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hvr/aeson-vs-json-ghc-7.2.2-report.html

Created December 23, 2011 10:35
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GHC-7.2 vs GHC-7.4 aeson/json performance
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aeson-vs-json-ghc-7.2.2-report.html
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<div id="wrap">
<div id="main" class="body">
<h1>criterion performance measurements (GHC-7.2.2/x86-64)</h1>
<h2>overview</h2>
<p><a href="#grokularation">want to understand this report?</a></p>
<div id="overview" class="ovchart" style="width:900px;height:100px;"></div>
<h2><a name="b0">decode/en/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde0" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time0" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.939085939579776e-3</span></td>
<td><span class="time">1.9658579618270925e-3</span></td>
<td><span class="citime">1.9949450284774805e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">1.3128462850415552e-4</span></td>
<td><span class="time">1.4358862065192113e-4</span></td>
<td><span class="citime">1.5243545347632802e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.6664573992316749</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b1">decode/en/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde1" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time1" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">9.821797826939396e-3</span></td>
<td><span class="time">9.864117124729923e-3</span></td>
<td><span class="citime">9.919833162480164e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">1.9760528782182595e-4</span></td>
<td><span class="time">2.461817110467368e-4</span></td>
<td><span class="citime">3.3489730215010026e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have moderate
(<span class="percent">0.18996575071145103</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b2">decode/jp/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde2" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time2" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">3.197669008427433e-3</span></td>
<td><span class="time">3.3174767286117584e-3</span></td>
<td><span class="citime">3.4809531957443263e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">5.405091039226964e-4</span></td>
<td><span class="time">6.975922964945093e-4</span></td>
<td><span class="citime">8.452634090504838e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.946810815426843</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b3">decode/jp/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde3" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time3" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">2.1161977270298764e-2</span></td>
<td><span class="time">2.18295898229416e-2</span></td>
<td><span class="citime">2.2445858934574885e-2</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">3.0305728748569183e-3</span></td>
<td><span class="time">3.299648052417885e-3</span></td>
<td><span class="citime">3.5177473265682927e-3</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9043368414274496</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b4">encode/en/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde4" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time4" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.4778222829635649e-3</span></td>
<td><span class="time">1.5743913442428624e-3</span></td>
<td><span class="citime">1.8160977155502354e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">1.0804495036570738e-5</span></td>
<td><span class="time">6.807781587569007e-4</span></td>
<td><span class="citime">1.2383442500084453e-3</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9891809610146962</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b5">encode/en/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde5" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time5" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.6924776822860753e-3</span></td>
<td><span class="time">1.7942490369613681e-3</span></td>
<td><span class="citime">2.0405449659164467e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">2.419005429924974e-4</span></td>
<td><span class="time">7.548605014823182e-4</span></td>
<td><span class="citime">1.3266633294081042e-3</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9891347881552265</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b6">encode/jp/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde6" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time6" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.5549816877182044e-3</span></td>
<td><span class="time">1.6153778821762115e-3</span></td>
<td><span class="citime">1.764992693119815e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">2.913901281179997e-4</span></td>
<td><span class="time">5.080955096679364e-4</span></td>
<td><span class="citime">8.129504706313891e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9784831950818133</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b7">encode/jp/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde7" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time7" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.4269008428390542e-3</span></td>
<td><span class="time">1.4895715505416904e-3</span></td>
<td><span class="citime">1.6091170102890057e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">2.5887964889836196e-4</span></td>
<td><span class="time">4.32386117634593e-4</span></td>
<td><span class="citime">6.368226328146871e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9782190512098128</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="grokularation">understanding this report</a></h2>
<p>In this report, each function benchmarked by criterion is assigned
a section of its own. In each section, we display two charts, each
with an <i>x</i> axis that represents measured execution time.
These charts are active; if you hover your mouse over data points
and annotations, you will see more details.</p>
<ul>
<li>The chart on the left is a
<a href="http://en.wikipedia.org/wiki/Kernel_density_estimation">kernel
density estimate</a> (also known as a KDE) of time
measurements. This graphs the probability of any given time
measurement occurring. A spike indicates that a measurement of a
particular time occurred; its height indicates how often that
measurement was repeated.</li>
<li>The chart on the right is the raw data from which the kernel
density estimate is built. Measurements are displayed on
the <i>y</i> axis in the order in which they occurred.</li>
</ul>
<p>Under the charts is a small table displaying the mean and standard
deviation of the measurements. We use a statistical technique
called
the <a href="http://en.wikipedia.org/wiki/Bootstrapping_(statistics)">bootstrap</a>
to provide confidence intervals on our estimates of these values.
The bootstrap-derived upper and lower bounds on the mean and
standard deviation let you see how accurate we believe those
estimates to be. (Hover the mouse over the table headers to see
the confidence levels.)</p>
<p>A noisy benchmarking environment can cause some or many
measurements to fall far from the mean. These outlying
measurements can have a significant inflationary effect on the
estimate of the standard deviation. We calculate and display an
estimate of the extent to which the standard deviation has been
inflated by outliers.</p>
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var units = $.timeUnits(mean);
var scale = units[0];
units = units[1];
mean *= scale;
kdetimes = $.scaleBy(scale, kdetimes);
var ts = $.scaleBy(scale, times);
var kq = $("#kde" + number);
var k = $.plot(kq,
[{ label: name + " time densities",
data: $.zip(kdetimes, kdepdf),
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{ xaxis: { tickFormatter: $.unitFormatter(units) },
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grid: { borderColor: "#777",
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var timepairs = new Array(ts.length);
for (var i = 0; i < ts.length; i++)
timepairs[i] = [ts[i],i];
$.plot($("#time" + number),
[{ label: name + " times",
data: timepairs }],
{ points: { show: true },
grid: { borderColor: "#777", hoverable: true },
