Object Stores for CMS data [Poster] Article Swipe
Nick Smith
,
B. Jayatilaka
,
David Mason
,
O. Gutsche
,
Alison Peisker
,
R. Illingworth
,
Chris Jones
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.2172/1896648
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.2172/1896648
in progress, each scanning at rates exceeding 10 megabytes per second, all of which are sharing access to a very large persistent address space distributed across multiple disks on multiple hosts. Specifically, POPM employs the following techniques to permit this scale of performance and access: Persistent objects: Experimental data to be scanned is ``populated`` as a data structure into the persistent address space supported by POPM. C++ classes with a few key overloaded operators provide nearly transparent semantics for access to the persistent storage. Distributed and parallel I/O: The persistent address space is automatically distributed across disks of multiple ``I/O nodes`` within the POPM system. A striping unit concept is implemented in POPM, permitting fast parallel I/O across the storage nodes, even for small single queries. Efficient Shared access: POPM implements an efficient mechanism for arbitration and multiplexing of I/O access among multiple queries on the same or separate compute nodes.
Related Topics
Concepts
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All OpenAlex metadata
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https://openalex.org/W4308619067Canonical identifier for this work in OpenAlex
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https://doi.org/10.2172/1896648Digital Object Identifier
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Object Stores for CMS data [Poster]Work title
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articleOpenAlex work type
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enPrimary language
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2022Year of publication
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2022-10-24Full publication date if available
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Nick Smith, B. Jayatilaka, David Mason, O. Gutsche, Alison Peisker, R. Illingworth, Chris JonesList of authors in order
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https://doi.org/10.2172/1896648Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.osti.gov/biblio/1896648Direct OA link when available
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Computer science, Object (grammar), Computer graphics (images), Database, Artificial intelligenceTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.progress, | 1 |
| abstract_inverted_index.semantics | 77 |
| abstract_inverted_index.structure | 57 |
| abstract_inverted_index.supported | 63 |
| abstract_inverted_index.Persistent | 45 |
| abstract_inverted_index.implements | 130 |
| abstract_inverted_index.overloaded | 72 |
| abstract_inverted_index.permitting | 113 |
| abstract_inverted_index.persistent | 21, 60, 82, 89 |
| abstract_inverted_index.techniques | 36 |
| abstract_inverted_index.Distributed | 84 |
| abstract_inverted_index.arbitration | 135 |
| abstract_inverted_index.distributed | 24, 94 |
| abstract_inverted_index.implemented | 110 |
| abstract_inverted_index.performance | 42 |
| abstract_inverted_index.transparent | 76 |
| abstract_inverted_index.Experimental | 47 |
| abstract_inverted_index.multiplexing | 137 |
| abstract_inverted_index.Specifically, | 31 |
| abstract_inverted_index.``populated`` | 53 |
| abstract_inverted_index.automatically | 93 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile.value | 0.15453344 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |