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4th usenix conference on file and storage technologies

作者： Joukov, N Wong, T Zadok, E SUNY Stony Brook Stony Brook NY 11794 USA

ISBN: (纸本)1931971390

Replaying traces is a time-honored method for benchmarking, stress-testing, and debugging systems-and more recently-forensic analysis. One benefit to replaying traces is the reproducibility of the exact set of operations that were captured during a specific workload. Existing trace capture and replay systems operate at different levels: network packets, disk device drivers, network file systems, or system calls. System call replayers miss memory-mapped operations and cannot replay I/O-intensive workloads at original speeds. Traces captured at other levels miss vital information that is available only at the file system level. We designed and implemented Replayfs, the first system for replaying file system traces at the VFS level. the VFS is the most appropriate level for replaying file system traces because all operations are reproduced in a manner that is most relevant to file-system developers. thanks to the uniform VFS API, traces can be replayed transparently onto any existing file system, even a different one than the one originally traced, without modifying existing file systems. Replayfs's user-level compiler prepares a trace to be replayed efficiently in the kernel where multiple kernel threads prefetch and schedule the replay of file system operations precisely and efficiently. these techniques allow us to replay YO-intensive traces at different speeds, and even accelerate them on the same hardware that the trace was captured on originally.

关键词： Program debugging

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Knockoff: Cheap versions in the cloud 15

Knockoff: Cheap versions in the cloud

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15th usenix conference on file and storage technologies (FAST)

作者： Dou, Xianzheng Chen, Peter M. Flinn, Jason Univ Michigan Ann Arbor MI 48109 USA

ISBN: (纸本)9781931971362

Cloud-based storage provides reliability and ease-of-management. Unfortunately, it can also incur significant costs for both storing and communicating data, even after using techniques such as chunk-based deduplication and delta compression. the current trend of providing access to past versions of data exacerbates both costs. In this paper, we show that deterministic recomputation of data can substantially reduce the cost of cloud storage. Borrowing a well-known dualism from the fault-tolerance community, we note that any data can be equivalently represented by a log of the nondeterministic inputs needed to produce that data. We design a file system, called Knockoff, that selectively substitutes nondeterministic inputs for file data to reduce communication and storage costs. Knockoff compresses both data and computation logs: it uses chunk-based deduplication for file data and delta compression for logs of nondeterminism. In two studies, Knockoff reduces the average cost of sending files to the cloud without versioning by 21% and 24%;the relative benefit increases as versions are retained more frequently.

关键词： Cloud storage

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Treating the storage Stack Like a Network

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ACM TRANSACTIONS ON storage 2017年第1期13卷 1–27页

作者： Stefanovici, Ioan Schroeder, Bianca O'Shea, Greg thereska, Eno Microsoft Res 21 Stn Rd Cambridge CB1 2FB England Univ Toronto Dept Comp Sci 10 Kings Coll RdRm 3302 Toronto ON M5S 3G4 Canada Confluent Inc 101 Univ AveSuite 111 Palo Alto CA 94301 USA Imperial Coll London London England

In a data center, an IO from an application to distributed storage traverses not only the network but also several software stages with diverse functionality. this set of ordered stages is known as the storage or IO stack. Stages include caches, hypervisors, IO schedulers, file systems, and device drivers. Indeed, in a typical data center, the number of these stages is often larger than the number of network hops to the destination. Yet, while packet routing is fundamental to networks, no notion of IO routing exists on the storage stack. the path of an IO to an endpoint is predetermined and hard coded. this forces IO with different needs (e.g., requiring different caching or replica selection) to flow through a one-size-fits-all IO stack structure, resulting in an ossified IO stack. this article proposes sRoute, an architecture that provides a routing abstraction for the storage stack. sRoute comprises a centralized control plane and "sSwitches" on the data plane. the control plane sets the forwarding rules in each sSwitch to route IO requests at runtime based on application-specific policies. A key strength of our architecture is that it works with unmodified applications and Virtual Machines (VMs). this article shows significant benefits of customized IO routing to data center tenants: for example, a factor of 10 for tail IO latency, more than 60% better throughput for a customized replication protocol, a factor of 2 in throughput for customized caching, and enabling live performance debugging in a running system.

关键词： Design Management Performance Data centers storage software-defined storage SDS routing storage stack

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Scalable Persistent Memory file System with Kernel-Userspace Collaboration 19

Scalable Persistent Memory File System with Kernel-Userspace...