xaxis: { min: kdetimes[0], max: kdetimes[kdetimes.length-1],
tickFormatter: $.unitFormatter(units) },
yaxis: { ticks: false },
});
$.addTooltip("#kde" + number, function(x,y) { return x + ' ' + units; });
$.addTooltip("#time" + number, function(x,y) { return x + ' ' + units; });
};
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mangulate(2, "decode/jp/aeson",
3.3174767286117584e-3,
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mangulate(3, "decode/jp/json",
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mangulate(4, "encode/en/aeson",
1.5743913442428624e-3,
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mangulate(5, "encode/en/json",
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mangulate(6, "encode/jp/aeson",
1.6153778821762115e-3,
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mangulate(7, "encode/jp/json",
1.4895715505416904e-3,
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<div class="footfirst">
<h2>colophon</h2>
<p>This report was created using the
<a href="http://hackage.haskell.org/package/criterion">criterion</a>
benchmark execution and performance analysis tool.</p>
<p>Criterion is developed and maintained
by <a href="http://www.serpentine.com/blog/">Bryan O'Sullivan</a>.</p>
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aeson-vs-json-ghc-7.4.1RC1-report.html
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<h1>criterion performance measurements (GHC-7.4.1RC1/x86_64)</h1>
<h2>overview</h2>
<p><a href="#grokularation">want to understand this report?</a></p>
<div id="overview" class="ovchart" style="width:900px;height:100px;"></div>
<h2><a name="b0">decode/en/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde0" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time0" class="timechart"
style="width:450px;height:278px;"></div></td>
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<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">2.007221284136177e-3</span></td>
<td><span class="time">2.0385256435722096e-3</span></td>
<td><span class="citime">2.0734754230827095e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">1.5578222331173145e-4</span></td>
<td><span class="time">1.7031513150606384e-4</span></td>
<td><span class="citime">1.8144463319342467e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.7277422896401989</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b1">decode/en/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde1" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time1" class="timechart"
style="width:450px;height:278px;"></div></td>
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</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">9.333433213457469e-3</span></td>
<td><span class="time">9.384285512194035e-3</span></td>
<td><span class="citime">9.445346894487734e-3</span></td>
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<tr>
<td>Standard deviation</td>
<td><span class="citime">2.3080022615494714e-4</span></td>
<td><span class="time">2.841447593209104e-4</span></td>
<td><span class="citime">3.8530290323161956e-4</span></td>
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</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have moderate
(<span class="percent">0.24847900876978565</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b2">decode/jp/aeson</a></h2>
<table width="100%">
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<th class="cibound"
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<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">3.363935055956244e-3</span></td>
<td><span class="time">3.4947171833366155e-3</span></td>
<td><span class="citime">3.6700382854789487e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">5.811657072360872e-4</span></td>
<td><span class="time">7.536815122538213e-4</span></td>
<td><span class="citime">9.106259466328861e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9469680950435837</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b3">decode/jp/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde3" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time3" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.695156485103071e-2</span></td>
<td><span class="time">1.7580679955706006e-2</span></td>
<td><span class="citime">1.8155504765734076e-2</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">2.8115368354603874e-3</span></td>
<td><span class="time">3.0726510215975354e-3</span></td>
<td><span class="citime">3.2476851377194788e-3</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9255758404211938</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b4">encode/en/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde4" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time4" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.970380845293403e-3</span></td>
<td><span class="time">2.0710840847343198e-3</span></td>
<td><span class="citime">2.323195042833687e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">1.1240405037132883e-5</span></td>
<td><span class="time">7.101201889022059e-4</span></td>
<td><span class="citime">1.289203975850973e-3</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9787235496691832</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b5">encode/en/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde5" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time5" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.411916318163276e-3</span></td>
<td><span class="time">1.5103808071464302e-3</span></td>
<td><span class="citime">1.762029233202338e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">4.653706487361002e-5</span></td>
<td><span class="time">7.053683354254399e-4</span></td>
<td><span class="citime">1.307599858592106e-3</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9892978475558789</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b6">encode/jp/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde6" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time6" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">2.104288640245795e-3</span></td>
<td><span class="time">2.1669307377189394e-3</span></td>
<td><span class="citime">2.3212686207145445e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">3.0208771558232276e-4</span></td>
<td><span class="time">5.241904135069803e-4</span></td>
<td><span class="citime">8.383365760830861e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9575392108471806</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b7">encode/jp/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde7" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time7" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.4282646801322687e-3</span></td>
<td><span class="time">1.4917317058891057e-3</span></td>
<td><span class="citime">1.6134372379630797e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">2.609729956827409e-4</span></td>
<td><span class="time">4.3827556390082655e-4</span></td>
<td><span class="citime">6.488960436676929e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9782615624103539</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="grokularation">understanding this report</a></h2>
<p>In this report, each function benchmarked by criterion is assigned
a section of its own. In each section, we display two charts, each
with an <i>x</i> axis that represents measured execution time.
These charts are active; if you hover your mouse over data points
and annotations, you will see more details.</p>
<ul>
<li>The chart on the left is a
<a href="http://en.wikipedia.org/wiki/Kernel_density_estimation">kernel
density estimate</a> (also known as a KDE) of time
measurements. This graphs the probability of any given time
measurement occurring. A spike indicates that a measurement of a
particular time occurred; its height indicates how often that
measurement was repeated.</li>
<li>The chart on the right is the raw data from which the kernel
density estimate is built. Measurements are displayed on
the <i>y</i> axis in the order in which they occurred.</li>
</ul>
<p>Under the charts is a small table displaying the mean and standard
deviation of the measurements. We use a statistical technique
called
the <a href="http://en.wikipedia.org/wiki/Bootstrapping_(statistics)">bootstrap</a>
to provide confidence intervals on our estimates of these values.
