# Changeset 3126 for docs/Working/re/re-main.tex.backup

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May 10, 2013, 4:16:34 PM (6 years ago)
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Rough notes.

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 r3124 \begin{abstract} A data parallel regular expression matching method using the concept of bitstream technology is introduced and studied in application to the problem of fast regular expression matching. A parallel regular expression matching method is introduced and studied in application to the problem of online pattern matching. The method is based on the concept of parallel %\input{introduction.tex} % parallel bitstream technology, parallelization, regular expressions Regular expresssion matching is an extensively studied problem with application to numerous application domains. A multitude of algorithms and software tools have been developed to the address the particular demands of the various application domains. The pattern matching problem can be stated as follows. Given a text T$_{1..n}$ of n characters and a pattern P, find all the text positions of T that start an occurrence of P. Alternatively, one may want all the final positions of occurrences. Some applications require slightly different output such as the line that matches the pattern. A pattern P can be a simple string, but it can also be, a regular expression. A regular expression, is an expression that specifies a set of strings. A regular expression is composed of (i) simple strings and (ii) the union, concatenation and Kleene closure of other regular expressions. To avoid parentheses it is assumed that the Kleene star has the highest priority, next concatenation and then alternation, however, most formalisms provides grouping operators to allow the definition of scope and operator precedence. Readers unfamiliar with the concept of regular expression matching are referred classical texts such as \cite{aho2007}. Regular expression matching is commonly performed using a wide variety of publically available software tools for on-line pattern matching. For instance, UNIX grep, Gnu grep, agrep, cgrep, nrgrep, and Perl regular expressions \cite{abou-assaleh2004}. Amongst these tools Gnu grep (egrep), agrep, and nrgrep are widely known and considered as the fastest regular expression matching tools in practice \cite{navarro2000}. and are of particular interest to this study. % simple patterns, extended patterns, regular expressions % motivation / previous work Although the finite state machine methods used in the scanning and parsing of Although tradi finite state machine methods used in the scanning and parsing of text streams is considered to be the hardest of the â13 dwarvesâ to parallelize [1], parallel bitstream technology shows considerable promise for these types of We further increase the parallelism in our methods by introducing a new parallel scanning primitive which we have coined 'Match Star' that returns all matches in a single operation and eliminates the need for back tracking ... (ELABORATE) scanning primitive which we have coined Match Star. Match Star returns all matches in a single operation and eliminates backtracking when a partially successful search path fails. The remainder of this paper is organized as follows. Given a text T$_{1..n}$ of n characters and a pattern P, the pattern matching problem can be stated as follows. Find all the text positions of T that start an occurrence of P. Alternatively, one may want all the final positions of occurrences. Some applications require slightly different output such as the line that matches the pattern. Section~\ref{Background} presents background material on classic regular expression pattern matching techniques and provides insight into the efficiency of traditional regular expression software tools. The pattern P can be just a simple string, but it can also be, for example, a regular expression. Section~\ref{Bitwise Parallel Data Streams} describes out data parallel regular expression matching techniques. A regular expression, or pattern, is an expression that specifies a set of strings. A regular expression is composed of (i) simple strings (ii) the empty or (ii) union, concatenation and Kleene closure of other regular expressions. To avoid parentheses it is assumed that the Kleene star has the highest priority, next concatenation and then alternation, however, most formalisms provides grouping operators to allow the definition of scope and operator precedence. Readers unfamiliar with the concept of regular expression matching are referred classical texts such as \cite{aho2007}. Section~\ref{Compiler Technology} Regular expression matching is commonly performed using a variety of publically available software tools. The most prominent, UNIX grep, Gnu grep, agrep, cgrep, nrgrep, and Perl regular expressions \cite{Abou-assaleh04surveyof}. Section~\ref{Methodology} describes the evaluation framework and Section~\ref{Experimental Results} presents a detailed performance analysis of our data parallel \bitstream{} techniques against Gnu grep, agrep, and nr-grep. Amongst these Gnu grep, agrep, and nrgrep are widely known and considered as the fastest regular expression matching tools in practice \cite{}. Of particular interest to this study are the performance oriented Gnu grep, agrep, and nrgrep. % Unix grep % Gnu grep % agrep % nrgrep Regular expresssion matching is an extensively studied problem with a multitude of algorithms and software tools developed to the demands of particular problem contexts. As such, we compare the performance of our parallel \bitstream{} techniques against various grep concentrate on the simpler case of reporting initial or final occurrence positions. Section~\ref{conclusion} concludes the paper. \section{Background} Historically, the origins of regular expression matching date back to automata theory and formal language theory developed by Kleene in the 1950s \cite{kleene1951representation}. and formal language theory developed by Kleene in the 1950s \cite{kleene1951}. In 1959, Dana and Scott demonstrated that \section{Parallel Bitwise Data Streams} \label{Parallel Bitwise Data Streams} \section{Compiler Technology} \label{Compiler Technology} \section{Methodology} \label{Methodology} %\input{methodology.tex} We compare the performance of our parallel \bitstream{} techniques against Gnu grep, agrep, and nr-grep. Given a regular expression R and a test T the regular expression matching problem finds all ending position of substrings in Q that matches a string in the language denoted by R. The behaviour of Gnu grep, agrep, and nr-grep are differ in that Gnu grep agrep nr-grep \section{Experimental Results}