Conference paper

KEKELY Michal and KOŘENEK Jan. Packet Classification with Limited Memory Resources. In: In proceedings 2017 Euromicro Conference on Digital System Design. Vieden: Institute of Electrical and Electronics Engineers, 2017, pp. 179-183. ISBN 978-1-5386-2145-5.
Publication language:english
Original title:Packet Classification with Limited Memory Resources
Title (cs):Klasifikace paketú s omezenými zdroji
Pages:179-183
Proceedings:In proceedings 2017 Euromicro Conference on Digital System Design
Conference:20th Euromicro Conference on Digital Systems Design
Place:Vieden, AT
Year:2017
ISBN:978-1-5386-2145-5
DOI:10.1109/DSD.2017.61
Publisher:Institute of Electrical and Electronics Engineers
Keywords
DCFL, packet classification, FPGA, P4
Annotation
Network security and monitoring devices use packet classification to match packet header fields in a set of rules. Many hardware architectures have been designed to accelerate packet classification and achieve wire-speed throughput for 100Gbps networks. The architectures are designed for high throughput even for the shortest packets. However, FPGA SoC and Intel Xeon with FPGA have limited resources for multiple accelerators. Usually, it is necessary to balance between available resources and the level of acceleration. Therefore, we have designed new hardware architecture for packet classification, which can balance between the processing speed and hardware resources. To achieve 10 Gbps average throughput the architecture need only 20 BlockRAMs for 5500 rules. Moreover, the architecture can scale the processing speed to wire-speed throughput on 100 Gbps line at the cost of additional memory resources.
BibTeX:
@INPROCEEDINGS{
   author = {Michal Kekely and Jan Ko{\v{r}}enek},
   title = {Packet Classification with Limited Memory
	Resources},
   pages = {179--183},
   booktitle = {In proceedings 2017 Euromicro Conference on Digital System
	Design},
   year = 2017,
   location = {Vieden, AT},
   publisher = {Institute of Electrical and Electronics Engineers},
   ISBN = {978-1-5386-2145-5},
   doi = {10.1109/DSD.2017.61},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php.en.iso-8859-2?id=11550}
}

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