arrow
Return

Sequence-preserving parallel IP lookup using multiple SRAM-based pipelines

delete2009-09-01
delete14
PRE
AI
W
Weirong Jiang *
V
Viktor K. Prasanna
DOI:10.1016/j.jpdc.2009.04.001delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
SRAM (static random access memory)-based pipelined algorithmic solutions have become competitive alternatives to TCAMs (ternary content addressable memories) for high-throughput IP lookup. Multiple pipelines can be utilized in parallel to improve the throughput further. However, several challenges must be addressed to make such solutions feasible. First, the memory distribution over different pipelines, as well as across different stages of each pipeline, must be balanced. Second, the traffic among these pipelines should be balanced. Third, the intra-flow packet order (i.e. the sequence) must be preserved. In this paper, we propose a parallel SRAM-based multi-pipeline architecture for IP lookup. A two-level mapping scheme is developed to balance the memory requirement among the pipelines as well as across the stages in each pipeline. To balance the traffic, we propose an early caching scheme to exploit the data locality inherent in the architecture. Our technique uses neither a large reorder buffer nor complex reorder logic. Instead, a flow-aware queuing scheme exploiting the flow information is used to maintain the intra-flow sequence. Extensive simulation using real-life traffic traces shows that the proposed architecture with 8 pipelines can achieve a throughput of up to 10 billion packets per second, i.e. 3.2 Tbps for minimum size (40 bytes) packets, while preserving intra-flow packet order. (c) 2009 Elsevier Inc. All rights reserved.
Keywords:
IP lookup
Pipeline
SRAM
Router
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Journal of Parallel and Distributed Computing cover
Journal of Parallel and Distributed Computing
IF:
4
Papers:
3.8K
Citations:
4.8K

Organization

U
university of southern california
Scholars:
4.6W
Papers: 3.8W
Citations: 51