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feat: initial tcp/tls benchmarks
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@ozwaldorf
ozwaldorf committed Apr 26, 2023
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1 change: 1 addition & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/base/benchmark.json
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{"group_id":"S2N-QUIC UFDP/Content Size (Kilobyte)","function_id":"1 request","value_str":"1","throughput":{"Bytes":1024},"full_id":"S2N-QUIC UFDP/Content Size (Kilobyte)/1 request/1","directory_name":"S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1","title":"S2N-QUIC UFDP/Content Size (Kilobyte)/1 request/1"}
1 change: 1 addition & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/base/estimates.json
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{"mean":{"confidence_interval":{"confidence_level":0.95,"lower_bound":2769224.9651104016,"upper_bound":3046182.3115599942},"point_estimate":2910454.6037243987,"standard_error":69961.11021134231},"median":{"confidence_interval":{"confidence_level":0.95,"lower_bound":2811016.4709821427,"upper_bound":2959369.836195055},"point_estimate":2917591.761734694,"standard_error":35834.593124963016},"median_abs_dev":{"confidence_interval":{"confidence_level":0.95,"lower_bound":45185.4270827982,"upper_bound":288930.4053597455},"point_estimate":158008.5232645198,"standard_error":61175.99343473613},"slope":{"confidence_interval":{"confidence_level":0.95,"lower_bound":2892259.650045142,"upper_bound":3213903.5700943484},"point_estimate":3023183.594499751,"standard_error":89449.53886450836},"std_dev":{"confidence_interval":{"confidence_level":0.95,"lower_bound":131820.87223683973,"upper_bound":451039.5054965065},"point_estimate":323023.4316509619,"standard_error":79353.42559667114}}
1 change: 1 addition & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/base/sample.json
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{"sampling_mode":"Linear","iters":[14.0,28.0,42.0,56.0,70.0,84.0,98.0,112.0,126.0,140.0,154.0,168.0,182.0,196.0,210.0,224.0,238.0,252.0,266.0,280.0],"times":[28397017.0,96421900.0,111184361.0,157415442.0,184375369.0,262741775.0,268335416.0,331791823.0,352385172.0,404191597.0,451542269.0,495270240.0,538048908.0,572833442.0,627458032.0,629673611.0,692688195.0,767482735.0,985829582.0,815517898.0]}
1 change: 1 addition & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/base/tukey.json
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[2323295.5486607132,2565357.502008928,3210856.044270834,3452917.9976190487]
1 change: 1 addition & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/change/estimates.json
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{"mean":{"confidence_interval":{"confidence_level":0.95,"lower_bound":0.6650283879472972,"upper_bound":0.9239789144467289},"point_estimate":0.7946837416072876,"standard_error":0.06548488398453345},"median":{"confidence_interval":{"confidence_level":0.95,"lower_bound":0.6556460374338917,"upper_bound":0.9805081512090017},"point_estimate":0.8772984872084382,"standard_error":0.09140035263133613}}
1 change: 1 addition & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/new/benchmark.json
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{"group_id":"S2N-QUIC UFDP/Content Size (Kilobyte)","function_id":"1 request","value_str":"1","throughput":{"Bytes":1024},"full_id":"S2N-QUIC UFDP/Content Size (Kilobyte)/1 request/1","directory_name":"S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1","title":"S2N-QUIC UFDP/Content Size (Kilobyte)/1 request/1"}
1 change: 1 addition & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/new/estimates.json
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{"mean":{"confidence_interval":{"confidence_level":0.95,"lower_bound":2769224.9651104016,"upper_bound":3046182.3115599942},"point_estimate":2910454.6037243987,"standard_error":69961.11021134231},"median":{"confidence_interval":{"confidence_level":0.95,"lower_bound":2811016.4709821427,"upper_bound":2959369.836195055},"point_estimate":2917591.761734694,"standard_error":35834.593124963016},"median_abs_dev":{"confidence_interval":{"confidence_level":0.95,"lower_bound":45185.4270827982,"upper_bound":288930.4053597455},"point_estimate":158008.5232645198,"standard_error":61175.99343473613},"slope":{"confidence_interval":{"confidence_level":0.95,"lower_bound":2892259.650045142,"upper_bound":3213903.5700943484},"point_estimate":3023183.594499751,"standard_error":89449.53886450836},"std_dev":{"confidence_interval":{"confidence_level":0.95,"lower_bound":131820.87223683973,"upper_bound":451039.5054965065},"point_estimate":323023.4316509619,"standard_error":79353.42559667114}}
