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Evaluating performance and energy in file system server workloads 10

Evaluating performance and energy in file system server work...

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proceedings of the 8th usenix conference on file and storage technologies

作者： Priya Sehgal Vasily Tarasov Erez Zadok Stony Brook University

Recently, power has emerged as a critical factor in designing components of storage systems, especially for power-hungry data centers. While there is some research into power-aware storage stack components, there are no systematic studies evaluating each component's impact separately. this paper evaluates the file system's impact on energy consumption and performance. We studied several popular Linux file systems, with various mount and format options, using the fileBench workload generator to emulate four server workloads: Web, database, mail, and file server. In case of a server node consisting of a single disk, CPU power generally exceeds disk-power consumption. However, file system design, implementation, and available features have a significant effect on CPU/disk utilization, and hence on performance and power. We discovered that default file system options are often suboptimal, and even poor. We show that a carefulmatching of expectedworkloads to file system types and options can improve power-performance efficiency by a factor ranging from 1.05 to 9.4 times.

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HydraFS: a high-throughput file system for the HYDRAstor content-addressable storage system 10

HydraFS: a high-throughput file system for the HYDRAstor con...

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proceedings of the 8th usenix conference on file and storage technologies

作者： Cristian Ungureanu Benjamin Atkin Akshat Aranya Salil Gokhale Stephen Rago Grzegorz Całkowski Cezary Dubnicki Aniruddha Bohra NEC Laboratories America

A content-addressable storage (CAS) system is a valuable tool for building storage solutions, providing efficiency by automatically detecting and eliminating duplicate blocks; it can also be capable of high throughput, at least for streaming access. However, the absence of a standardized API is a barrier to the use of CAS for existing applications. Additionally, applications would have to deal with the unique characteristics of CAS, such as immutability of blocks and high latency of operations. An attractive alternative is to build a file system on top of CAS, since applications can use its interface without *** a file system onto a CAS system efficiently, so as to obtain high duplicate elimination and high throughput, requires a very different design than for a traditional disk subsystem. In this paper, we present the design, implementation, and evaluation of HydraFS, a file system built on top of HYDRAstor, a scalable, distributed, content-addressable block storage system. HydraFS provides high-performance reads and writes for streaming access, achieving 82-100% of the HYDRAstor throughput, while maintaining high duplicate elimination.

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DFS: a file system for virtualized flash storage 10

DFS: a file system for virtualized flash storage

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proceedings of the 8th usenix conference on file and storage technologies

作者： William K. Josephson Lars A. Bongo David Flynn Kai Li

this paper presents the design, implementation and evaluation of Direct file System (DFS) for virtualized flash storage. Instead of using traditional layers of abstraction, our layers of abstraction are designed for directly accessing flash memory devices. DFS has two main novel features. First, it lays out its files directly in a very large virtual storage address space provided by FusionIO's virtual flash storage layer. Second, it leverages the virtual flash storage layer to perform block allocations and atomic updates. As a result, DFS performs better and it is much simpler than a traditional Unix file system with similar functionalities. Our microbenchmark results show that DFS can deliver 94,000 I/O operations per second (IOPS) for direct reads and 71,000 IOPS for direct writes with the virtualized flash storage layer on FusionIO's ioDrive. For direct access performance, DFS is consistently better than ext3 on the same platform, sometimes by 20%. For buffered access performance, DFS is also consistently better than ext3, and sometimes by over 149%. Our application benchmarks show that DFS outperforms ext3 by 7% to 250% while requiring less CPU power.

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Membrane: operating system support for restartable file systems 10

Membrane: operating system support for restartable file syst...

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proceedings of the 8th usenix conference on file and storage technologies

作者： Swaminathan Sundararaman Sriram Subramanian Abhishek Rajimwale Andrea C. Arpaci-Dusseau Remzi H. Arpaci-Dusseau Michael M. Swift Computer Sciences Department University of Wisconsin Madison

We introduce Membrane, a set of changes to the operating system to support restartable file systems. Membrane allows an operating system to tolerate a broad class of file system failures and does so while remaining transparent to running applications; upon failure, the file system restarts, its state is restored, and pending application requests are serviced as if no failure had occurred. Membrane provides transparent recovery through a lightweight logging and checkpoint infrastructure, and includes novel techniques to improve performance and correctness of its fault-anticipation and recovery machinery. We tested Membrane with ext2, ext3, and VFAT. through experimentation, we show that Membrane induces little performance overhead and can tolerate a wide range of file system crashes. More critically, Membrane does so with little or no change to existing file systems thus improving robustness to crashes without mandating intrusive changes to existing file-system code.

