<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1405-5546</journal-id>
<journal-title><![CDATA[Computación y Sistemas]]></journal-title>
<abbrev-journal-title><![CDATA[Comp. y Sist.]]></abbrev-journal-title>
<issn>1405-5546</issn>
<publisher>
<publisher-name><![CDATA[Instituto Politécnico Nacional, Centro de Investigación en Computación]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-55462006000400007</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Parallel Hardware/Software Architecture for the BWT and LZ77 Lossless Data Compression Algorithms]]></article-title>
<article-title xml:lang="es"><![CDATA[Arquitectura Hardware/Software Paralela para los Algoritmos de Compresión de Datos sin Pérdida BWT y LZ77]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Zuñiga Grajeda]]></surname>
<given-names><![CDATA[Virgilio]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Feregrino Uribe]]></surname>
<given-names><![CDATA[Claudia]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cumplido Parra]]></surname>
<given-names><![CDATA[Rene]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,National Institute for Astrophysics, Optics and Electronics  ]]></institution>
<addr-line><![CDATA[Tonantzintla Puebla]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2006</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2006</year>
</pub-date>
<volume>10</volume>
<numero>2</numero>
<fpage>172</fpage>
<lpage>188</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-55462006000400007&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-55462006000400007&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-55462006000400007&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Nowadays, the use of digital communication systems has increased in such a way that network bandwidth is affected. This problem can be solved by implementing data compression algorithms in communication devices to reduce the amount of data to be transmitted. However, the design of large hardware data compression models implies to consider an efficient use of the silicon area. This work proposes the conjunction of two different hardware lossless data compression approaches which share common hardware elements. The project also involves the design of a hardware/software architecture to exploit parallelism increasing execution speed while keeping flexibility. A custom coprocessor unit executes the compute-intense tasks of the Burrows-Wheeler Transform and the Lempel-Ziv lossless data compression schemes. This coprocessor unit is controlled by a SPARC V8 compatible general purpose microprocessor called LEON2.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Hoy en día, el uso de sistemas de comunicación digitales ha aumentado de tal forma que el ancho de banda en las redes resulta afectado. Este problema puede solucionarse implementando algoritmos de compresión de datos en dispositivos de comunicación reduciendo la cantidad de datos a transmitir. Sin embargo, el diseño de modelos complejos de compresión de datos en hardware implica considerar el uso eficiente de la superficie de silicio. Este trabajo propone la combinación de dos esquemas diferentes de compresión de datos sin pérdida que compartan elementos comunes. Este proyecto también trata el diseño de una arquitectura hardware/software que explote el paralelismo e incremente la velocidad de ejecución manteniendo su flexibilidad. Un coprocesador ejecuta las tareas computacionalmente intensas de los esquemas de compresión Burrows-Wheeler Transform y Lempel-Ziv. El coprocesador es controlado por un microprocesador de propósito general compatible con la arquitectura SPARC V8 llamado LEON2.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Data compression]]></kwd>
<kwd lng="en"><![CDATA[Burrows-Wheeler Transform]]></kwd>
<kwd lng="en"><![CDATA[Lempel-Ziv]]></kwd>
<kwd lng="en"><![CDATA[Coprocessor]]></kwd>
<kwd lng="en"><![CDATA[LEON2]]></kwd>
<kwd lng="es"><![CDATA[Compresión de Datos]]></kwd>
<kwd lng="es"><![CDATA[Transformada de Burrows-Wheeler]]></kwd>
<kwd lng="es"><![CDATA[Lempel-Ziv]]></kwd>
<kwd lng="es"><![CDATA[Coprocesador]]></kwd>
