Detail publikace

Fast Reconfigurable Hash Functions for Network Flow Hashing in FPGAs

GROCHOL, D. SEKANINA, L.

Originální název

Fast Reconfigurable Hash Functions for Network Flow Hashing in FPGAs

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Efficient monitoring of high speed computer networks operating with a 100 Gigabit per second (Gbps) data throughput requires a suitable hardware acceleration of its key components. We present a platform capable of automated design of hash functions suitable for network flow hashing. The platform employs a multi-objective linear genetic programming developed for the hash function design. We evolved high-quality hash functions and implemented them in a field programmable gate array (FPGA). Several evolved hash functions were combined together in order to form a new reconfigurable hash function. The proposed reconfigurable design significantly reduces the area on a chip while the maximum operation frequency remains very close to the fastest hash functions. Properties of evolved hash functions were compared with the state-of-the-art hash functions in terms of the quality of hashing, area and operation frequency in the FPGA.

Klíčová slova

hash function, FPGA, genetic programming, network flow

Autoři

GROCHOL, D.; SEKANINA, L.

Vydáno

15. 6. 2018

Nakladatel

Institute of Electrical and Electronics Engineers

Místo

Edinburgh

ISBN

978-1-5386-7753-7

Kniha

Proceedings of the 2018 NASA/ESA Conference on Adaptive Hardware and Systems

Strany od

257

Strany do

263

Strany počet

7

URL

https://www.fit.vut.cz/research/publication/11706/

BibTex

@inproceedings{BUT155031,
  author="David {Grochol} and Lukáš {Sekanina}",
  title="Fast Reconfigurable Hash Functions for Network Flow Hashing in FPGAs",
  booktitle="Proceedings of the 2018 NASA/ESA Conference on Adaptive Hardware and Systems",
  year="2018",
  pages="257--263",
  publisher="Institute of Electrical and Electronics Engineers",
  address="Edinburgh",
  doi="10.1109/AHS.2018.8541401",
  isbn="978-1-5386-7753-7",
  url="https://www.fit.vut.cz/research/publication/11706/"
}