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SRCMap: energy proportional storage using dynamic consolidation 10

SRCMap: energy proportional storage using dynamic consolidat...

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proceedings of the 8th usenix conference on file and storage technologies

作者： Akshat Verma Ricardo Koller Luis Useche Raju Rangaswami IBM Research India Florida International University

We investigate the problem of creating an energy proportional storage system through power-aware dynamic storage consolidation. Our proposal, Sample-Replicate-Consolidate Mapping (SRCMap), is a storage virtualization layer optimization that enables energy proportionality for dynamic I/O workloads by consolidating the cumulative workload on a subset of physical volumes proportional to the I/O workload intensity. Instead of migrating data across physical volumes dynamically or replicating entire volumes, both of which are prohibitively expensive, SRCMap samples a subset of blocks from each data volume that constitutes its working set and replicates these on other physical volumes. During a given consolidation interval, SRCMap activates a minimal set of physical volumes to serve the workload and spins down the remaining volumes, redirecting their workload to replicas on active volumes. We present both theoretical and experimental evidence to establish the effectiveness of SRCMap in minimizing the power consumption of enterprise storage systems.

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qufiles: the right file at the right time 10

quFiles: the right file at the right time

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proceedings of the 8th usenix conference on file and storage technologies

作者： Kaushik Veeraraghavan Jason Flinn Edmund B. Nightingale Brian Noble University of Michigan Microsoft Research Redmond

A qufile is a unifying abstraction that simplifies data management by encapsulating different physical representations of the same logical data. Similar to a quBit (quantum bit), the particular representation of the logical data displayed by a qufile is not determined until the moment it is needed. the representation returned by a qufile is specified by a data-specific policy that can take into account context such as the application requesting the data, the device on which data is accessed, screen size, and battery status. We demonstrate the generality of the qufile abstraction by using it to implement six case studies: resource management, copy-on-write versioning, data redaction, resource-aware directories, application-aware adaptation, and platform-specific encoding. Most qufile policies were expressed using less than one hundred lines of code. Our experimental results show that, with caching and other performance optimizations, qufiles add less than 1% overhead to application-level file system benchmarks.

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Panache: a parallel file system cache for global file access 10

Panache: a parallel file system cache for global file access

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proceedings of the 8th usenix conference on file and storage technologies

作者： Marc Eshel Roger Haskin Dean Hildebrand Manoj Naik Frank Schmuck Renu Tewari IBM Almaden Research

Cloud computing promises large-scale and seamless access to vast quantities of data across the globe. Applications will demand the reliability, consistency, and performance of a traditional cluster file system regardless of the physical distance between data *** is a scalable, high-performance, clustered file system cache for parallel data-intensive applications that require wide area file access. Panache is the first file system cache to exploit parallelism in every aspect of its design--parallel applications can access and update the cache from multiple nodes while data and metadata is pulled into and pushed out of the cache in parallel. Data is cached and updated using pNFS, which performs parallel I/O between clients and servers, eliminating the single-server bottleneck of vanilla client-server file access protocols. Furthermore, Panache shields applications from fluctuating WAN latencies and outages and is easy to deploy as it relies on open standards for high-performance file serving and does not require any proprietary hardware or software to be installed at the remote *** this paper, we present the overall design and implementation of Panache and evaluate its key features with multiple workloads across local and wide area networks.

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Efficient object storage journaling in a distributed parallel file system 10

Efficient object storage journaling in a distributed paralle...

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proceedings of the 8th usenix conference on file and storage technologies

作者： Sarp Oral Feiyi Wang David Dillow Galen Shipman Ross Miller Oleg Drokin National Center for Computational Sciences Oak Ridge National Laboratory Lustre Center of Excellence at ORNL Sun Microsystem Inc.

