The Experts below are selected from a list of 162 Experts worldwide ranked by ideXlab platform
Gaetano T. Montelione - One of the best experts on this subject based on the ideXlab platform.
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SPINS: Standardized ProteIn NMR Storage. A data dictionary and object-oriented relational database for archiving protein NMR spectra
Journal of Biomolecular NMR, 2002Co-Authors: Michael C. Baran, Hunter N.b. Moseley, Gurmukh Sahota, Gaetano T. MontelioneAbstract:Modern protein NMR spectroscopy laboratories have a rapidly growing need for an easily queried local Archival System of raw experimental NMR datasets. SPINS ( S tandardized P rote I n N mr S torage) is an object-oriented relational database that provides facilities for high-volume NMR data Archival, organization of analyses, and dissemination of results to the public domain by automatic preparation of the header files required for submission of data to the BioMagResBank (BMRB). The current version of SPINS coordinates the process from data collection to BMRB deposition of raw NMR data by standardizing and integrating the storage and retrieval of these data in a local laboratory file System. Additional facilities include a data mining query tool, graphical database administration tools, and a NMRStar v2.1.1 file generator. SPINS also includes a user-friendly internet-based graphical user interface, which is optionally integrated with Varian VNMR NMR data collection software. This paper provides an overview of the data model underlying the SPINS database System, a description of its implementation in Oracle, and an outline of future plans for the SPINS project.
J R Scott - One of the best experts on this subject based on the ideXlab platform.
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slash the scalable lightweight Archival storage hierarchy
IEEE Conference on Mass Storage Systems and Technologies, 2005Co-Authors: P Nowoczynski, N Stone, J Sommerfield, B Gill, J R ScottAbstract:Growing compute capacity coupled with advances in parallel fileSystem performance and stability mean that HPC users will inevitably create and store larger datasets. If data residing on parallel fileSystems is not efficiently offloaded to Archival storage, disruptions in the compute cycle will occur. Hierarchical storage caches are a vital aspect of the HPC storage machine because they offload and prime the compute engine's parallel fileSystem. To keep pace with expanding HPC data Systems, these caches must adapt via new scalable architectures. The Pittsburgh Supercomputing Center (PSC) has developed a cooperative caching architecture to act as a distributed front-end cache to a hierarchical storage manager. SLASH, the scalable lightweight Archival storage hierarchy, provides means for creating parallel caching Systems on an otherwise "monolithic" Archival storage System without requiring modifications the Archival System software.
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MSST - SLASH - the scalable lightweight Archival storage hierarchy
22nd IEEE 13th NASA Goddard Conference on Mass Storage Systems and Technologies (MSST'05), 1Co-Authors: P Nowoczynski, N Stone, J Sommerfield, B Gill, J R ScottAbstract:Growing compute capacity coupled with advances in parallel fileSystem performance and stability mean that HPC users will inevitably create and store larger datasets. If data residing on parallel fileSystems is not efficiently offloaded to Archival storage, disruptions in the compute cycle will occur. Hierarchical storage caches are a vital aspect of the HPC storage machine because they offload and prime the compute engine's parallel fileSystem. To keep pace with expanding HPC data Systems, these caches must adapt via new scalable architectures. The Pittsburgh Supercomputing Center (PSC) has developed a cooperative caching architecture to act as a distributed front-end cache to a hierarchical storage manager. SLASH, the scalable lightweight Archival storage hierarchy, provides means for creating parallel caching Systems on an otherwise "monolithic" Archival storage System without requiring modifications the Archival System software.
Michael C. Baran - One of the best experts on this subject based on the ideXlab platform.
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SPINS: Standardized ProteIn NMR Storage. A data dictionary and object-oriented relational database for archiving protein NMR spectra
Journal of Biomolecular NMR, 2002Co-Authors: Michael C. Baran, Hunter N.b. Moseley, Gurmukh Sahota, Gaetano T. MontelioneAbstract:Modern protein NMR spectroscopy laboratories have a rapidly growing need for an easily queried local Archival System of raw experimental NMR datasets. SPINS ( S tandardized P rote I n N mr S torage) is an object-oriented relational database that provides facilities for high-volume NMR data Archival, organization of analyses, and dissemination of results to the public domain by automatic preparation of the header files required for submission of data to the BioMagResBank (BMRB). The current version of SPINS coordinates the process from data collection to BMRB deposition of raw NMR data by standardizing and integrating the storage and retrieval of these data in a local laboratory file System. Additional facilities include a data mining query tool, graphical database administration tools, and a NMRStar v2.1.1 file generator. SPINS also includes a user-friendly internet-based graphical user interface, which is optionally integrated with Varian VNMR NMR data collection software. This paper provides an overview of the data model underlying the SPINS database System, a description of its implementation in Oracle, and an outline of future plans for the SPINS project.
