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  • weber/simcore-rs
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results/barbershop/100000/new/raw.csv deleted 100644 → 0
View file @ e4e01a0c
group,function,value,throughput_num,throughput_type,sample_measured_value,unit,iteration_count
Barbershop,,100000,,,11258300.0,ns,8
Barbershop,,100000,,,23151400.0,ns,16
Barbershop,,100000,,,40156200.0,ns,24
Barbershop,,100000,,,45149100.0,ns,32
Barbershop,,100000,,,60543800.0,ns,40
Barbershop,,100000,,,71699100.0,ns,48
Barbershop,,100000,,,80908600.0,ns,56
Barbershop,,100000,,,91111400.0,ns,64
Barbershop,,100000,,,101436500.0,ns,72
Barbershop,,100000,,,115971500.0,ns,80
Barbershop,,100000,,,129275200.0,ns,88
Barbershop,,100000,,,156750700.0,ns,96
Barbershop,,100000,,,152675000.0,ns,104
Barbershop,,100000,,,159118900.0,ns,112
Barbershop,,100000,,,172122500.0,ns,120
Barbershop,,100000,,,181849500.0,ns,128
Barbershop,,100000,,,194189300.0,ns,136
Barbershop,,100000,,,214791000.0,ns,144
Barbershop,,100000,,,219014100.0,ns,152
Barbershop,,100000,,,230268100.0,ns,160
Barbershop,,100000,,,236874700.0,ns,168
Barbershop,,100000,,,251145100.0,ns,176
Barbershop,,100000,,,265018500.0,ns,184
Barbershop,,100000,,,276687500.0,ns,192
Barbershop,,100000,,,283880800.0,ns,200
Barbershop,,100000,,,330524200.0,ns,208
Barbershop,,100000,,,335799500.0,ns,216
Barbershop,,100000,,,322610900.0,ns,224
Barbershop,,100000,,,334612300.0,ns,232
Barbershop,,100000,,,343695900.0,ns,240
Barbershop,,100000,,,352043900.0,ns,248
Barbershop,,100000,,,368207000.0,ns,256
Barbershop,,100000,,,378854900.0,ns,264
Barbershop,,100000,,,386805900.0,ns,272
Barbershop,,100000,,,403057700.0,ns,280
Barbershop,,100000,,,414145400.0,ns,288
Barbershop,,100000,,,425241200.0,ns,296
Barbershop,,100000,,,435164000.0,ns,304
Barbershop,,100000,,,449720100.0,ns,312
Barbershop,,100000,,,464929500.0,ns,320
Barbershop,,100000,,,467967100.0,ns,328
Barbershop,,100000,,,485652600.0,ns,336
Barbershop,,100000,,,489110800.0,ns,344
Barbershop,,100000,,,505077900.0,ns,352
Barbershop,,100000,,,521007300.0,ns,360
Barbershop,,100000,,,530084600.0,ns,368
Barbershop,,100000,,,533162100.0,ns,376
Barbershop,,100000,,,553346000.0,ns,384
Barbershop,,100000,,,568680100.0,ns,392
Barbershop,,100000,,,577911800.0,ns,400
Barbershop,,100000,,,587679000.0,ns,408
Barbershop,,100000,,,594449700.0,ns,416
Barbershop,,100000,,,604859200.0,ns,424
Barbershop,,100000,,,617146600.0,ns,432
Barbershop,,100000,,,652916800.0,ns,440
Barbershop,,100000,,,643365800.0,ns,448
Barbershop,,100000,,,649919000.0,ns,456
Barbershop,,100000,,,671399400.0,ns,464
Barbershop,,100000,,,677201500.0,ns,472
Barbershop,,100000,,,684634300.0,ns,480
Barbershop,,100000,,,697488200.0,ns,488
Barbershop,,100000,,,716516000.0,ns,496
Barbershop,,100000,,,721044200.0,ns,504
Barbershop,,100000,,,731838500.0,ns,512
Barbershop,,100000,,,740138200.0,ns,520
Barbershop,,100000,,,755934800.0,ns,528
Barbershop,,100000,,,769604300.0,ns,536
Barbershop,,100000,,,810699600.0,ns,544
Barbershop,,100000,,,821170400.0,ns,552
Barbershop,,100000,,,823984500.0,ns,560
Barbershop,,100000,,,815695000.0,ns,568
Barbershop,,100000,,,821230400.0,ns,576
Barbershop,,100000,,,837383300.0,ns,584
Barbershop,,100000,,,851223400.0,ns,592
Barbershop,,100000,,,863588200.0,ns,600
Barbershop,,100000,,,876111800.0,ns,608
Barbershop,,100000,,,884431700.0,ns,616
Barbershop,,100000,,,900753300.0,ns,624
Barbershop,,100000,,,906882700.0,ns,632
Barbershop,,100000,,,916174800.0,ns,640
Barbershop,,100000,,,928050500.0,ns,648
Barbershop,,100000,,,941027000.0,ns,656
Barbershop,,100000,,,953379100.0,ns,664
Barbershop,,100000,,,964365900.0,ns,672
Barbershop,,100000,,,978582000.0,ns,680
Barbershop,,100000,,,997588400.0,ns,688
Barbershop,,100000,,,1012511400.0,ns,696
Barbershop,,100000,,,1019418400.0,ns,704
Barbershop,,100000,,,1032338000.0,ns,712
Barbershop,,100000,,,1055256400.0,ns,720
Barbershop,,100000,,,1048397500.0,ns,728
Barbershop,,100000,,,1055206300.0,ns,736
Barbershop,,100000,,,1071154100.0,ns,744
Barbershop,,100000,,,1080270800.0,ns,752
