Volltext-Downloads (blau) und Frontdoor-Views (grau)

nKV: near-data processing with KV-stores on native computational storage

  • Massive data transfers in modern key/value stores resulting from low data-locality and data-to-code system design hurt their performance and scalability. Near-data processing (NDP) designs represent a feasible solution, which although not new, have yet to see widespread use. In this paper we introduce nKV, which is a key/value store utilizing native computational storage and near-data processing. On the one hand, nKV can directly control the data and computation placement on the underlying storage hardware. On the other hand, nKV propagates the data formats and layouts to the storage device where, software and hardware parsers and accessors are implemented. Both allow NDP operations to execute in host-intervention-free manner, directly on physical addresses and thus better utilize the underlying hardware. Our performance evaluation is based on executing traditional KV operations (GET, SCAN) and on complex graph-processing algorithms (Betweenness Centrality) in-situ, with 1.4×-2.7× better performance on real hardware – the COSMOS+ platform.

Download full text files

  • 2819.pdf
    eng

Export metadata

Additional Services

Share in Twitter Search Google Scholar

Statistics

frontdoor_oas
Metadaten
Name:Vinçon, Tobias; Bernhardt, Arthur; Petrov, Ilia
DOI:https://doi.org/10.1145/3399666.3399934
ISBN:978-1-4503-8024-9
Erschienen in:DaMoN '20 : proceedings of the 16th International Workshop on Data Management on New Hardware : Portland, Oregon, June, 2020
Publisher:Assoc. of Computing Machinery
Place of publication:New York, NY
Document Type:Conference Proceeding
Language:English
Year of Publication:2020
Pagenumber:11
Dewey Decimal Classification:004 Informatik
Open Access:Nein
Licence (English):License Logo  Lizenzbedingungen ACM