The bootstrap-derived upper and lower bounds on the mean and
standard deviation let you see how accurate we believe those
estimates to be. (Hover the mouse over the table headers to see
the confidence levels.)</p>
<p>A noisy benchmarking environment can cause some or many
measurements to fall far from the mean. These outlying
measurements can have a significant inflationary effect on the
estimate of the standard deviation. We calculate and display an
estimate of the extent to which the standard deviation has been
inflated by outliers.</p>
<script type="text/javascript">
$(function () {
function mangulate(number, name, mean, times, kdetimes, kdepdf) {
var meanSecs = mean;
var units = $.timeUnits(mean);
var scale = units[0];
units = units[1];
mean *= scale;
kdetimes = $.scaleBy(scale, kdetimes);
var ts = $.scaleBy(scale, times);
var kq = $("#kde" + number);
var k = $.plot(kq,
[{ label: name + " time densities",
data: $.zip(kdetimes, kdepdf),
}],
{ xaxis: { tickFormatter: $.unitFormatter(units) },
yaxis: { ticks: false },
grid: { borderColor: "#777",
hoverable: true, markings: [ { color: '#6fd3fb',
lineWidth: 1.5, xaxis: { from: mean, to: mean } } ] },
});
var o = k.pointOffset({ x: mean, y: 0});
kq.append('<div class="meanlegend" title="' + $.renderTime(meanSecs) +
'" style="position:absolute;left:' + (o.left + 4) +
'px;bottom:139px;">mean</div>');
var timepairs = new Array(ts.length);
for (var i = 0; i < ts.length; i++)
timepairs[i] = [ts[i],i];
$.plot($("#time" + number),
[{ label: name + " times",
data: timepairs }],
{ points: { show: true },
grid: { borderColor: "#777", hoverable: true },
xaxis: { min: kdetimes[0], max: kdetimes[kdetimes.length-1],
tickFormatter: $.unitFormatter(units) },
yaxis: { ticks: false },
});
$.addTooltip("#kde" + number, function(x,y) { return x + ' ' + units; });
$.addTooltip("#time" + number, function(x,y) { return x + ' ' + units; });
};
mangulate(0, "decode/en/aeson",
2.0385256435722096e-3,
[2.0269790317863226e-3,2.0298400547355414e-3,2.361957135424018e-3,1.9320884373039008e-3,1.9320884373039008e-3,2.2868552830070258e-3,1.9509235050529242e-3,1.9010940220206976e-3,2.25395351909101e-3,1.8870273258537055e-3,1.983110013231635e-3,2.2978225376456976e-3,1.9349494602531195e-3,1.9149222996085883e-3,2.240840497240424e-3,1.897040906175971e-3,1.9049087192863226e-3,2.3099818851798773e-3,1.930896344408393e-3,1.9127765323966742e-3,2.264920773729682e-3,1.913968625292182e-3,1.9027629520744086e-3,2.2417941715568305e-3,1.9018092777580023e-3,1.985971036180854e-3,2.2990146305412055e-3,1.913968625292182e-3,1.9130149509757758e-3,2.242032590135932e-3,1.9180217411369086e-3,1.9039550449699164e-3,2.3109355594962836e-3,1.9218364384025336e-3,1.9189754154533148e-3,2.2677817966789008e-3,1.9189754154533148e-3,1.8999019291251898e-3,2.2427478458732367e-3,1.8848815586417914e-3,1.980010571703315e-3,2.3059287693351508e-3,1.9227901127189398e-3,1.9158759739249945e-3,2.2401252415031195e-3,1.9108691837638617e-3,1.8989482548087836e-3,2.318803372606635e-3,1.9239822056144476e-3,1.9208827640861273e-3,2.2639670994132758e-3,1.9158759739249945e-3,1.9030013706535101e-3,2.256099286302924e-3,1.8829742100089789e-3,2.000037732347846e-3,2.2918620731681586e-3,1.9158759739249945e-3,1.910153928026557e-3,2.2499004032462836e-3,1.908008160814643e-3,1.8979945804923773e-3,2.3049750950187445e-3,1.9268432285636664e-3,1.9170680668205023e-3,2.2739806797355414e-3,1.9099155094474555e-3,1.9039550449699164e-3,2.2429862644523383e-3,1.8879810001701117e-3,1.98692471049726e-3,2.301875653490424e-3,1.9189754154533148e-3,1.919929089769721e-3,2.2379794742912055e-3,1.9149222996085883e-3,1.8929877903312445e-3,2.3168960239738226e-3,1.9189754154533148e-3,1.919929089769721e-3,2.267066540941596e-3,1.9149222996085883e-3,1.9010940220206976e-3,2.2549071934074164e-3,1.8808284427970648e-3,1.9938388492912055e-3,2.295915189012885e-3,1.9168296482414008e-3,1.9208827640861273e-3,2.2448936130851508e-3,1.9068160679191351e-3,1.894895138964057e-3,2.309028210863471e-3,1.9189754154533148e-3,1.9337573673576117e-3,2.258960309252143e-3,1.9158759739249945e-3,1.900855603441596e-3,2.2439399387687445e-3,1.8898883488029242e-3,],
[1.8327155735343695e-3,1.8372616714174587e-3,1.8418077693005482e-3,1.8463538671836374e-3,1.8508999650667267e-3,1.8554460629498161e-3,1.8599921608329054e-3,1.8645382587159948e-3,1.869084356599084e-3,1.8736304544821733e-3,1.8781765523652628e-3,1.882722650248352e-3,1.8872687481314412e-3,1.8918148460145307e-3,1.89636094389762e-3,1.9009070417807092e-3,1.9054531396637986e-3,1.9099992375468879e-3,1.9145453354299773e-3,1.9190914333130666e-3,1.9236375311961558e-3,1.9281836290792453e-3,1.9327297269623345e-3,1.9372758248454238e-3,1.9418219227285132e-3,1.9463680206116025e-3,1.9509141184946917e-3,1.955460216377781e-3,1.9600063142608706e-3,1.9645524121439596e-3,1.969098510027049e-3,1.9736446079101386e-3,1.9781907057932276e-3,1.982736803676317e-3,1.9872829015594065e-3,1.9918289994424955e-3,1.996375097325585e-3,2.0009211952086744e-3,2.0054672930917635e-3,2.010013390974853e-3,2.0145594888579424e-3,2.0191055867410314e-3,2.023651684624121e-3,2.0281977825072103e-3,2.0327438803902998e-3,2.037289978273389e-3,2.0418360761564783e-3,2.0463821740395677e-3,2.0509282719226567e-3,2.055474369805746e-3,2.0600204676888357e-3,2.0645665655719247e-3,2.069112663455014e-3,2.0736587613381036e-3,2.0782048592211926e-3,2.082750957104282e-3,2.0872970549873715e-3,2.0918431528704606e-3,2.09638925075355e-3,2.1009353486366395e-3,2.1054814465197285e-3,2.110027544402818e-3,2.1145736422859074e-3,2.1191197401689964e-3,2.123665838052086e-3,2.1282119359351754e-3,2.1327580338182644e-3,2.137304131701354e-3,2.1418502295844433e-3,2.1463963274675323e-3,2.150942425350622e-3,2.1554885232337112e-3,2.1600346211168007e-3,2.1645807189998897e-3,2.169126816882979e-3,2.1736729147660686e-3,2.1782190126491577e-3,2.182765110532247e-3,2.1873112084153366e-3,2.1918573062984256e-3,2.196403404181515e-3,2.2009495020646045e-3,2.2054955999476935e-3,2.210041697830783e-3,2.2145877957138725e-3,2.219133893596962e-3,2.223679991480051e-3,2.2282260893631404e-3,2.23277218724623e-3,2.237318285129319e-3,2.2418643830124083e-3,2.246410480895498e-3,2.250956578778587e-3,2.2555026766616763e-3,2.2600487745447657e-3,2.2645948724278548e-3,2.2691409703109442e-3,2.2736870681940337e-3,2.2782331660771227e-3,2.282779263960212e-3,2.2873253618433016e-3,2.2918714597263906e-3,2.29641755760948e-3,2.3009636554925696e-3,2.3055097533756586e-3,2.310055851258748e-3,2.3146019491418375e-3,2.3191480470249265e-3,2.323694144908016e-3,2.3282402427911054e-3,2.3327863406741945e-3,2.337332438557284e-3,2.3418785364403734e-3,2.3464246343234624e-3,2.350970732206552e-3,2.3555168300896413e-3,2.3600629279727304e-3,2.36460902585582e-3,2.3691551237389093e-3,2.3737012216219983e-3,2.3782473195050878e-3,2.382793417388177e-3,2.3873395152712667e-3,2.3918856131543557e-3,2.396431711037445e-3,2.4009778089205346e-3,2.405523906803624e-3,2.410070004686713e-3,],
