issue 2, May 2005
Volume 1 Issue 1, February 2005
 
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