<kwd lng="es"><![CDATA[LEON2]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[ <p align="center"><font face="verdana" size="4"><b>Parallel Hardware/Software Architecture for the BWT and LZ77 Lossless Data Compression Algorithms</b></font></p>     <p align="center"><font face="verdana" size="2">&nbsp;</font></p>     <p align="center"><font face="verdana" size="3"><b><i>Arquitectura Hardware/Software Paralela para los Algoritmos de Compresi&oacute;n de Datos sin P&eacute;rdida BWT y LZ77</i></b></font></p>     <p align="center"><font face="verdana" size="2">&nbsp;</font></p>     <p align="center"><font face="verdana" size="2"><b>Virgilio Zu&ntilde;iga Grajeda, Claudia Feregrino Uribe and Rene Cumplido Parra</b></font></p>     <p align="justify"><font face="verdana" size="2">&nbsp;</font></p>     <p align="justify"><font face="verdana" size="2"><i>National Institute for Astrophysics, Optics and Electronics Luis Enrique Erro No. 1. Tonantzintla, Puebla, Mexico. Postal Code: 72840  <a href="mailto:virgilio@inaoep.mx">virgilio@inaoep.mx </a> ; <a href="mailto:cferegrino@inaoep.mx">cferegrino@inaoep.mx</a> ; <a href="mailto:rcumplido@inaoep.mx">rcumplido@inaoep.mx</a></i></font></p>     <p align="justify"><font face="verdana" size="2">&nbsp;</font></p>     <p align="justify"><font face="verdana" size="2">Article received on july 25, 2006    <br> Accepted on october 2, 2006</font></p>     ]]></body>
<body><![CDATA[<p align="justify"><font face="verdana" size="2">&nbsp;</font></p>     <p align="justify"><font face="verdana" size="2"><b>Abstract.</b></font></p>     <p align="justify"><font face="verdana" size="2">Nowadays, the use of digital communication systems has increased in such a way that network bandwidth is affected. This problem can be solved by implementing data compression algorithms in communication devices to reduce the amount of data to be transmitted. However, the design of large hardware data compression models implies to consider an efficient use of the silicon area. This work proposes the conjunction of two different hardware lossless data compression approaches which share common hardware elements. The project also involves the design of a hardware/software architecture to exploit parallelism increasing execution speed while keeping flexibility. A custom coprocessor unit executes the compute&#150;intense tasks of the Burrows&#150;Wheeler Transform and the Lempel&#150;Ziv lossless data compression schemes. This coprocessor unit is controlled by a SPARC V8 compatible general purpose microprocessor called LEON2. </font></p>     <p align="justify"><font face="verdana" size="2"><b>Keywords: </b>Data compression, Burrows&#150;Wheeler Transform, Lempel&#150;Ziv, Coprocessor, LEON2.</font></p>     <p align="justify"><font face="verdana" size="2">&nbsp;</font></p>     <p align="justify"><font face="verdana" size="2"><b>Resumen.</b></font></p>     <p align="justify"><font face="verdana" size="2">Hoy en d&iacute;a, el uso de sistemas de comunicaci&oacute;n digitales ha aumentado de tal forma que el ancho de banda en las redes resulta afectado. Este problema puede solucionarse implementando algoritmos de compresi&oacute;n de datos en dispositivos de comunicaci&oacute;n reduciendo la cantidad de datos a transmitir. Sin embargo, el dise&ntilde;o de modelos complejos de compresi&oacute;n de datos en hardware implica considerar el uso eficiente de la superficie de silicio. Este trabajo propone la combinaci&oacute;n de dos esquemas diferentes de compresi&oacute;n de datos sin p&eacute;rdida que compartan elementos comunes. Este proyecto tambi&eacute;n trata el dise&ntilde;o de una arquitectura hardware/software que explote el paralelismo e incremente la velocidad de ejecuci&oacute;n manteniendo su flexibilidad. Un coprocesador ejecuta las tareas computacionalmente intensas de los esquemas de compresi&oacute;n Burrows&#150;Wheeler Transform y Lempel&#150;Ziv. El coprocesador es controlado por un microprocesador de prop&oacute;sito general compatible con la arquitectura SPARC V8 llamado LEON2. </font></p>     <p align="justify"><font face="verdana" size="2"><b>Palabras clave: </b>Compresi&oacute;n de Datos, Transformada de Burrows&#150;Wheeler, Lempel&#150;Ziv, Coprocesador, LEON2.</font></p>     <p align="justify"><font face="verdana" size="2">&nbsp;</font></p>     <p align="justify"><font face="verdana" size="2"><a href="/pdf/cys/v10n2/v10n2a7.pdf" target="_blank">DESCARGAR ART&Iacute;CULO EN FORMATO PDF</a></font></p>     ]]></body>
<body><![CDATA[<p align="justify"><font face="verdana" size="2">&nbsp;</font></p>     <p align="justify"><font face="verdana" size="2"><b>Acknowledgments</b></font></p>     <p align="justify"><font face="verdana" size="2">The authors acknowledge the financial support from the Mexican National Council for Science and Technology (CONACyT), grant number 181512.</font></p>     <p align="justify"><font face="verdana" size="2">&nbsp;</font></p>     <p align="justify"><font face="verdana" size="2"><b>References</b></font></p>     <!-- ref --><p align="justify"><font face="verdana" size="2">1. <b>N. 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