[5.570788224583704e-6,1.221715872541054e-4,3.286594586777759e-3,5.793237019221248e-2,0.714290149253847,6.181364363175655,37.9622747877213,167.89687709213078,545.3848865483595,1335.452499986392,2554.8146233792195,4025.258934073436,5613.569445122841,7385.432177282509,9301.100008744508,11135.953001153686,13007.950614877202,15032.293526857702,16121.571146177896,14743.36866304299,11191.685294345663,7400.028414852435,4597.087340328745,2705.1019054907324,1489.0067009515953,890.3287344167417,656.838833095451,476.2641730052076,294.46423014315377,256.84186705713836,511.39519020194285,1091.8155339232683,1804.1647316875394,2269.883747552506,2248.933450687453,1859.175801015902,1380.5782863594593,957.2134984372593,595.657539791256,340.597550017296,303.119091588667,537.674142674456,905.239210098448,1088.3583131575574,900.4195491315454,510.61016402273873,198.39662150398667,52.81461916844916,9.633302677188674,1.2034553787023576,0.10333442777440018,5.804818479478395e-3,4.5548989644525955e-4,-1.80758803156663e-4,1.6547088873629417e-4,-1.4591660068714537e-4,1.2884820530757645e-4,-1.1381545602860868e-4,1.0052242927014956e-4,-8.870103930920483e-5,7.811436834650502e-5,-6.855483188713347e-5,5.984073332250955e-5,-5.181221854917431e-5,4.432710756021139e-5,-3.725695288760819e-5,3.0483262909732524e-5,-2.389398700965161e-5,1.7380156342142e-5,-1.0832579172681559e-5,4.138579016916275e-6,2.8213461163599293e-6,-1.0176943377210158e-5,1.8071625591886457e-5,-2.666572063771635e-5,3.6139083312380406e-5,-4.669211764561784e-5,5.854458173845847e-5,-7.185501841887302e-5,9.077626974401899e-5,3.757984663770871e-5,3.8816005530899296e-3,6.97702981447895e-2,0.9174112134385153,8.534029327092183,56.57107712259917,268.0355085446451,909.9872238361664,2221.970363379016,3940.133811962915,5204.005936691329,5422.503082288616,4937.150602860066,4399.667361678006,4022.2190461214473,3646.5101904372027,3062.8443617251132,2271.391372142115,1593.2218618397526,1386.40652006853,1699.7267530562256,2348.586058483709,3156.206593125552,3906.3219984136767,4267.0327550588945,4040.128836176528,3340.7454349158356,2404.4238183588805,1443.579591068013,678.3312304853179,236.40022040029723,59.59758965835807,15.163985227679559,27.668926701008747,99.30465294263563,255.3097043406643,450.18420555099226,543.8766600798904,450.1839279935842,255.3035930792133,99.19822038704001,26.407343104053673,4.816610133972844,0.6017753895458773,5.161228336553155e-2,2.965425262181913e-3,1.5563066955654855e-4,-7.925240227107735e-6,]);
mangulate(1, "decode/en/json",
9.384285512194035e-3,
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mangulate(2, "decode/jp/aeson",
3.4947171833366155e-3,
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mangulate(3, "decode/jp/json",
1.7580679955706006e-2,
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mangulate(4, "encode/en/aeson",
2.0710840847343198e-3,
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mangulate(5, "encode/en/json",
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mangulate(6, "encode/jp/aeson",
2.1669307377189394e-3,
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mangulate(7, "encode/jp/json",
1.4917317058891057e-3,
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var benches = ["decode/en/aeson","decode/en/json","decode/jp/aeson","decode/jp/json","encode/en/aeson","encode/en/json","encode/jp/aeson","encode/jp/json",];
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<div id="footer">
<div class="body">
<div class="footfirst">
<h2>colophon</h2>
<p>This report was created using the
<a href="http://hackage.haskell.org/package/criterion">criterion</a>
benchmark execution and performance analysis tool.</p>
<p>Criterion is developed and maintained
by <a href="http://www.serpentine.com/blog/">Bryan O'Sullivan</a>.</p>
</div>
</div>
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</body>
</html>
Raw
aeson-vs-json-ghc-report.txt
GHC-7.2.2
=========
warming up
estimating clock resolution...
mean is 2.441854 us (320001 iterations)
found 2174 outliers among 319999 samples (0.7%)
1675 (0.5%) high severe
estimating cost of a clock call...
mean is 55.81076 ns (14 iterations)
found 1 outliers among 14 samples (7.1%)
1 (7.1%) high mild
benchmarking decode/en/aeson
mean: 1.965858 ms, lb 1.939086 ms, ub 1.994945 ms, ci 0.950
std dev: 143.5886 us, lb 131.2846 us, ub 152.4355 us, ci 0.950
variance introduced by outliers: 66.646%
variance is severely inflated by outliers
benchmarking decode/en/json
mean: 9.864117 ms, lb 9.821798 ms, ub 9.919833 ms, ci 0.950
std dev: 246.1817 us, lb 197.6053 us, ub 334.8973 us, ci 0.950
found 2 outliers among 100 samples (2.0%)
2 (2.0%) high mild
variance introduced by outliers: 18.997%
variance is moderately inflated by outliers
benchmarking decode/jp/aeson
mean: 3.317477 ms, lb 3.197669 ms, ub 3.480953 ms, ci 0.950
std dev: 697.5923 us, lb 540.5091 us, ub 845.2634 us, ci 0.950
found 14 outliers among 100 samples (14.0%)
13 (13.0%) high severe
variance introduced by outliers: 94.681%
variance is severely inflated by outliers
benchmarking decode/jp/json
mean: 21.82959 ms, lb 21.16198 ms, ub 22.44586 ms, ci 0.950
std dev: 3.299648 ms, lb 3.030573 ms, ub 3.517747 ms, ci 0.950
variance introduced by outliers: 90.434%
variance is severely inflated by outliers
benchmarking encode/en/aeson
mean: 1.574391 ms, lb 1.477822 ms, ub 1.816098 ms, ci 0.950
std dev: 680.7782 us, lb 10.80450 us, ub 1.238344 ms, ci 0.950
found 6 outliers among 100 samples (6.0%)
3 (3.0%) high mild
3 (3.0%) high severe
variance introduced by outliers: 98.918%
variance is severely inflated by outliers
benchmarking encode/en/json
mean: 1.794249 ms, lb 1.692478 ms, ub 2.040545 ms, ci 0.950
std dev: 754.8605 us, lb 241.9005 us, ub 1.326663 ms, ci 0.950
found 3 outliers among 100 samples (3.0%)
3 (3.0%) high severe
variance introduced by outliers: 98.913%
variance is severely inflated by outliers
benchmarking encode/jp/aeson
mean: 1.615378 ms, lb 1.554982 ms, ub 1.764993 ms, ci 0.950
std dev: 508.0955 us, lb 291.3901 us, ub 812.9505 us, ci 0.950
found 4 outliers among 100 samples (4.0%)
3 (3.0%) high severe
variance introduced by outliers: 97.848%
variance is severely inflated by outliers
benchmarking encode/jp/json
mean: 1.489572 ms, lb 1.426901 ms, ub 1.609117 ms, ci 0.950
std dev: 432.3861 us, lb 258.8796 us, ub 636.8226 us, ci 0.950
found 11 outliers among 100 samples (11.0%)
2 (2.0%) high mild
9 (9.0%) high severe
variance introduced by outliers: 97.822%
variance is severely inflated by outliers
---------------------------------------------------------------------------------
GHC-7.4.1RC1
============
warming up
estimating clock resolution...
