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Author Moraru, Iulian ♦ Andersen, David G.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2012
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data
Subject Keyword Bloom filters ♦ CPU caches ♦ Pattern matching ♦ Memory efficiency
Abstract This article presents a new, memory efficient and cache-optimized algorithm for simultaneously searching for a large number of patterns in a very large corpus. This algorithm builds upon the Rabin-Karp string search algorithm and incorporates a new type of Bloom filter that we call a feed-forward Bloom filter. While it retains the asymptotic time complexity of previous multiple pattern matching algorithms, we show that this technique, along with a CPU architecture-aware design of the Bloom filter, can provide speed-ups between 2× and 30×, and memory consumption reductions as large as 50× when compared with grep. Our algorithm is also well suited for implementations on GPUs: A modern GPU can search for 3 million patterns at a rate of 580MB/s, and for 100 million patterns (a prohibitive number for traditional algorithms) at a rate of 170MB/s.
ISSN 10846654
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2012-09-01
Publisher Place New York
e-ISSN 10846654
Journal Journal of Experimental Algorithmics (JEA)
Volume Number 17
Page Count 18
Starting Page 3.1
Ending Page 3.18

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Source: ACM Digital Library