1 change: 1 addition & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/new/sample.json
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{"sampling_mode":"Linear","iters":[14.0,28.0,42.0,56.0,70.0,84.0,98.0,112.0,126.0,140.0,154.0,168.0,182.0,196.0,210.0,224.0,238.0,252.0,266.0,280.0],"times":[28397017.0,96421900.0,111184361.0,157415442.0,184375369.0,262741775.0,268335416.0,331791823.0,352385172.0,404191597.0,451542269.0,495270240.0,538048908.0,572833442.0,627458032.0,629673611.0,692688195.0,767482735.0,985829582.0,815517898.0]}
1 change: 1 addition & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/new/tukey.json
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[2323295.5486607132,2565357.502008928,3210856.044270834,3452917.9976190487]
303 changes: 303 additions & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/report/MAD.svg
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298 changes: 298 additions & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/report/SD.svg
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343 changes: 343 additions & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/report/both/pdf.svg
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292 changes: 292 additions & 0 deletions ...on/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/report/both/regression.svg
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315 changes: 315 additions & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/report/change/mean.svg
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320 changes: 320 additions & 0 deletions ...rion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/report/change/median.svg
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240 changes: 240 additions & 0 deletions ...rion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/report/change/t-test.svg
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292 changes: 292 additions & 0 deletions criterion/S2N-QUIC UFDP_Content Size (Kilobyte)/1 request/1/report/index.html
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<!DOCTYPE html>
<html>

<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<title>S2N-QUIC UFDP/Content Size (Kilobyte)/1 request/1 - 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>S2N-QUIC UFDP/Content Size (Kilobyte)/1 request/1</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="0.95 confidence level" class="ci-bound">Lower bound</th>
<th>Estimate</th>
<th title="0.95 confidence level" class="ci-bound">Upper bound</th>
</tr>
</thead>
<tbody>
<tr>
<td>Slope</td>
<td class="ci-bound">2.8923 ms</td>
<td>3.0232 ms</td>
<td class="ci-bound">3.2139 ms</td>
</tr>
<tr>
<td>Throughput</td>
<td class="ci-bound">311.15 KiB/s</td>
<td>330.78 KiB/s</td>
<td class="ci-bound">345.75 KiB/s</td>
</tr>
<tr>
<td>R&#xb2;</td>
<td class="ci-bound">0.7353525</td>
<td>0.7739982</td>
<td class="ci-bound">0.6963410</td>
</tr>
<tr>
<td>Mean</td>
<td class="ci-bound">2.7692 ms</td>
<td>2.9105 ms</td>
<td class="ci-bound">3.0462 ms</td>
</tr>
<tr>
<td title="Standard Deviation">Std. Dev.</td>
<td class="ci-bound">131.82 µs</td>
<td>323.02 µs</td>
<td class="ci-bound">451.04 µs</td>
</tr>
<tr>
<td>Median</td>
<td class="ci-bound">2.8110 ms</td>
<td>2.9176 ms</td>
<td class="ci-bound">2.9594 ms</td>
</tr>
<tr>
<td title="Median Absolute Deviation">MAD</td>
<td class="ci-bound">45.185 µs</td>
<td>158.01 µs</td>
<td class="ci-bound">288.93 µs</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 probability 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="0.95 confidence level" class="ci-bound">Lower bound</th>
<th>Estimate</th>
<th title="0.95 confidence level" class="ci-bound">Upper bound</th>
<th></th>
</tr>
</thead>
<tbody>
<tr>
<td>Change in time</td>
<td class="ci-bound">+66.503%</td>
<td>+79.468%</td>
<td class="ci-bound">+92.398%</td>
<td>(p = 0.00 &lt;
0.05)</td>
</tr>
<tr>
<td>Change in throughput</td>
<td class="ci-bound">-39.941%</td>
<td>-44.280%</td>
<td class="ci-bound">-48.024%</td>
<td></td>
</tr>
</tbody>
</table>
Performance has regressed.
</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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