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19th usenix conference on file and storage technologies (FAST)

作者： Chen, Youmin Lu, Youyou Zhu, Bohong Arpaci-Dusseau, Andrea C. Arpaci-Dusseau, Remzi H. Shu, Jiwu Tsinghua Univ Beijing Peoples R China Univ Wisconsin Madison WI 53706 USA

ISBN: (纸本)9781939133205

We introduce Kuco, a novel direct-access file system architecture whose main goal is scalability. Kuco utilizes three key techniques - collaborative indexing, two-level locking, and versioned reads - to offload time-consuming tasks, such as pathname resolution and concurrency control, from the kernel to userspace, thus avoiding kernel processing bottlenecks. Upon Kuco, we present the design and implementation of KucoFS, and then experimentally show that KucoFS has excellent performance in a wide range of experiments;importantly, KucoFS scales better than existing file systems by up to an order of magnitude for metadata operations, and fully exploits device bandwidth for data operations.

关键词： Concurrency control

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Reducing Solid-State storage Device Write Stress through Opportunistic In-Place Delta Compression 14

Reducing Solid-State Storage Device Write Stress Through Opp...

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14th usenix conference on file and storage technologies (FAST)

作者： Zhang, Xuebin Li, Jiangpeng Wang, Hao Zhao, Kai Zhang, Tong Rensselaer Polytech Inst ECSE Dept Troy NY 12181 USA SanDisk Corp Milpitas CA USA

ISBN: (纸本)9781931971287

Inside modern SSDs, a small portion of MLC/TLC NAND flash memory blocks operate in SLC-mode to serve as write buffer/cache and/or store hot data. these SLC-mode blocks absorb a large percentage of write operations. To balance memory wear-out, such MLC/TLC-to-SLC configuration rotates among all the memory blocks inside SSDs. this paper presents a simple yet effective design approach to reduce write stress on SLC-mode flash blocks and hence improve the overall SSD lifetime. the key is to implement well-known delta compression without being subject to the read latency and data management complexity penalties inherent to conventional practice. the underlying theme is to leverage the partial programmability of SLC-mode flash memory pages to ensure that the original data and all the subsequent deltas always reside in the same memory physical page. To avoid the storage capacity overhead, we further propose to combine intra-sector lossless data compression with intra-page delta compression, leading to opportunistic in-place delta compression. this paper presents specific techniques to address important issues for its practical implementation, including data error correction, and intra-page data placement and management. We carried out comprehensive experiments, simulations, and ASIC (application-specific integrated circuit) design. the results show that the proposed design solution can largely reduce the write stress on SLC-mode flash memory pages without significant latency overhead and meanwhile incurs relatively small silicon implementation cost.

关键词： Integrated circuit design

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Optimizing Every Operation in a Write-Optimized file System 14

Optimizing Every Operation in a Write-Optimized File System

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14th usenix conference on file and storage technologies (FAST)

作者： Yuan, Jun Zhan, Yang Jannen, William Pandey, Prashant Akshintala, Amogh Chandnani, Kanchan Deo, Pooja Kasheff, Zardosht Walsh, Leif Bender, Michael A. Farach-Colton, Martin Johnson, Rob Kuszmaul, Bradley C. Porter, Donald E. SUNY Stony Brook Stony Brook NY 11794 USA Facebook Menlo Pk CA USA Two Sigma New York NY USA Rutgers State Univ New Brunswick NJ USA MIT Cambridge MA 02139 USA

ISBN: (纸本)9781931971287

file systems that employ write-optimized dictionaries (WODs) can perform random-writes, metadata updates, and recursive directory traversals orders of magnitude faster than conventional file systems. However, previous WOD-based file systems have not obtained all of these performance gains without sacrificing performance on other operations, such as file deletion, file or directory renaming, or sequential writes. Using three techniques, late-binding journaling, zoning, and range deletion, we show that there is no fundamental trade-off in write-optimization. these dramatic improvements can be retained while matching conventional file systems on all other operations. BetrFS 0.2 delivers order-of-magnitude better performance than conventional file systems on directory scans and small random writes and matches the performance of conventional file systems on rename, delete, and sequential I/O. For example, BetrFS 0.2 performs directory scans 2.2x faster, and small random writes over two orders of magnitude faster, than the fastest conventional file system. But unlike BetrFS 0.1, it renames and deletes files commensurate with conventional file systems and performs large sequential I/O at nearly disk bandwidth. the performance benefits of these techniques extend to applications as well. BetrFS 0.2 continues to outperform conventional file systems on many applications, such as as rsync, git-diff, and tar, but improves git-clone performance by 35% over BetrFS 0.1, yielding performance comparable to other file systems.