Barbershop,,100000,,,1095260000.0,ns,760
Barbershop,,100000,,,1097986500.0,ns,768
Barbershop,,100000,,,1105461000.0,ns,776
Barbershop,,100000,,,1115698800.0,ns,784
Barbershop,,100000,,,1134741200.0,ns,792
Barbershop,,100000,,,1145929400.0,ns,800
results/barbershop/100000/new/sample.json deleted 100644 → 0
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{"sampling_mode":"Linear","iters":[8.0,16.0,24.0,32.0,40.0,48.0,56.0,64.0,72.0,80.0,88.0,96.0,104.0,112.0,120.0,128.0,136.0,144.0,152.0,160.0,168.0,176.0,184.0,192.0,200.0,208.0,216.0,224.0,232.0,240.0,248.0,256.0,264.0,272.0,280.0,288.0,296.0,304.0,312.0,320.0,328.0,336.0,344.0,352.0,360.0,368.0,376.0,384.0,392.0,400.0,408.0,416.0,424.0,432.0,440.0,448.0,456.0,464.0,472.0,480.0,488.0,496.0,504.0,512.0,520.0,528.0,536.0,544.0,552.0,560.0,568.0,576.0,584.0,592.0,600.0,608.0,616.0,624.0,632.0,640.0,648.0,656.0,664.0,672.0,680.0,688.0,696.0,704.0,712.0,720.0,728.0,736.0,744.0,752.0,760.0,768.0,776.0,784.0,792.0,800.0],"times":[11258300.0,23151400.0,40156200.0,45149100.0,60543800.0,71699100.0,80908600.0,91111400.0,101436500.0,115971500.0,129275200.0,156750700.0,152675000.0,159118900.0,172122500.0,181849500.0,194189300.0,214791000.0,219014100.0,230268100.0,236874700.0,251145100.0,265018500.0,276687500.0,283880800.0,330524200.0,335799500.0,322610900.0,334612300.0,343695900.0,352043900.0,368207000.0,378854900.0,386805900.0,403057700.0,414145400.0,425241200.0,435164000.0,449720100.0,464929500.0,467967100.0,485652600.0,489110800.0,505077900.0,521007300.0,530084600.0,533162100.0,553346000.0,568680100.0,577911800.0,587679000.0,594449700.0,604859200.0,617146600.0,652916800.0,643365800.0,649919000.0,671399400.0,677201500.0,684634300.0,697488200.0,716516000.0,721044200.0,731838500.0,740138200.0,755934800.0,769604300.0,810699600.0,821170400.0,823984500.0,815695000.0,821230400.0,837383300.0,851223400.0,863588200.0,876111800.0,884431700.0,900753300.0,906882700.0,916174800.0,928050500.0,941027000.0,953379100.0,964365900.0,978582000.0,997588400.0,1012511400.0,1019418400.0,1032338000.0,1055256400.0,1048397500.0,1055206300.0,1071154100.0,1080270800.0,1095260000.0,1097986500.0,1105461000.0,1115698800.0,1134741200.0,1145929400.0]}
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[1382557.362869584,1405953.0950970615,1468341.7143703348,1491737.4465978122]
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<!DOCTYPE html>
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<title>Barbershop/100000 - Criterion.rs</title>
<style type="text/css">
body {
font: 14px Helvetica Neue;
text-rendering: optimizelegibility;
}
.body {
width: 960px;
margin: auto;
}
th {
font-weight: 200
}
th,
td {
padding-right: 3px;
padding-bottom: 3px;
}
a:link {
color: #1F78B4;
text-decoration: none;
}
th.ci-bound {
opacity: 0.6
}
td.ci-bound {
opacity: 0.5
}
.stats {
width: 80%;
margin: auto;
display: flex;
}
.additional_stats {
flex: 0 0 60%
}
.additional_plots {
flex: 1
}
h2 {
font-size: 36px;
font-weight: 300;
}
h3 {
font-size: 24px;
font-weight: 300;
}
#footer {
height: 40px;
background: #888;
color: white;
font-size: larger;
font-weight: 300;
}
#footer a {
color: white;
text-decoration: underline;
}
#footer p {
text-align: center
}
</style>
</head>
<body>
<div class="body">
<h2>Barbershop/100000</h2>
<div class="absolute">
<section class="plots">
<table width="100%">
<tbody>
<tr>
<td>
<a href="pdf.svg">
<img src="pdf_small.svg" alt="PDF of Slope" width="450" height="300" />
</a>
</td>
<td>
<a href="regression.svg">
<img src="regression_small.svg" alt="Regression" width="450" height="300" />
</a>
</td>
</tr>
</tbody>
</table>
</section>
<section class="stats">
<div class="additional_stats">
<h4>Additional Statistics:</h4>
<table>
<thead>
<tr>
<th></th>
<th title="0.99 confidence level" class="ci-bound">Lower bound</th>
<th>Estimate</th>
<th title="0.99 confidence level" class="ci-bound">Upper bound</th>
</tr>
</thead>
<tbody>
<tr>
<td>Slope</td>
<td class="ci-bound">1.4356 ms</td>
<td>1.4398 ms</td>
<td class="ci-bound">1.4448 ms</td>
