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Initial commit with SimSo 0.7 (core only).
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  <div class="section" id="introduction">
<h1>Introduction<a class="headerlink" href="#introduction" title="Permalink to this headline"></a></h1>
<div class="section" id="what-is-simso">
<h2>What is SimSo?<a class="headerlink" href="#what-is-simso" title="Permalink to this headline"></a></h2>
<p>SimSo is a scheduling simulator for real-time multiprocessor architectures that takes into account some scheduling overheads (scheduling decisions, context switches) and the impact of caches through statistical models. Based on a Discrete-Event Simulator (SimPy), it allows quick simulations and a fast prototyping of scheduling policies using Python.</p>
<p>SimSo is an open source software, available under the <a class="reference external" href="licenses.html">CeCILL license</a>, a GPL compatible license.</p>
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<div class="section" id="download">
<h2>Download<a class="headerlink" href="#download" title="Permalink to this headline"></a></h2>
<p>You can find the last version of SimSo on the <a class="reference external" href="http://homepages.laas.fr/mcheramy/simso/">SimSo Website</a>.</p>
</div>
<div class="section" id="installation">
<h2>Installation<a class="headerlink" href="#installation" title="Permalink to this headline"></a></h2>
<p>SimSo is available for the main platforms and so is its source code. The archive containing the source code is more often updated and should be used when possible.</p>
<p>In order to install SimSo from the souce code, the dependences must be installed first. Then, type &#8220;python setup.py install&#8221; to install SimSo.</p>
<div class="section" id="dependencies">
<h3>Dependencies<a class="headerlink" href="#dependencies" title="Permalink to this headline"></a></h3>
<p>When using SimSo from the sources, the following softwares and librairies are required:</p>
<blockquote>
<div><ul class="simple">
<li>Python 2.7+</li>
<li>SimPy 2.3.1 (not compatible with SimPy 3)</li>
<li>NumPy 1.6+</li>
<li>PyQt4 4.9+</li>
</ul>
</div></blockquote>
<p>If you are using a binary, everything should be packed in the binary.</p>
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<div class="section" id="first-step">
<h2>First step<a class="headerlink" href="#first-step" title="Permalink to this headline"></a></h2>
<p>SimSo is provided with a graphical user interface that aims to be very easy to use. This is a good way to develop and test a scheduler. See <a class="reference external" href="write_scheduler.html">How to write a scheduling policy</a>.</p>
<p>It is also possible to use SimSo as a library. This allows in particular to run simulations in text mode with a maximum of flexibility.</p>
</div>
<div class="section" id="available-schedulers">
<h2>Available Schedulers<a class="headerlink" href="#available-schedulers" title="Permalink to this headline"></a></h2>
<p>Currently, the following schedulers are available:</p>
<p><strong>Uniprocessor schedulers</strong></p>
<blockquote>
<div><ul class="simple">
<li>Earliest Deadline First (EDF)</li>
<li>Rate Monotonic (RM)</li>
<li>Fixed Priority (FP)</li>
<li>Static-EDF (A DVFS EDF)</li>
<li>CC-EDF: Real-Time dynamic voltage scaling for low-power embedded operating systems by P. Pillai et al.</li>
</ul>
</div></blockquote>
<dl class="docutils">
<dt><strong>Uniprocessor schedulers adapted to multiprocessor</strong></dt>
<dd><ul class="first last simple">
<li>Global-EDF</li>
<li>Global-RM</li>
<li>Earliest Deadline Zero Laxity (EDZL)</li>
<li>Least Laxity First (LLF)</li>
<li>Modified Least Laxity First (MLLF): A Modified Least-Laxity-First Scheduling Algorithm for Real-Time Tasks by S.-H. Oh and S.-M. Yang.</li>
<li>PriD: Real-time scheduling on multiprocessors by J., Baruah, S., &amp; Funk, S.</li>
<li>EDF-US</li>
<li>G-FL: Fair lateness scheduling: Reducing maximum lateness in G-EDF-like scheduling by Erickson and Anderson.</li>
</ul>
</dd>
<dt><strong>Partitionned</strong></dt>
<dd><p class="first">Any uniprocessor scheduler using a partitionning algorithm. The following heuristics are provided:</p>
<ul class="last simple">
<li>First-Fit and Decreasing-First-Fit</li>
<li>Next-Fit and Decreasing-Next-Fit</li>
<li>Best-Fit and Decreasing-Best-Fit</li>
<li>Worst-Fit and Decreasing-Worst-Fit</li>
</ul>
</dd>
<dt><strong>PFair</strong></dt>
<dd><ul class="first last simple">
<li>Earliest Pseudo-Deadline First (EPDF)</li>
<li>PD2 and ER-PD2: Early-Release Fair Scheduling. In Proceedings of the Euromicro Conference on Real-Time Systems by J. H. Anderson et al.</li>
</ul>
</dd>
<dt><strong>DPFair</strong></dt>
<dd><ul class="first last simple">
<li>LLREF: An Optimal Real-Time Scheduling Algorithm for Multiprocessors by Cho et al.</li>
<li>LRE-TL:  An Optimal Multiprocessor Scheduling Algorithm for Sporadic Task Sets by S. Funk et al.</li>
<li>DP-WRAP: DP-FAIR: A Simple Model for Understanding Optimal Multiprocessor Scheduling by Levin et al.</li>
<li>BF: Multiple-resource periodic scheduling problem: how much fairness is necessary? by Zhu et al.</li>
<li>NVNLF: Work-Conversing Optimal Real-Time Scheduling on Multiprocessors by Funaoka et al.</li>
</ul>
</dd>
<dt><strong>Semi-partitionned</strong></dt>
<dd><ul class="first last simple">
<li>EKG:  Multiprocessor Scheduling with Few Preemptions by B. Andersson and E. Tovar.</li>
<li>EDHS: Semi-Partitioning Technique for Multiprocessor Real-Time Scheduling by Kato et al.</li>
</ul>
</dd>
<dt><strong>Other</strong></dt>
<dd><ul class="first last simple">
<li>RUN: Optimal Multiprocessor Real-Time Scheduling via Reduction to Uniprocessor by Regnier et al.</li>
<li>U-EDF: an Unfair but Optimal Multiprocessor Scheduling Algorithm for Sporadic Tasks by Nelissen et al.</li>
</ul>
</dd>
</dl>
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