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Article . 2020
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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Non-relational Databases on FPGAs: Survey, Design Decisions, Challenges

Authors: Jonas Dann; Daniel Ritter 0001; Holger Fröning;

Non-relational Databases on FPGAs: Survey, Design Decisions, Challenges

Abstract

Non-relational database systems (NRDS) such as graph and key-value have gained attention in various trending business and analytical application domains. However, while CPU performance scaling becomes increasingly more difficult, field-programmable gate arrays (FPGA)- accelerated NRDS have not been systematically studied yet. This survey describes and categorizes the inherent differences and non-trivial tradeoffs of relevant NRDS classes (i.e., graph, document, key-value, and wide-column) as well as their commonalities in the context of common design decisions when building such a system with FPGAs. In particular, we highlight accelerator tasks, FPGA placement, accelerator design patterns, and justification for using FPGAs in different system contexts. We close with open research and engineering challenges to outline the future of FPGA-accelerated NRDS.

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Keywords

FOS: Computer and information sciences, Computer Science - Databases, Hardware Architecture (cs.AR), Databases (cs.DB), Computer Science - Hardware Architecture

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Top 10%
Top 10%
Green