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<title>Methodology — CodeCarbon 2.0.0 documentation</title>
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<p class="caption" role="heading"><span class="caption-text">Introduction</span></p>
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<li class="toctree-l1"><a class="reference internal" href="motivation.html">Motivation</a></li>
<li class="toctree-l1 current"><a class="current reference internal" href="#">Methodology</a><ul>
<li class="toctree-l2"><a class="reference internal" href="#carbon-intensity">Carbon Intensity</a></li>
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<section id="methodology">
<span id="id1"></span><h1>Methodology<a class="headerlink" href="#methodology" title="Permalink to this heading"></a></h1>
<p>Carbon dioxide (CO₂) emissions, expressed as kilograms of CO₂-equivalents [CO₂eq], are the product of two main factors :</p>
<div class="highlight-text notranslate"><div class="highlight"><pre><span></span>C = Carbon Intensity of the electricity consumed for computation: quantified as g of CO₂ emitted per kilowatt-hour of electricity.
P = Power Consumed by the computational infrastructure: quantified as kilowatt-hours.
</pre></div>
</div>
<p>Carbon dioxide emissions (CO₂eq) can then be calculated as <code class="docutils literal notranslate"><span class="pre">C</span> <span class="pre">*</span> <span class="pre">P</span></code></p>
<section id="carbon-intensity">
<h2>Carbon Intensity<a class="headerlink" href="#carbon-intensity" title="Permalink to this heading"></a></h2>
<p>Carbon Intensity of the consumed electricity is calculated as a weighted average of the emissions from the different
energy sources that are used to generate electricity, including fossil fuels and renewables. In this toolkit, the fossil fuels coal, petroleum, and natural gas are associated with specific carbon intensities: a known amount of carbon dioxide is emitted for each kilowatt-hour of electricity generated. Renewable or low-carbon fuels include solar power, hydroelectricity, biomass, geothermal, and more. The nearby energy grid contains a mixture of fossil fuels and low-carbon energy sources, called the Energy Mix. Based on the mix of energy sources in the local grid, this package calculates the Carbon Intensity of the electricity consumed.</p>
<a class="reference internal image-reference" href="_images/grid_energy_mix.png"><img alt="Grid Energy Mix" class="align-center" src="_images/grid_energy_mix.png" style="width: 350px; height: 300px;" /></a>
<p>When available, CodeCarbon uses global carbon intensity of electricity per cloud provider ( <a class="reference external" href="https://github.com/mlco2/codecarbon/blob/master/codecarbon/data/cloud/impact.csv">here</a> ) or per country ( <a class="reference external" href="https://github.com/mlco2/codecarbon/blob/master/codecarbon/data/private_infra/eu-carbon-intensity-electricity.csv">here</a> ).</p>
<p>If we don’t have the global carbon intensity or electricity of a country, but we have its electricity mix, we compute the carbon intensity of electricity using this table :</p>
<table class="docutils align-center" id="id5">
<caption><span class="caption-text">Carbon Intensity Across Energy Sources</span><a class="headerlink" href="#id5" title="Permalink to this table"></a></caption>
<colgroup>
<col style="width: 50%" />
<col style="width: 50%" />
</colgroup>
<thead>
<tr class="row-odd"><th class="head"><p>Energy Source</p></th>
<th class="head"><p>Carbon Intensity (kg/MWh)</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p>Coal</p></td>
<td><p>995</p></td>
</tr>
<tr class="row-odd"><td><p>Petroleum</p></td>
<td><p>816</p></td>
</tr>
<tr class="row-even"><td><p>Natural Gas</p></td>
<td><p>743</p></td>
</tr>
<tr class="row-odd"><td><p>Geothermal</p></td>
<td><p>38</p></td>
</tr>
<tr class="row-even"><td><p>Hydroelectricity</p></td>
<td><p>26</p></td>
</tr>
<tr class="row-odd"><td><p>Nuclear</p></td>
<td><p>29</p></td>
</tr>
<tr class="row-even"><td><p>Solar</p></td>
<td><p>48</p></td>
</tr>
<tr class="row-odd"><td><p>Wind</p></td>
<td><p>26</p></td>
</tr>
</tbody>
</table>
<dl class="simple">
<dt>Sources:</dt><dd><ul class="simple">
<li><p><a class="reference external" href="https://github.com/responsibleproblemsolving/energy-usage#conversion-to-co2">for fossil energies</a></p></li>
<li><p><a class="reference external" href="http://www.world-nuclear.org/uploadedFiles/org/WNA/Publications/Working_Group_Reports/comparison_of_lifecycle.pdf">for renewables energies</a></p></li>