mean is 1.714099 us (320001 iterations)
found 1769 outliers among 319999 samples (0.6%)
1246 (0.4%) high severe
estimating cost of a clock call...
mean is 55.72774 ns (10 iterations)
found 1 outliers among 10 samples (10.0%)
1 (10.0%) high mild
benchmarking decode/en/aeson
mean: 2.038526 ms, lb 2.007221 ms, ub 2.073475 ms, ci 0.950
std dev: 170.3151 us, lb 155.7822 us, ub 181.4446 us, ci 0.950
variance introduced by outliers: 72.774%
variance is severely inflated by outliers
benchmarking decode/en/json
mean: 9.384286 ms, lb 9.333433 ms, ub 9.445347 ms, ci 0.950
std dev: 284.1448 us, lb 230.8002 us, ub 385.3029 us, ci 0.950
found 7 outliers among 100 samples (7.0%)
3 (3.0%) low mild
3 (3.0%) high mild
1 (1.0%) high severe
variance introduced by outliers: 24.848%
variance is moderately inflated by outliers
benchmarking decode/jp/aeson
mean: 3.494717 ms, lb 3.363935 ms, ub 3.670038 ms, ci 0.950
std dev: 753.6815 us, lb 581.1657 us, ub 910.6259 us, ci 0.950
found 19 outliers among 100 samples (19.0%)
6 (6.0%) low mild
13 (13.0%) high severe
variance introduced by outliers: 94.697%
variance is severely inflated by outliers
benchmarking decode/jp/json
mean: 17.58068 ms, lb 16.95156 ms, ub 18.15550 ms, ci 0.950
std dev: 3.072651 ms, lb 2.811537 ms, ub 3.247685 ms, ci 0.950
variance introduced by outliers: 92.558%
variance is severely inflated by outliers
benchmarking encode/en/aeson
mean: 2.071084 ms, lb 1.970381 ms, ub 2.323195 ms, ci 0.950
std dev: 710.1202 us, lb 11.24041 us, ub 1.289204 ms, ci 0.950
found 8 outliers among 100 samples (8.0%)
6 (6.0%) high mild
2 (2.0%) high severe
variance introduced by outliers: 97.872%
variance is severely inflated by outliers
benchmarking encode/en/json
mean: 1.510381 ms, lb 1.411916 ms, ub 1.762029 ms, ci 0.950
std dev: 705.3683 us, lb 46.53706 us, ub 1.307600 ms, ci 0.950
found 7 outliers among 100 samples (7.0%)
2 (2.0%) high mild
5 (5.0%) high severe
variance introduced by outliers: 98.930%
variance is severely inflated by outliers
benchmarking encode/jp/aeson
mean: 2.166931 ms, lb 2.104289 ms, ub 2.321269 ms, ci 0.950
std dev: 524.1904 us, lb 302.0877 us, ub 838.3366 us, ci 0.950
found 6 outliers among 100 samples (6.0%)
6 (6.0%) high severe
variance introduced by outliers: 95.754%
variance is severely inflated by outliers
benchmarking encode/jp/json
mean: 1.491732 ms, lb 1.428265 ms, ub 1.613437 ms, ci 0.950
std dev: 438.2756 us, lb 260.9730 us, ub 648.8960 us, ci 0.950
found 12 outliers among 100 samples (12.0%)
4 (4.0%) high mild
8 (8.0%) high severe
variance introduced by outliers: 97.826%
variance is severely inflated by outliers
Raw
aeson5-vs-json-ghc-7.2.2-report.html
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<h1>criterion performance measurements</h1>
<h2>overview</h2>
<p><a href="#grokularation">want to understand this report?</a></p>
<div id="overview" class="ovchart" style="width:900px;height:100px;"></div>
<h2><a name="b0">decode/en/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde0" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time0" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.9661993628101674e-3</span></td>
<td><span class="time">1.994142020280871e-3</span></td>
<td><span class="citime">2.025780165727648e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">1.3914539075750776e-4</span></td>
<td><span class="time">1.5246609974016803e-4</span></td>
<td><span class="citime">1.6538109263435855e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.6869027024340345</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b1">decode/en/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde1" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time1" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">9.850484812791856e-3</span></td>
<td><span class="time">9.893478835161245e-3</span></td>
<td><span class="citime">9.953546011980091e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">1.9788173067552812e-4</span></td>
<td><span class="time">2.5733009967704017e-4</span></td>
<td><span class="citime">3.636170113891002e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have moderate
(<span class="percent">0.19981466079269555</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b2">decode/jp/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde2" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time2" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">3.2315153723316533e-3</span></td>
<td><span class="time">3.356849635179554e-3</span></td>
<td><span class="citime">3.5270971899586047e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">5.616267489716673e-4</span></td>
<td><span class="time">7.264792994452522e-4</span></td>
<td><span class="citime">8.793150547519892e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9469891818519076</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b3">decode/jp/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde3" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time3" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">2.0813018763597518e-2</span></td>
<td><span class="time">2.148062654786877e-2</span></td>
<td><span class="citime">2.2096006358202018e-2</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">3.010308012205435e-3</span></td>
<td><span class="time">3.279645060699455e-3</span></td>
<td><span class="citime">3.4933572839038695e-3</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9044493606449342</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b4">encode/en/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde4" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time4" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.3211817389088018e-3</span></td>
<td><span class="time">1.322831595476184e-3</span></td>
<td><span class="citime">1.3248653059559211e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">7.817801177463099e-6</span></td>
<td><span class="time">9.355428668127622e-6</span></td>
<td><span class="citime">1.1599176056477865e-5</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have no
(<span class="percent">9.899999999999829e-3</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b5">encode/en/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde5" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time5" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.441254103715931e-3</span></td>
<td><span class="time">1.536831343706165e-3</span></td>
<td><span class="citime">1.7773337011890748e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">3.8893921580562794e-5</span></td>
<td><span class="time">6.782761967269643e-4</span></td>
<td><span class="citime">1.2439623826030837e-3</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.989213806079108</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b6">encode/jp/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde6" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time6" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.365811312730823e-3</span></td>
<td><span class="time">1.3673371916370736e-3</span></td>
<td><span class="citime">1.3700050955372193e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">6.816938389949421e-6</span></td>
<td><span class="time">1.0093913295380896e-5</span></td>
<td><span class="citime">1.8535077577860197e-5</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have no
(<span class="percent">9.900000000000153e-3</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b7">encode/jp/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde7" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time7" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.458034003313099e-3</span></td>
<td><span class="time">1.5230888968067518e-3</span></td>
<td><span class="citime">1.6490740423755982e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">2.631184176147466e-4</span></td>
<td><span class="time">4.485902794030462e-4</span></td>
<td><span class="citime">6.792339643740553e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9782700921689556</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="grokularation">understanding this report</a></h2>
<p>In this report, each function benchmarked by criterion is assigned
a section of its own. In each section, we display two charts, each
with an <i>x</i> axis that represents measured execution time.
