Parallel and Efficient IP Lookup using Bloom Filters on Intel R Xeon PhiTM

  • Alexandre Lucchesi
  • André C. Drummond
  • George Teodoro


The IP lookup phase is the core operation in packet forwarding, which is implemented via a Longest Prefix Matching (LPM) to find the next hop for every input address. In this work, we evaluate the use of parallel techniques to develop a highly optimized IP lookup algorithm that employs Bloom filters and hash tables. More specifically, we investigate the implementation of our algorithm on multi-core CPUs and on the Intel R Xeon PhiTM (Intel Phi) many-core coprocessor. Our analysis includes the efficient parallelization of our Bloom filters algorithm on both devices, and the experimental results show that we were able to attain high performance with this solution (over 88 million lookups per second on a single Intel Phi for IPv6). We also compared the Bloom filters optimized solution to an efficient approach based on the Multi-Index Hybrid Trie (MIHT). This comparison shows that the most efficient sequential algorithm may not be the best option in a parallel setting. Instead, it is necessary to evaluate the processors characteristics, algorithms compute/data demands and data structures employed to analyze how the algorithms will benefit from the target computing device. These findings are also important to new efforts in algorithmic developments in the topic, which have been highly focused on sequential solutions.
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LUCCHESI, Alexandre; DRUMMOND, André C.; TEODORO, George. Parallel and Efficient IP Lookup using Bloom Filters on Intel R Xeon PhiTM. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 35. , 2017, Belém. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2017 . ISSN 2177-9384.