</tr>
<tr>
<td>R&#xb2;</td>
<td class="ci-bound">0.9800653</td>
<td>0.9812034</td>
<td class="ci-bound">0.9795715</td>
</tr>
<tr>
<td>Mean</td>
<td class="ci-bound">1.4377 ms</td>
<td>1.4463 ms</td>
<td class="ci-bound">1.4577 ms</td>
</tr>
<tr>
<td title="Standard Deviation">Std. Dev.</td>
<td class="ci-bound">17.121 us</td>
<td>39.620 us</td>
<td class="ci-bound">59.052 us</td>
</tr>
<tr>
<td>Median</td>
<td class="ci-bound">1.4344 ms</td>
<td>1.4366 ms</td>
<td class="ci-bound">1.4404 ms</td>
</tr>
<tr>
<td title="Median Absolute Deviation">MAD</td>
<td class="ci-bound">7.1859 us</td>
<td>11.867 us</td>
<td class="ci-bound">16.779 us</td>
</tr>
</tbody>
</table>
</div>
<div class="additional_plots">
<h4>Additional Plots:</h4>
<ul>
<li>
<a href="typical.svg">Typical</a>
</li>
<li>
<a href="mean.svg">Mean</a>
</li>
<li>
<a href="SD.svg">Std. Dev.</a>
</li>
<li>
<a href="median.svg">Median</a>
</li>
<li>
<a href="MAD.svg">MAD</a>
</li>
<li>
<a href="slope.svg">Slope</a>
</li>
</ul>
</div>
</section>
<section class="explanation">
<h4>Understanding this report:</h4>
<p>The plot on the left displays the average time per iteration for this benchmark. The shaded region
shows the estimated probabilty of an iteration taking a certain amount of time, while the line
shows the mean. Click on the plot for a larger view showing the outliers.</p>
<p>The plot on the right shows the linear regression calculated from the measurements. Each point
represents a sample, though here it shows the total time for the sample rather than time per
iteration. The line is the line of best fit for these measurements.</p>
<p>See <a href="https://bheisler.github.io/criterion.rs/book/user_guide/command_line_output.html#additional-statistics">the
documentation</a> for more details on the additional statistics.</p>
</section>
</div>
<section class="plots">
<h3>Change Since Previous Benchmark</h3>
<div class="relative">
<table width="100%">
<tbody>
<tr>
<td>
<a href="both/pdf.svg">
<img src="relative_pdf_small.svg" alt="PDF Comparison" width="450"
height="300" />
</a>
</td>
<td>
<a href="both/regression.svg">
<img src="relative_regression_small.svg" alt="Regression Comparison" width="450"
height="300" />
</a>
</td>
</tr>
</tbody>
</table>
</div>
</section>
<section class="stats">
<div class="additional_stats">
<h4>Additional Statistics:</h4>
<table>
<thead>
<tr>
<th></th>
<th title="0.99 confidence level" class="ci-bound">Lower bound</th>
<th>Estimate</th>
<th title="0.99 confidence level" class="ci-bound">Upper bound</th>
<th></th>
</tr>
</thead>
<tbody>
<tr>
<td>Change in time</td>
<td class="ci-bound">-2.6656%</td>
<td>-1.9682%</td>
<td class="ci-bound">-1.2352%</td>
<td>(p = 0.00 &lt;
0.05)</td>
</tr>
</tbody>
</table>
Performance has improved.
</div>
<div class="additional_plots">
<h4>Additional Plots:</h4>
<ul>
<li>
<a href="change/mean.svg">Change in mean</a>
</li>
<li>
<a href="change/median.svg">Change in median</a>
</li>
<li>
<a href="change/t-test.svg">T-Test</a>
</li>
</ul>
</div>
</section>
<section class="explanation">
<h4>Understanding this report:</h4>
<p>The plot on the left shows the probability of the function taking a certain amount of time. The red
curve represents the saved measurements from the last time this benchmark was run, while the blue curve
shows the measurements from this run. The lines represent the mean time per iteration. Click on the
plot for a larger view.</p>
<p>The plot on the right shows the two regressions. Again, the red line represents the previous measurement
while the blue line shows the current measurement.</p>
<p>See <a href="https://bheisler.github.io/criterion.rs/book/user_guide/command_line_output.html#change">the
documentation</a> for more details on the additional statistics.</p>
</section>
</div>
<div id="footer">
<p>This report was generated by
<a href="https://github.com/bheisler/criterion.rs">Criterion.rs</a>, a statistics-driven benchmarking
library in Rust.</p>
</div>
</body>
</html>
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