Speaking of Power instead of Energy

Author: ArneTR

details.html

@@ -38,7 +38,7 @@ <h1 id="website-name" class="ui massive teal ribbon label"></h1>
                         <h2 style="
                 display: inline-block;
                 margin-bottom: 0px;
-                ">Rendering Energy</h2>
+                ">Rendering Power</h2>
                         <p>The CPU power consumption for rendering was <span id="rendering-power" class="ui label"></span></p>
                         <p>With a visit time of <span class="ui label measurement-duration"></span> this equates to <span id="rendering-energy" class="ui label"></span></p>
                         <p>If you have 10,000 people visiting your page per month this would consume <span id="rendering-energy-10k" class="ui label"></span> of energy</p>

methodology.html

@@ -30,15 +30,15 @@ <h2 class="ui image header">
                 <h1>How does it work?</h1>
                 <hr>
                 <p>All metrics are generated by making a measurement with our open source software the <a href="https://www.green-coding.io/products/green-metrics-tool" target='_blank' rel='noopener'>Green Metrics Tool</a></p>
-                <h3>Rendering Energy</h3>
-                <p>The rendering energy shown by WebNRG is the energy consumed by the CPU.</p>
+                <h3>Rendering Power</h3>
+                <p>The rendering power shown by WebNRG is the power drawn by the CPU only.</p>
                 <p>In order to get the energy of the page rendering we utilize an aptly configured dedicated on-premise server that can sample the <b>CPU energy</b> at a <b>2 ms interval</b>.</p>
                 <p>This data comes from <a href="https://sustainable-computing.io/archive/design/kepler-energy-sources/" target='_blank' rel='noopener'>RAPL</a>.</p>
                 <p>To isolate the rendering cost from startup of the browser and also from network latency we first download the website completely through a reverse proxy, caching everything local to the machine. Then we destroy the browser context and reload the page from the reverse proxy effectively only measuring the parsing and rendering of the webpage.</p>
                 <p>The benchmark contains loading the page, waiting for 5 seconds and then scrolling down until the end of the page is reached (or 40 seconds if pages have infinite scrolling).</p>
                 <p>To make the measurements even more reliable we tightly accuracy control our measurement machines. See more on this below.</p>
-                <h4>Rendering Energy Label</h4>
-                <p>To generate the categories from <b>A+ to F</b> we use the idle power consumption of our measurement machine as capture by the <i>Idle</i> phase in the Green Metrics Tool. We then take the lowest energy consuming page we could find (<a href="https://motherfuckingwebsite.com" target='_blank' rel='noopener'>motherfuckingwebsite.com</a>) as A+ and then <b>linearly increment steps by 25% </b>increase in rendering power. Everything above <i>2.5*Idle Power</i> is considered F.</p>
+                <h4>Rendering Power Label</h4>
+                <p>To generate the categories from <b>A+ to F</b> we use the idle power consumption of our measurement machine as capture by the <i>Idle</i> phase in the Green Metrics Tool. We then take the lowest power drawing page we could find (<a href="https://motherfuckingwebsite.com" target='_blank' rel='noopener'>motherfuckingwebsite.com</a>) as A+ and then <b>linearly increment steps by 25% </b>increase in rendering power. Everything above <i>2.5*Idle Power</i> is considered F.</p>
                 <p>The decision for <i>25%</i> was made because on our measurement system we see a 95p STDDEV of 0.2 W. 25% of the idle power consumption equals 2.5x this STDDEV which is a typical way of determining a range for a statistical relevant difference (outlier) between categories / observations.</p>
                 <hr>
                 <h3>Network Traffic and Carbon</h3>