Journaling is a widely used technique to increase file system robustness against metadata and/or data corruptions. While the overhead of journaling can be masked by the page cache for small-scale, local file systems, we found that Lustre's use of journaling for the object store significantly impacted the overall performance of our large-scale centerwide parallel file system. By requiring that each write request wait for a journal transaction to commit, Lustre introduced serialization to the client request stream and imposed additional latency due to disk head movement (seeks) for each *** this paper, we present the challenges we faced while deploying a very large scale production storage system. Our work provides a head-to-head comparison of two significantly different approaches to increasing the overall efficiency of the Lustre file system. First, we present a hardware solution using external journaling devices to eliminate the latencies incurred by the extra disk head seeks due to journaling. Second, we introduce a software-based optimization to remove the synchronous commit for each write request, side-stepping additional latency and amortizing the journal seeks across a much larger number of *** solutions have been implemented and experimentally tested on our Spider storage system, a very large scale Lustre deployment. Our tests show both methods considerably improve the write performance, in some cases up to 93%. Testing with a real-world scientific application showed a 37% decrease in the number journal updates, each with an associated seek - which translated into an average I/O bandwidth improvement of 56.3%.

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BASIL: automated IO load balancing across storage devices 10

BASIL: automated IO load balancing across storage devices

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proceedings of the 8th usenix conference on file and storage technologies

作者： Ajay Gulati Chethan Kumar Irfan Ahmad Karan Kumar VMware Inc. Carnegie Mellon University

Live migration of virtual hard disks between storage arrays has long been possible. However, there is a dearth of online tools to perform automated virtual disk placement and IO load balancing across multiple storage arrays. this problem is quite challenging because the performance of IO workloads depends heavily on their own characteristics and that of the underlying storage device. Moreover, many device-specific details are hidden behind the interface exposed by storage *** this paper, we introduce BASIL, a novel software system that automatically manages virtual disk placement and performs load balancing across devices without assuming any support from the storage arrays. BASIL uses IO latency as a primary metric for modeling. Our technique involves separate online modeling of workloads and storage devices. BASIL uses these models to recommend migrations between devices to balance load and improve overall *** present the design and implementation of BASIL in the context of VMware ESX, a hypervisor-based virtualization system, and demonstrate that the modeling works well for a wide range of workloads and devices. We evaluate the placements recommended by BASIL, and show that they lead to improvements of at least 25% in both latency and throughput for 80 percent of the hundreds of microbenchmark configurations we ran. When tested with enterprise applications, BASIL performed favorably versus human experts, improving latency by 18-27%.

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Discovery of application workloads from network file traces 10

Discovery of application workloads from network file traces

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proceedings of the 8th usenix conference on file and storage technologies

作者： Neeraja J. Yadwadkar Chiranjib Bhattacharyya K. Gopinath thirumale Niranjan Sai Susarla Department of Computer Science and Automation Indian Institute of Science NetApp Advanced Technology Group

An understanding of application I/O access patterns is useful in several situations. First, gaining insight into what applications are doing with their data at a semantic level helps in designing efficient storage systems. Second, it helps create benchmarks that mimic realistic application behavior closely. third, it enables autonomic systems as the information obtained can be used to adapt the system in a closed *** these use cases require the ability to extract the application-level semantics of I/O operations. Methods such as modifying application code to associate I/O operations with semantic tags are intrusive. It is well known that network file system traces are an important source of information that can be obtained non-intrusively and analyzed either online or offline. these traces are a sequence of primitive file system operations and their parameters. Simple counting, statistical analysis or deterministic search techniques are inadequate for discovering application-level semantics in the general case, because of the inherent variation and noise in realistic *** this paper, we describe a trace analysis methodology based on Profile Hidden Markov Models. We show that the methodology has powerful discriminatory capabilities that enable it to recognize applications based on the patterns in the traces, and to mark out regions in a long trace that encapsulate sets of primitive operations that represent higher-level application actions. It is robust enough that it can work around discrepancies between training and target traces such as in length and interleaving with other operations. We demonstrate the feasibility of recognizing patterns based on a small sampling of the trace, enabling faster trace analysis. Preliminary experiments show that the method is capable of learning accurate profile models on live traces in an online setting. We present a detailed evaluation of this methodology in a UNIX environment using NFS traces of selected commonly used a

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