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        <title>STXXL</title>
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    </head>
    <body>
        <h1>
            STXXL 
        </h1>
        <p style="margin-top: 1ex">
                <b>STXXL: Standard Template Library for Extra Large Data Sets.</b>
        </p>
        <table align="right">
            <tr>
                <td>
                        <script type="text/javascript" src="http://www.ohloh.net/p/11530/widgets/project_basic_stats.js">
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                        <img src="layer_diagram.png" align="right" alt="Grafik"/>
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        </table>
        <p>
            The core of <b>STXXL</b>
            is an implementation of the C++ <a href="http://en.wikipedia.org/wiki/Standard_Template_Library">standard template library STL</a>
            for external memory (out-of-core) computations, i.e., <b>STXXL</b>
            implements containers and algorithms that can process <b>huge volumes of data</b>
            that only fit on disks. While the closeness to the STL supports ease of use and compatibility with existing applications, another design priority is high performance. [<a href="http://algo2.iti.kit.edu/dementiev/stxxl/report/">more info</a>] 
        </p>
        <p style="padding-bottom: 0px;">
                    The key features of <b>STXXL</b>
                    are: 
        </p>
        <ul style="margin-left: 20px;">
                    <li>
                        Transparent support of parallel disks. The library provides implementations of basic <b>parallel disk</b>
                        algorithms. <b>STXXL</b>
                        is the only external memory algorithm library supporting parallel disks. 
                    </li>
                    <li>
                        The library is able to handle problems of <b>very large</b>
                        size (tested to up to dozens of terabytes). 
                    </li>
            <li>
                Improved utilization of computer resources.
                <b>STXXL</b>
                implementations of external memory algorithms and data structures benefit from overlapping of I/O and computation. 
            </li>
            <li>
                Small constant factors in I/O volume. A unique library feature called <b>"pipelining"</b>
                can save more than <b>half</b>
                the number of I/Os in many applications. 
            </li>
            <li>
                Shorter <b>development times</b>
                due to well known <b>STL-compatible</b>
                interfaces for external memory algorithms and data structures.
            </li>
            <li>
                STL algorithms can be directly applied to <b>STXXL</b>
                containers; 
                moreover, the I/O complexity of the algorithms remains optimal in most of the cases. 
                <br/>
                [<a href="http://algo2.iti.kit.edu/dementiev/stxxl/report/">more info</a>] 
            </li>
        </ul>
        <p>
            <b>Current contributors: </b><NAME>, <NAME> 
                <br/>
            <b>Past contributors: </b><NAME> (author), <NAME> 
        </p>
        <br/>
        <h2>
            Support 
        </h2>
        <p>
            Questions concerning use and development of the <b>STXXL</b><commit_msg>Mention parallel algorithms more prominently.<commit_after><!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
    <head>
        <meta http-equiv="Content-type" content="text/html; charset=iso-8859-1"/>
        <title>STXXL</title>
        <link href="stxxl.css" rel="stylesheet" type="text/css"/>
    </head>
    <body>
        <h1>
            STXXL 
        </h1>
        <p style="margin-top: 1ex">
                <b>STXXL: Standard Template Library for Extra Large Data Sets.</b>
        </p>
        <table align="right">
            <tr>
                <td>
                        <script type="text/javascript" src="http://www.ohloh.net/p/11530/widgets/project_basic_stats.js">
                        </script>
                </td>
                <td>
                        <img src="layer_diagram.png" align="right" alt="Grafik"/>
                </td>
            </tr>
        </table>
        <p>
            The core of <b>STXXL</b>
            is an implementation of the C++ <a href="http://en.wikipedia.org/wiki/Standard_Template_Library">standard template library STL</a>
            for external memory (out-of-core) computations, i.e., <b>STXXL</b>
            implements containers and algorithms that can process <b>huge volumes of data</b>
            that only fit on disks. While the closeness to the STL supports ease of use and compatibility with existing applications, another design priority is high performance. [<a href="http://algo2.iti.kit.edu/dementiev/stxxl/report/">more info</a>] 
        </p>
        <p style="padding-bottom: 0px;">
                    The key features of <b>STXXL</b>
                    are: 
        </p>
        <ul style="margin-left: 20px;">
                    <li>
                        Transparent support of parallel disks. The library provides implementations of basic <b>parallel disk</b>
                        algorithms. <b>STXXL</b>
                        is the only external memory algorithm library supporting parallel disks. 
                    </li>
                    <li>
                        The library is able to handle problems of <b>very large</b>
                        size (tested to up to dozens of terabytes). 
                    </li>
            <li>
                Improved utilization of computer resources.
                <b>STXXL</b>
                implementations of external memory algorithms and data structures benefit from overlapping of I/O and computation. 
            </li>
            <li>
                Small constant factors in I/O volume. A unique library feature called <b>"pipelining"</b>
                can save more than <b>half</b> the number of I/Os, by streaming data between algorithmic components, 
                instead of temporarily storing them on disk.  
                A development branch supports <b>asynchronous</b> execution of the algorithmic components, 
                enabling high-level task parallelism.  
            </li>
            <li>
                Shorter <b>development times</b>
                due to well known <b>STL-compatible</b>
                interfaces for external memory algorithms and data structures.
            </li>
            <li>
                STL algorithms can be directly applied to <b>STXXL</b>
                containers; 
                moreover, the I/O complexity of the algorithms remains optimal in most of the cases. 
                <br/>
                [<a href="http://algo2.iti.kit.edu/dementiev/stxxl/report/">more info</a>] 
            </li>
            <li>
                For internal computation, <b>parallel</b> algorithms from the MCSTL or the libstdc++ parallel mode are optionally utilized,
                making the algorithms inherently benefit from <b>multi-core</b> parallelism. 
            </li>
        </ul>
        <p>
            <b>Current contributors: </b><NAME>, <NAME> 
                <br/>
            <b>Past contributors: </b><NAME> (author), <NAME> 
        </p>
        <br/>
        <h2>
            Support 
        </h2>
        <p>
            Questions concerning use and development of the <b>STXXL</b>
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