These charts are active; if you hover your mouse over data points
and annotations, you will see more details.</p>
<ul>
<li>The chart on the left is a
<a href="http://en.wikipedia.org/wiki/Kernel_density_estimation">kernel
density estimate</a> (also known as a KDE) of time
measurements. This graphs the probability of any given time
measurement occurring. A spike indicates that a measurement of a
particular time occurred; its height indicates how often that
measurement was repeated.</li>
<li>The chart on the right is the raw data from which the kernel
density estimate is built. Measurements are displayed on
the <i>y</i> axis in the order in which they occurred.</li>
</ul>
<p>Under the charts is a small table displaying the mean and standard
deviation of the measurements. We use a statistical technique
called
the <a href="http://en.wikipedia.org/wiki/Bootstrapping_(statistics)">bootstrap</a>
to provide confidence intervals on our estimates of these values.
The bootstrap-derived upper and lower bounds on the mean and
standard deviation let you see how accurate we believe those
estimates to be. (Hover the mouse over the table headers to see
the confidence levels.)</p>
<p>A noisy benchmarking environment can cause some or many
measurements to fall far from the mean. These outlying
measurements can have a significant inflationary effect on the
estimate of the standard deviation. We calculate and display an
estimate of the extent to which the standard deviation has been
inflated by outliers.</p>
<script type="text/javascript">
$(function () {
function mangulate(number, name, mean, times, kdetimes, kdepdf) {
var meanSecs = mean;
var units = $.timeUnits(mean);
var scale = units[0];
units = units[1];
mean *= scale;
kdetimes = $.scaleBy(scale, kdetimes);
var ts = $.scaleBy(scale, times);
var kq = $("#kde" + number);
var k = $.plot(kq,
[{ label: name + " time densities",
data: $.zip(kdetimes, kdepdf),
}],
{ xaxis: { tickFormatter: $.unitFormatter(units) },
yaxis: { ticks: false },
grid: { borderColor: "#777",
hoverable: true, markings: [ { color: '#6fd3fb',
lineWidth: 1.5, xaxis: { from: mean, to: mean } } ] },
});
var o = k.pointOffset({ x: mean, y: 0});
kq.append('<div class="meanlegend" title="' + $.renderTime(meanSecs) +
'" style="position:absolute;left:' + (o.left + 4) +
'px;bottom:139px;">mean</div>');
var timepairs = new Array(ts.length);
for (var i = 0; i < ts.length; i++)
timepairs[i] = [ts[i],i];
$.plot($("#time" + number),
[{ label: name + " times",
data: timepairs }],
{ points: { show: true },
grid: { borderColor: "#777", hoverable: true },
xaxis: { min: kdetimes[0], max: kdetimes[kdetimes.length-1],
tickFormatter: $.unitFormatter(units) },
yaxis: { ticks: false },
});
$.addTooltip("#kde" + number, function(x,y) { return x + ' ' + units; });
$.addTooltip("#time" + number, function(x,y) { return x + ' ' + units; });
};
mangulate(0, "decode/en/aeson",
1.994142020280871e-3,
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mangulate(2, "decode/jp/aeson",
3.356849635179554e-3,
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mangulate(3, "decode/jp/json",
2.148062654786877e-2,
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mangulate(4, "encode/en/aeson",
1.322831595476184e-3,
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mangulate(6, "encode/jp/aeson",
1.3673371916370736e-3,
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mangulate(7, "encode/jp/json",
1.5230888968067518e-3,
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var benches = ["decode/en/aeson","decode/en/json","decode/jp/aeson","decode/jp/json","encode/en/aeson","encode/en/json","encode/jp/aeson","encode/jp/json",];
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<div id="footer">
<div class="body">
<div class="footfirst">
<h2>colophon</h2>
<p>This report was created using the
<a href="http://hackage.haskell.org/package/criterion">criterion</a>
benchmark execution and performance analysis tool.</p>
<p>Criterion is developed and maintained
by <a href="http://www.serpentine.com/blog/">Bryan O'Sullivan</a>.</p>
</div>
</div>
</div>
</body>
</html>
Raw
aeson5-vs-json-ghc-7.2.2-report.txt
warming up
estimating clock resolution...
mean is 2.385651 us (320001 iterations)
found 2156 outliers among 319999 samples (0.7%)
1675 (0.5%) high severe
estimating cost of a clock call...
