Evaluation of cache base network processor by using real backbone network trace

Shinichi Ishida, Michitaka Okuno, Hiroaki Nishi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper a novel cache-based packet-processing-engine (PPE) architecture that achieves high packet-processing throughput with low-power consumption is proposed and evaluated. As network packets of the same header information appear repeatedly in a short time, a special cache, the so called header-learning cache(HLC), memorizes the packet-processing method and enables most packets to skip the execution at the processing units array. The implementation of the cache-based PPE architecture, P-Gear, was designed. Real backbone network trace was used to evaluate the performance of it. This P-Gear can achieve over 80% cache hit rate using 4K/32K entry for access/core networks. Compared to conventional PPE, P-Gear can achieve 100-Gbps (gigabit per second) packet-processing throughput with only 36.5% of the die size and 32.6% of the power consumption required by the conventional PPE.

Original languageEnglish
Title of host publication2006 Workshop on High Performance Switching and Routing, HPSR 2006
PublisherIEEE Computer Society
Pages49-54
Number of pages6
ISBN (Print)0780395697, 9780780395695
DOIs
Publication statusPublished - 2006
Event2006 Workshop on High Performance Switching and Routing, HPSR 2006 - Poznan, Poland
Duration: 2006 Jun 72006 Jun 9

Publication series

Name2006 Workshop on High Performance Switching and Routing, HPSR 2006

Other

Other2006 Workshop on High Performance Switching and Routing, HPSR 2006
Country/TerritoryPoland
CityPoznan
Period06/6/706/6/9

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Theoretical Computer Science

Fingerprint

Dive into the research topics of 'Evaluation of cache base network processor by using real backbone network trace'. Together they form a unique fingerprint.

Cite this