P Nowoczynski - One of the best experts on this subject based on the ideXlab platform.
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slash the scalable lightweight Archival storage hierarchy
IEEE Conference on Mass Storage Systems and Technologies, 2005Co-Authors: P Nowoczynski, N Stone, J Sommerfield, B Gill, J R ScottAbstract:Growing compute capacity coupled with advances in parallel fileSystem performance and stability mean that HPC users will inevitably create and store larger datasets. If data residing on parallel fileSystems is not efficiently offloaded to Archival storage, disruptions in the compute cycle will occur. Hierarchical storage caches are a vital aspect of the HPC storage machine because they offload and prime the compute engine's parallel fileSystem. To keep pace with expanding HPC data Systems, these caches must adapt via new scalable architectures. The Pittsburgh Supercomputing Center (PSC) has developed a cooperative caching architecture to act as a distributed front-end cache to a hierarchical storage manager. SLASH, the scalable lightweight Archival storage hierarchy, provides means for creating parallel caching Systems on an otherwise "monolithic" Archival storage System without requiring modifications the Archival System software.
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MSST - SLASH - the scalable lightweight Archival storage hierarchy
22nd IEEE 13th NASA Goddard Conference on Mass Storage Systems and Technologies (MSST'05), 1Co-Authors: P Nowoczynski, N Stone, J Sommerfield, B Gill, J R ScottAbstract:Growing compute capacity coupled with advances in parallel fileSystem performance and stability mean that HPC users will inevitably create and store larger datasets. If data residing on parallel fileSystems is not efficiently offloaded to Archival storage, disruptions in the compute cycle will occur. Hierarchical storage caches are a vital aspect of the HPC storage machine because they offload and prime the compute engine's parallel fileSystem. To keep pace with expanding HPC data Systems, these caches must adapt via new scalable architectures. The Pittsburgh Supercomputing Center (PSC) has developed a cooperative caching architecture to act as a distributed front-end cache to a hierarchical storage manager. SLASH, the scalable lightweight Archival storage hierarchy, provides means for creating parallel caching Systems on an otherwise "monolithic" Archival storage System without requiring modifications the Archival System software.
Cameron G. Walker - One of the best experts on this subject based on the ideXlab platform.
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Benchmarking and modeling disk-based storage tiers for practical storage design
ACM SIGMETRICS Performance Evaluation Review, 2012Co-Authors: Dongjin Lee, Michael O'sullivan, Cameron G. WalkerAbstract:This paper investigates benchmarking and modeling for a disk-based storage System in order to design and build a practical storage tier. As a practical case study, we focus on the design of an Archival storage tier. The Archival tiers play a critical role in data preservation as almost all current data will eventually be archived and the demands placed on Archival tiers are growing because of large regularly-scheduled back-ups. Archival tiers usually consist of tape-based devices with a large storage capacity, but limited I/O performance for retrieving data, especially when multiple retrieval requests are made simultaneously. As the cost of disk-based devices continues to decrease while the capacity of individual disks increases, disk-based Systems are becoming a more realistic option for both enterprise and commodity Archival storage tiers. We utilize Archival workloads developed from an analysis of historical data in order to provide accurate and robust benchmarks of System performance as an archive. We then embed our practical measurements in a measurementdriven optimization approach to design an Archival System. Our approach produces a low cost design for a commodity disk-based Archival storage System. Using our measurementdriven model, ideal storage building blocks are identified for a real-world Archival tier design.
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Benchmarking and modeling disk-based storage tiers for practical storage design
Proceedings of the second international workshop on Performance modeling benchmarking and simulation of high performance computing systems - PMBS '11, 2011Co-Authors: Dongjin Lee, Michael O'sullivan, Cameron G. WalkerAbstract:This paper presents benchmark experiments for designing an optimal Archival storage System. The benchmark utilizes Archival workloads developed from an analysis of historical file size distributions. The workloads provide more appropriate measurements of System performance as an archive than traditional approaches. We use these benchmarks to measure disk-based Archival Systems. We then consider designing an Archival System based on our benchmark measurements and produce a low cost design for a commodity disk-based Archival storage System. Combining results of predictions along with our optimization-driven design, we discover an ideal building block for an Archival storage System.