mean is 55.34834 ns (14 iterations)
benchmarking decode/en/aeson
mean: 1.994142 ms, lb 1.966199 ms, ub 2.025780 ms, ci 0.950
std dev: 152.4661 us, lb 139.1454 us, ub 165.3811 us, ci 0.950
variance introduced by outliers: 68.690%
variance is severely inflated by outliers
benchmarking decode/en/json
mean: 9.893479 ms, lb 9.850485 ms, ub 9.953546 ms, ci 0.950
std dev: 257.3301 us, lb 197.8817 us, ub 363.6170 us, ci 0.950
found 3 outliers among 100 samples (3.0%)
2 (2.0%) high mild
1 (1.0%) high severe
variance introduced by outliers: 19.981%
variance is moderately inflated by outliers
benchmarking decode/jp/aeson
mean: 3.356850 ms, lb 3.231515 ms, ub 3.527097 ms, ci 0.950
std dev: 726.4793 us, lb 561.6267 us, ub 879.3151 us, ci 0.950
found 14 outliers among 100 samples (14.0%)
13 (13.0%) high severe
variance introduced by outliers: 94.699%
variance is severely inflated by outliers
benchmarking decode/jp/json
mean: 21.48063 ms, lb 20.81302 ms, ub 22.09601 ms, ci 0.950
std dev: 3.279645 ms, lb 3.010308 ms, ub 3.493357 ms, ci 0.950
variance introduced by outliers: 90.445%
variance is severely inflated by outliers
benchmarking encode/en/aeson
mean: 1.322832 ms, lb 1.321182 ms, ub 1.324865 ms, ci 0.950
std dev: 9.355429 us, lb 7.817801 us, ub 11.59918 us, ci 0.950
benchmarking encode/en/json
mean: 1.536831 ms, lb 1.441254 ms, ub 1.777334 ms, ci 0.950
std dev: 678.2762 us, lb 38.89392 us, ub 1.243962 ms, ci 0.950
found 6 outliers among 100 samples (6.0%)
2 (2.0%) high mild
4 (4.0%) high severe
variance introduced by outliers: 98.921%
variance is severely inflated by outliers
benchmarking encode/jp/aeson
mean: 1.367337 ms, lb 1.365811 ms, ub 1.370005 ms, ci 0.950
std dev: 10.09391 us, lb 6.816938 us, ub 18.53508 us, ci 0.950
benchmarking encode/jp/json
mean: 1.523089 ms, lb 1.458034 ms, ub 1.649074 ms, ci 0.950
std dev: 448.5903 us, lb 263.1184 us, ub 679.2340 us, ci 0.950
found 8 outliers among 100 samples (8.0%)
2 (2.0%) high mild
6 (6.0%) high severe
variance introduced by outliers: 97.827%
variance is severely inflated by outliers
Raw
aeson5-vs-json-ghc-7.4.1RC1-report.html
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<h1>criterion performance measurements</h1>
<h2>overview</h2>
<p><a href="#grokularation">want to understand this report?</a></p>
<div id="overview" class="ovchart" style="width:900px;height:100px;"></div>
<h2><a name="b0">decode/en/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde0" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time0" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">2.0026225218041367e-3</span></td>
<td><span class="time">2.0304721960289905e-3</span></td>
<td><span class="citime">2.061242497847839e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">1.373712733174556e-4</span></td>
<td><span class="time">1.4996462340527813e-4</span></td>
<td><span class="citime">1.592207411359323e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.676362503289399</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b1">decode/en/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde1" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time1" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">9.103514588759708e-3</span></td>
<td><span class="time">9.152841008590025e-3</span></td>
<td><span class="citime">9.216937459395683e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">2.227967422247683e-4</span></td>
<td><span class="time">2.857160217505227e-4</span></td>
<td><span class="citime">4.0221733249387717e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have moderate
(<span class="percent">0.267428742084142</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b2">decode/jp/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde2" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time2" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">3.357750810073181e-3</span></td>
<td><span class="time">3.477684892104431e-3</span></td>
<td><span class="citime">3.6408561834557485e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">5.408811806866654e-4</span></td>
<td><span class="time">6.987107482405236e-4</span></td>
<td><span class="citime">8.471169976040098e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9465065635616907</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b3">decode/jp/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde3" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time3" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.644129220335321e-2</span></td>
<td><span class="time">1.704663697569208e-2</span></td>
<td><span class="citime">1.760640565244989e-2</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">2.7443530612696228e-3</span></td>
<td><span class="time">2.983146835297758e-3</span></td>
<td><span class="citime">3.173373191403144e-3</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9255872015995154</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b4">encode/en/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde4" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time4" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.3566416868432004e-3</span></td>
<td><span class="time">1.3580841192467653e-3</span></td>
<td><span class="citime">1.359898484633728e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">6.785756682640039e-6</span></td>
<td><span class="time">8.251785038149742e-6</span></td>
<td><span class="citime">1.0538103375717323e-5</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have no
(<span class="percent">9.899999999999883e-3</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b5">encode/en/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde5" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time5" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.4339083799584347e-3</span></td>
<td><span class="time">1.5317792066796257e-3</span></td>
<td><span class="citime">1.770829595015808e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">4.431903255346626e-4</span></td>
<td><span class="time">7.897009286326246e-4</span></td>
<td><span class="citime">1.2720851643369614e-3</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9894238209575761</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b6">encode/jp/aeson</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde6" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time6" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.5008229383690795e-3</span></td>
<td><span class="time">1.5021914610131224e-3</span></td>
<td><span class="citime">1.5046471723778685e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">5.9128293153193095e-6</span></td>
<td><span class="time">9.111995409129009e-6</span></td>
<td><span class="citime">1.7065080285640153e-5</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have no
(<span class="percent">9.900000000000136e-3</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="b7">encode/jp/json</a></h2>
<table width="100%">
<tbody>
<tr>
<td><div id="kde7" class="kdechart"
style="width:450px;height:278px;"></div></td>
<td><div id="time7" class="timechart"
style="width:450px;height:278px;"></div></td>
</tr>
</tbody>
</table>
<table>
<thead class="analysis">
<th></th>
<th class="cibound"
title="0.95 confidence level">lower bound</th>
<th>estimate</th>
<th class="cibound"
title="0.95 confidence level">upper bound</th>
</thead>
<tbody>
<tr>
<td>Mean execution time</td>
<td><span class="citime">1.4147943624718625e-3</span></td>
<td><span class="time">1.4769715437157583e-3</span></td>
<td><span class="citime">1.5969199308617547e-3</span></td>
</tr>
<tr>
<td>Standard deviation</td>
<td><span class="citime">2.53850180471426e-4</span></td>
<td><span class="time">4.2974414868750466e-4</span></td>
<td><span class="citime">6.459034328177269e-4</span></td>
</tr>
</tbody>
</table>
<span class="outliers">
<p>Outlying measurements have severe
(<span class="percent">0.9782274581851318</span>%)
effect on estimated standard deviation.</p>
</span>
<h2><a name="grokularation">understanding this report</a></h2>
<p>In this report, each function benchmarked by criterion is assigned
a section of its own. In each section, we display two charts, each
with an <i>x</i> axis that represents measured execution time.
These charts are active; if you hover your mouse over data points
and annotations, you will see more details.</p>
<ul>
<li>The chart on the left is a
<a href="http://en.wikipedia.org/wiki/Kernel_density_estimation">kernel
density estimate</a> (also known as a KDE) of time
measurements. This graphs the probability of any given time
measurement occurring. A spike indicates that a measurement of a
particular time occurred; its height indicates how often that
measurement was repeated.</li>
<li>The chart on the right is the raw data from which the kernel
density estimate is built. Measurements are displayed on
the <i>y</i> axis in the order in which they occurred.</li>
</ul>
<p>Under the charts is a small table displaying the mean and standard
deviation of the measurements. We use a statistical technique
called
the <a href="http://en.wikipedia.org/wiki/Bootstrapping_(statistics)">bootstrap</a>
to provide confidence intervals on our estimates of these values.
