Search results for "Storage management"

showing 4 items of 4 documents

Random Slicing: Efficient and Scalable Data Placement for Large-Scale Storage Systems

2014

The ever-growing amount of data requires highly scalable storage solutions. The most flexible approach is to use storage pools that can be expanded and scaled down by adding or removing storage devices. To make this approach usable, it is necessary to provide a solution to locate data items in such a dynamic environment. This article presents and evaluates the Random Slicing strategy, which incorporates lessons learned from table-based, rule-based, and pseudo-randomized hashing strategies and is able to provide a simple and efficient strategy that scales up to handle exascale data. Random Slicing keeps a small table with information about previous storage system insert and remove operations…

DesignComputer scienceDistributed computingPerformancestorage managementHash function0102 computer and information sciences02 engineering and technologyParallel computingUSable01 natural sciencesSlicingrandomized data distributionAffordable and Clean Energy0202 electrical engineering electronic engineering information engineeringRandomnessExperimentationscalabilityPseudorandom number generatorbusiness.industry020206 networking & telecommunicationsReliabilityData FormatPRNG010201 computation theory & mathematicsHardware and ArchitectureComputer data storageScalabilityTable (database)businessNetworking & Telecommunications
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LPCC

2019

Most high-performance computing (HPC) clusters use a global parallel file system to enable high data throughput. The parallel file system is typically centralized and its storage media are physically separated from the compute cluster. Compute nodes as clients of the parallel file system are often additionally equipped with SSDs. The node internal storage media are rarely well-integrated into the I/O and compute workflows. How to make full and flexible use of these storage media is therefore a valuable research question. In this paper, we propose a hierarchical Persistent Client Caching (LPCC) mechanism for the Lustre file system. LPCC provides two modes: RW-PCC builds a read-write cache on…

File systemComputer scienceComputer clusterHierarchical storage management0202 electrical engineering electronic engineering information engineeringOperating system020206 networking & telecommunications020207 software engineeringLustre (file system)02 engineering and technologyCachecomputer.software_genrecomputerProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
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NVMM-Oriented Hierarchical Persistent Client Caching for Lustre

2021

In high-performance computing (HPC), data and metadata are stored on special server nodes and client applications access the servers’ data and metadata through a network, which induces network latencies and resource contention. These server nodes are typically equipped with (slow) magnetic disks, while the client nodes store temporary data on fast SSDs or even on non-volatile main memory (NVMM). Therefore, the full potential of parallel file systems can only be reached if fast client side storage devices are included into the overall storage architecture. In this article, we propose an NVMM-based hierarchical persistent client cache for the Lustre file system (NVMM-LPCC for short). NVMM-LPC…

Record lockingComputer science020206 networking & telecommunications020207 software engineering02 engineering and technologyClient-sidecomputer.software_genreMetadataHardware and ArchitectureServerHierarchical storage managementScalability0202 electrical engineering electronic engineering information engineeringOperating systemLustre (file system)NamespacecomputerACM Transactions on Storage
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Fusing storage and computing for the domain of business intelligence and analytics: research opportunities

2015

With the growing importance of external and shared data, the set of requirements for Business Intelligence and Analytics (BIA) is shifting. Current solutions still come with shortcomings, esp. In multi-stakeholder environments where sensitive content is exchanged. We argue that a new level in the evolution of BIA can be unlocked by tearing down the barriers between storage and computing based on upcoming storage technologies. In particular, we propose a revitalization of ideas from object-oriented databases. We present results from a joint project that aimed at delineating design options for BIA solutions built upon this idea. The paper outlines the interplay of various architectural layers…

Supply chain managementCompetitive intelligenceComputer sciencebusiness.industryObject-oriented databasesCloud computingStorage managementData scienceData modelingDomain (software engineering)Business intelligenceBases de dades orientades a objectesAnalyticsBusiness intelligenceCompetitive intelligenceBusiness logicbusiness:Informàtica::Arquitectura de computadors [Àrees temàtiques de la UPC]Intel·ligència competitiva
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