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Exact Pattern Matching with Feed-Forward Bloom Filters Iulian Moraru

Summary: Exact Pattern Matching with Feed-Forward Bloom Filters
Iulian Moraru
David G. Andersen
This paper presents a new, memory efficient and cache-
optimized algorithm for simultaneously searching for a large
number of patterns in a very large corpus. This algo-
rithm 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 al-
gorithms, we show that this technique, along with a CPU
architecture aware design of the Bloom filter, can provide
speedups between 2 and 30, and memory consumption
reductions as large as 50 when compared with grep.
1 Introduction
Matching a large corpus of data against a database
of thousands or millions of patterns is an important
component of virus scanning [18], data mining and
machine learning [1], and bioinformatics [19], to name


Source: Andersen, Dave - School of Computer Science, Carnegie Mellon University


Collections: Computer Technologies and Information Sciences