</ul>
</dd>
</dl>
<p>Then, for example, if the Energy Mix of the Grid Electricity is 25% Coal, 35% Petroleum, 26% Natural Gas and 14% Nuclear:</p>
<div class="highlight-text notranslate"><div class="highlight"><pre><span></span>Net Carbon Intensity = 0.25 * 995 + 0.35 * 816 + 0.26 * 743 + 0.14 * 29 = 731.59 kgCO₂/kWh
</pre></div>
</div>
<p>If ever we have neither the global carbon intensity of a country nor it’s electricity mix, we apply a world avarage of 475 gCO2.eq/KWh ( <a class="reference external" href="https://www.iea.org/reports/global-energy-co2-status-report-2019/emissions">source</a> ).</p>
<p>As you can see, we try to be as accurate as possible in estimating carbon intensity of electricity. Still there is room for improvement and all contributions are welcome.</p>
</section>
<section id="power-usage">
<h2>Power Usage<a class="headerlink" href="#power-usage" title="Permalink to this heading"></a></h2>
<p>Power supply to the underlying hardware is tracked at frequent time intervals. This is a configurable parameter
<code class="docutils literal notranslate"><span class="pre">measure_power_secs</span></code>, with default value 15 seconds, that can be passed when instantiating the emissions tracker.</p>
<p>Currently, the package supports the following hardware infrastructure.</p>
<section id="gpu">
<h3>GPU<a class="headerlink" href="#gpu" title="Permalink to this heading"></a></h3>
<p>Tracks Nvidia GPUs poxer consumption using <code class="docutils literal notranslate"><span class="pre">pynvml</span></code> library (installed with the package).</p>
</section>
<section id="ram">
<h3>RAM<a class="headerlink" href="#ram" title="Permalink to this heading"></a></h3>
<p>CodeCarbon uses a 3 Watts for 8 BG ratio <a class="reference external" href="https://www.crucial.com/support/articles-faq-memory/how-much-power-does-memory-use">source</a> .
This mesure is not satisfying and if ever you have an idea how to enhance it please do not hesitate to contribute.</p>
</section>
<section id="cpu">
<h3>CPU<a class="headerlink" href="#cpu" title="Permalink to this heading"></a></h3>
<ul class="simple">
<li><p><strong>On Windows or Mac</strong></p></li>
</ul>
<p>Tracks Intel processors power consumption using the <code class="docutils literal notranslate"><span class="pre">Inter</span> <span class="pre">Power</span> <span class="pre">Gadget</span></code>. You need to install it yourself from this <a class="reference external" href="https://www.intel.com/content/www/us/en/developer/articles/tool/power-gadget.html">source</a> .</p>
<ul class="simple">
<li><p><strong>On Linux</strong></p></li>
</ul>
<p>Tracks Intel Processor power consumption from Inter RAPL files at <code class="docutils literal notranslate"><span class="pre">\sys\class\powercap\intel-rapl</span></code> ( <a class="reference external" href="https://web.eece.maine.edu/~vweaver/projects/rapl/">reference</a> ).
All CPUs listed in this directory will be tracked. <a class="reference external" href="https://github.com/mlco2/codecarbon/issues/156">Help us improve this and make it configurable</a>.</p>
<p><em>Note</em>: The Power Consumption will be tracked only if the RAPL files exist at the above mentioned path</p>
<p>If none of the tracking tools are available on a computing resource, CodeCarbon will be switched to a fall back mode:
It will first detect which CPU hardware is currently in use, and then map it to a data source listing 2000+ Intel and AMD CPUs and their corresponding thermal design powers (TDPs).
If the CPU is not found in the data source, a global constant will be applied. CodeCarbon assumes that 50% of the TDP will be the average power consumption to make this approximation.
We could not find any good resource showing statistical relationships between TDP and average power so we empirically tested that 50% is a decent approximation.</p>
<p>The net Power Used is the net power supply consumed during the compute time, measured as <code class="docutils literal notranslate"><span class="pre">kWh</span></code>.</p>
</section>
</section>
<section id="references">
<h2>References<a class="headerlink" href="#references" title="Permalink to this heading"></a></h2>
<p><a class="reference external" href="https://arxiv.org/pdf/1911.08354.pdf">Energy Usage Reports: Environmental awareness as part of algorithmic accountability</a></p>
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