The bootstrap-derived upper and lower bounds on the mean and
standard deviation let you see how accurate we believe those
estimates to be. (Hover the mouse over the table headers to see
the confidence levels.)</p>
<p>A noisy benchmarking environment can cause some or many
measurements to fall far from the mean. These outlying
measurements can have a significant inflationary effect on the
estimate of the standard deviation. We calculate and display an
estimate of the extent to which the standard deviation has been
inflated by outliers.</p>
<script type="text/javascript">
$(function () {
function mangulate(number, name, mean, times, kdetimes, kdepdf) {
var meanSecs = mean;
var units = $.timeUnits(mean);
var scale = units[0];
units = units[1];
mean *= scale;
kdetimes = $.scaleBy(scale, kdetimes);
var ts = $.scaleBy(scale, times);
var kq = $("#kde" + number);
var k = $.plot(kq,
[{ label: name + " time densities",
data: $.zip(kdetimes, kdepdf),
}],
{ xaxis: { tickFormatter: $.unitFormatter(units) },
yaxis: { ticks: false },
grid: { borderColor: "#777",
hoverable: true, markings: [ { color: '#6fd3fb',
lineWidth: 1.5, xaxis: { from: mean, to: mean } } ] },
});
var o = k.pointOffset({ x: mean, y: 0});
kq.append('<div class="meanlegend" title="' + $.renderTime(meanSecs) +
'" style="position:absolute;left:' + (o.left + 4) +
'px;bottom:139px;">mean</div>');
var timepairs = new Array(ts.length);
for (var i = 0; i < ts.length; i++)
timepairs[i] = [ts[i],i];
$.plot($("#time" + number),
[{ label: name + " times",
data: timepairs }],
{ points: { show: true },
grid: { borderColor: "#777", hoverable: true },
xaxis: { min: kdetimes[0], max: kdetimes[kdetimes.length-1],
tickFormatter: $.unitFormatter(units) },
yaxis: { ticks: false },
});
$.addTooltip("#kde" + number, function(x,y) { return x + ' ' + units; });
$.addTooltip("#time" + number, function(x,y) { return x + ' ' + units; });
};
mangulate(0, "decode/en/aeson",
2.0304721960289905e-3,
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mangulate(1, "decode/en/json",
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mangulate(2, "decode/jp/aeson",
3.477684892104431e-3,
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mangulate(3, "decode/jp/json",
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mangulate(4, "encode/en/aeson",
1.3580841192467653e-3,
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mangulate(5, "encode/en/json",
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mangulate(6, "encode/jp/aeson",
1.5021914610131224e-3,
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mangulate(7, "encode/jp/json",
1.4769715437157583e-3,
[1.6970080503685909e-3,1.4140051969750362e-3,1.4128131040795284e-3,1.402084268019958e-3,1.3968390592797237e-3,1.3980311521752315e-3,1.3839644560082393e-3,1.3899249204857784e-3,1.3899249204857784e-3,1.393978036330505e-3,1.39779273359613e-3,1.4018458494408565e-3,1.383010781691833e-3,1.4068526396019893e-3,1.3861102232201534e-3,3.925744927809997e-3,1.416866219924255e-3,1.3870638975365596e-3,1.3718051084740596e-3,1.3670367368920284e-3,1.3739508756859737e-3,1.3660830625756221e-3,1.3708514341576534e-3,1.3679904112084346e-3,1.3799113401635128e-3,1.3698977598412471e-3,1.393978036330505e-3,1.363937295363708e-3,1.3629836210473018e-3,1.3789576658471065e-3,1.3660830625756221e-3,1.3818186887963253e-3,1.371089852736755e-3,3.192846215651794e-3,1.3811034330590206e-3,1.37490455000238e-3,1.3670367368920284e-3,1.3758582243187862e-3,1.3651293882592159e-3,1.3777655729515987e-3,1.3670367368920284e-3,1.3820571073754268e-3,1.3667983183129268e-3,1.3679904112084346e-3,1.377050317214294e-3,1.3689440855248409e-3,1.3739508756859737e-3,1.3679904112084346e-3,1.3758582243187862e-3,1.3679904112084346e-3,3.1549376615746453e-3,1.3980311521752315e-3,1.3789576658471065e-3,1.363937295363708e-3,1.3768118986351924e-3,1.3739508756859737e-3,1.3698977598412471e-3,1.3739508756859737e-3,1.3760966428978878e-3,1.37490455000238e-3,1.3648909696801143e-3,1.3760966428978878e-3,1.3629836210473018e-3,1.371089852736755e-3,1.3689440855248409e-3,1.37490455000238e-3,1.363937295363708e-3,1.383010781691833e-3,3.1659049162133172e-3,1.4087599882348018e-3,1.3548773893578487e-3,1.37490455000238e-3,1.3698977598412471e-3,1.3660830625756221e-3,1.3849181303246456e-3,1.3698977598412471e-3,1.3701361784203487e-3,1.3670367368920284e-3,1.3758582243187862e-3,1.363937295363708e-3,1.37490455000238e-3,1.363937295363708e-3,1.37490455000238e-3,1.3689440855248409e-3,1.3651293882592159e-3,1.3758582243187862e-3,3.112022317336364e-3,1.3899249204857784e-3,1.3658446439965206e-3,1.3701361784203487e-3,1.3789576658471065e-3,1.3758582243187862e-3,1.3648909696801143e-3,1.377050317214294e-3,1.3698977598412471e-3,1.3739508756859737e-3,1.3698977598412471e-3,1.3880175718529659e-3,1.3620299467308956e-3,1.37490455000238e-3,],
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[1.5132563397924548,-4.682970077948788,8.317317648545497,-12.859671891512669,19.02679746669882,-28.133309302285664,42.9007908029406,-69.82602332942822,127.67669746583371,-282.2970512428148,2340.7077655694516,28272.458366878134,7366.814470412765,1115.2399587503958,145.99892606159736,-66.58693565074633,41.36483399432115,-28.238208842865426,20.31513345206966,-15.047078345795317,11.174249375015886,-7.785582373281383,3.240175193158349,15.667702195489298,382.72216107374857,17.57250519630716,-0.7128972361206748,-1.470246149979791,1.947924861998537,-1.9981942210203933,1.9131808414715328,-1.7847712082306253,1.6468344484680766,-1.5127239387467095,1.3876038589168116,-1.2731287021594997,1.169403172002122,-1.0758595779342106,0.9916672452130759,-0.9159269268709335,0.8477620640182693,-0.7863591536565946,0.730982701054132,-0.6809775737673918,0.6357653425266134,-0.5948380273991214,0.5577510188944319,-0.5241160714247639,0.49359480131445355,-0.46589287472146873,0.44075494225601547,-0.4179603141901863,0.3973193432481182,-0.3786704758565674,0.36187793
Raw
aeson5-vs-json-ghc-7.4.1RC1-report.txt
View raw

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