DocumentCode :
2720304
Title :
Configurable hardware-based streaming architecture using Online Programmable-Blocks
Author :
Najafi, Mohammadreza ; Sadoghi, Mohammad ; Jacobsen, Hans-Arno
fYear :
2015
fDate :
13-17 April 2015
Firstpage :
819
Lastpage :
830
Abstract :
The limitations of traditional general-purpose processors have motivated the use of specialized hardware solutions (e.g., FPGAs) to achieve higher performance in stream processing. However, state-of-the-art hardware-only solutions have limited support to adapt to changes in the query workload. In this work, we present a reconfigurable hardware-based streaming architecture that offers the flexibility to accept new queries and to change existing ones without the need for expensive hardware reconfiguration. We introduce the Online Programmable Block (OP-Block), a ”Lego-like” connectable stream processing element, for constructing a custom Flexible Query Processor (FQP), suitable to a wide range of data streaming applications, including real-time data analytics, information filtering, intrusion detection, algorithmic trading, targeted advertising, and complex event processing. Through evaluations, we conclude that updating OP-Blocks to support new queries takes on the order of nano to micro-seconds (e.g., 40 ns to realize a join operator on an OP-Block), a feature critical to support of streaming applications on FPGAs.
Keywords :
field programmable gate arrays; query processing; reconfigurable architectures; FPGA; FQP; Lego-like connectable stream processing element; OP-block; algorithmic trading; complex event processing; configurable hardware-based streaming architecture; data streaming applications; flexible query processor; general-purpose processors; hardware reconfiguration; information filtering; intrusion detection; online programmable block; online programmable-blocks; real-time data analytics; reconfigurable hardware-based streaming architecture; targeted advertising; Computer architecture; Field programmable gate arrays; Hardware; Logic gates; Pipeline processing; Random access memory; Software;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering (ICDE), 2015 IEEE 31st International Conference on
Conference_Location :
Seoul
Type :
conf
DOI :
10.1109/ICDE.2015.7113336
Filename :
7113336
Link To Document :
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