关键词： Economic and social effects

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Quiver: An informed storage cache for deep learning 18

Quiver: An informed storage cache for deep learning

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18th usenix conference on file and storage technologies, FAST 2020

作者： Kumar, Abhishek Vijaya Sivathanu, Muthian Microsoft Research India

ISBN: (纸本)9781939133120

We introduce Quiver, an informed storage cache for deep learning training (DLT) jobs in a cluster of GPUs. Quiver employs domain-specific intelligence within the caching layer, to achieve much higher efficiency compared to a generic storage cache. First, Quiver uses a secure hash-based addressing to transparently reuse cached data across multiple jobs and even multiple users operating on the same dataset. Second, by codesigning with the deep learning framework (e.g., PyTorch), Quiver employs a technique of substitutable cache hits to get more value from the existing contents of the cache, thus avoiding cache thrashing when cache capacity is much smaller than the working set. third, Quiver dynamically prioritizes cache allocation to jobs that benefit the most from the caching. With a prototype implementation in PyTorch, we show that Quiver can significantly improve throughput of deep learning workloads. Copyright © Proc. of the 18th usenix conference on file and storage Tech., FAST 2020. All rights reserved.

关键词： Program processors

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Infusing Pub-Sub storage with Transactions 22

Infusing Pub-Sub Storage with Transactions

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14th ACM Workshop on Hot Topics in storage and file Systems (Hotstorage)

作者： Rodriguez, Liana V. Bent, John Shaffer, Tim Rangaswami, Raju Florida Int Univ Miami FL 33199 USA Seagate Technol Dublin Ireland

ISBN: (纸本)9781450393997

the need to support new features in existing storage systems is an ongoing concern for storage developers. So is the desire to develop next generation storage systems that can adopt newly developed feature improvements with relative ease. Extending storage systems is challenging because of the inherent complexity of their codebases and the need to ensure that the storage state does not become corrupt or inconsistent when enabling new features. In this work, we examine a new storage architecture, FDMI, that uses the well-established publish-subscribe model for extending the feature set of a host storage system using plugins. A central mechanism in FDMI is transactional coupling. With transactional coupling, the subscribed plugin can either create new transactions that execute asynchronously following the successful completion of the precipitating event or can participate in the pending transaction and control whether the precipitating event itself will or will not be committed. We further create a classification of transactional mechanisms as well as possible desired plugin functionality and explore the matrix of these two classifications to create a new model for faster, safer distributed storage development.

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GIFT: A coupon based throttle-and-reward mechanism for fair and efficient I/O Bandwidth management on parallel storage systems 18

GIFT: A coupon based throttle-and-reward mechanism for fair ...

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18th usenix conference on file and storage technologies, FAST 2020

作者： Patel, Tirthak Garg, Rohan Tiwari, Devesh Northeastern University Nutanix

ISBN: (纸本)9781939133120

Large-scale parallel applications are highly data-intensive and perform terabytes of I/O routinely. Unfortunately, on a large-scale system where multiple applications run concurrently, I/O contention negatively affects system efficiency and causes unfair bandwidth allocation among applications. To address these challenges, this paper introduces GIFT, a principled dynamic approach to achieve fairness among competing applications and improve system efficiency. Copyright © Proc. of the 18th usenix conference on file and storage Tech., FAST 2020. All rights reserved.

关键词： Large scale systems

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Sketching Volume Capacities in Deduplicated storage 17

Sketching Volume Capacities in Deduplicated Storage

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17th usenix conference on file and storage technologies (FAST)

作者： Harnik, Danny Hershcovitch, Moshik Shatsky, Yosef Epstein, Amir Kat, Ronen IBM Res Haifa Israel Citi Innovat Lab TLV Tel Aviv Israel

ISBN: (纸本)9781939133090

the adoption of deduplication in storage systems has introduced significant new challenges for storage management. Specifically, the physical capacities associated with volumes are no longer readily available. In this work we introduce a new approach to analyzing capacities in deduplicated storage environments. We provide sketch-based estimations of fundamental capacity measures required for managing a storage system: How much physical space would be reclaimed if a volume or group of volumes were to be removed from a system (the reclaimable capacity) and how much of the physical space should be attributed to each of the volumes in the system (the attributed capacity). Our methods also support capacity queries for volume groups across multiple storage systems, e.g., how much capacity would a volume group consume after being migrated to another storage system? We provide analytical accuracy guarantees for our estimations as well as empirical evaluations. Our technology is integrated into a prominent all-flash storage array and exhibits high performance even for very large systems. We also demonstrate how this method opens the door for performing placement decisions at the data center level and obtaining insights on deduplication in the field.

关键词： storage management

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