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‎docs/index.html‎

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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<title>CPU Load Generator</title>
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<!-- lightweight, self‑contained styling -->
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<style>
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:root {
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--accent: #0069d9;
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--bg: #f7f9fc;
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--text: #222;
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--code-bg: #eee;
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}
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* { box-sizing: border-box; }
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body {
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margin: 0;
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font-family: system-ui, -apple-system, "Segoe UI", Roboto, sans-serif;
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line-height: 1.6;
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color: var(--text);
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background: var(--bg);
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}
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header {
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background: var(--accent);
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color: #fff;
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padding: 2rem 1rem;
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text-align: center;
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}
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header h1 { margin: 0 0 .25rem; font-size: 2.25rem; }
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header a { color: #fff; font-weight: 600; text-decoration: underline; }
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main {
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max-width: 58rem;
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margin: 2rem auto;
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padding: 0 1rem;
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}
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section {
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background: #fff;
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padding: 2rem 1.5rem;
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border-radius: .85rem;
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box-shadow: 0 2px 6px rgba(0,0,0,.08);
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margin-bottom: 2rem;
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}
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h2 { margin-top: 0; color: var(--accent); }
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h3, h4 { color: var(--accent); margin-bottom: .25rem; }
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img { max-width: 100%; height: auto; border-radius: .5rem; }
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ul { padding-left: 1.25rem; }
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pre, code {
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font-family: ui-monospace, "SFMono-Regular", Consolas, monospace;
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background: var(--code-bg);
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border-radius: .35rem;
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}
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pre { padding: .75rem 1rem; overflow-x: auto; }
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footer {
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text-align: center;
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padding: 1rem;
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font-size: .9rem;
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color: #666;
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}
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</style>
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</head>
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<body>
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---
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layout: default # use the layout that ships with jekyll-theme-minimal
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title: CPU Load Generator # appears in the <title> tag and navbar (if any)
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---
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<!-- lightweight, self‑contained styling -->
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<style>
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:root {
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--accent: #0069d9;
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--bg: #f7f9fc;
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--text: #222;
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--code-bg: #eee;
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}
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* { box-sizing: border-box; }
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body {
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margin: 0;
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font-family: system-ui, -apple-system, "Segoe UI", Roboto, sans-serif;
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line-height: 1.6;
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color: var(--text);
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background: var(--bg);
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}
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header {
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background: var(--accent);
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color: #fff;
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padding: 2rem 1rem;
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text-align: center;
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}
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header h1 { margin: 0 0 .25rem; font-size: 2.25rem; }
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header a { color: #fff; font-weight: 600; text-decoration: underline; }
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main {
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max-width: 58rem;
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margin: 2rem auto;
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padding: 0 1rem;
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}
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section {
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background: #fff;
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padding: 2rem 1.5rem;
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border-radius: .85rem;
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box-shadow: 0 2px 6px rgba(0,0,0,.08);
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margin-bottom: 2rem;
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}
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h2 { margin-top: 0; color: var(--accent); }
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h3, h4 { color: var(--accent); margin-bottom: .25rem; }
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img { max-width: 100%; height: auto; border-radius: .5rem; }
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ul { padding-left: 1.25rem; }
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pre, code {
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font-family: ui-monospace, "SFMono-Regular", Consolas, monospace;
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background: var(--code-bg);
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border-radius: .35rem;
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}
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pre { padding: .75rem 1rem; overflow-x: auto; }
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footer {
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text-align: center;
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padding: 1rem;
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font-size: .9rem;
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color: #666;
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}
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</style>
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<!-- ===== Hero ===== -->
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<header>
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target="_blank" rel="noopener">View the project on GitHub ↗︎</a>
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</p>
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</header>
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<main>
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<main>
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<!-- ===== Motivation ===== -->
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<section id="motivation">
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<h2>Motivation</h2>
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<strong>stable CPU load for a finite period</strong> by closing the loop with a PID regulator.
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</p>
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<ul>
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<li>
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<strong>Performance&nbsp;testing:&nbsp;</strong>
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Stress‑test applications and full systems to uncover bottlenecks and verify robustness under load.
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</li>
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<li>
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<strong>Resource‑allocation optimisation:&nbsp;</strong>
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Reproduce real‑world utilisation scenarios so you can fine‑tune CPU quotas and scheduling policies.
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</li>
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<li>
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<strong>Benchmarking:&nbsp;</strong>
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Generate a consistent, repeatable workload that makes it easy to compare CPUs, machines, or configurations.
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</li>
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<li>
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<strong>Education&nbsp;&amp;&nbsp;training:&nbsp;</strong>
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Give students hands‑on experience with discrete PID control and demonstrate how load impacts performance.
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</li>
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<li>
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<strong>Thermal&nbsp;/&nbsp;power analysis:&nbsp;</strong>
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Investigate heat dissipation and energy consumption under a controlled, steady workload.
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</li>
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<li><strong>Performance&nbsp;testing:&nbsp;</strong>Stress‑test applications and full systems to uncover bottlenecks and verify robustness under load.</li>
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<li><strong>Resource‑allocation optimisation:&nbsp;</strong>Reproduce real‑world utilisation scenarios so you can fine‑tune CPU quotas and scheduling policies.</li>
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<li><strong>Benchmarking:&nbsp;</strong>Generate a consistent, repeatable workload that makes it easy to compare CPUs, machines, or configurations.</li>
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<li><strong>Education&nbsp;&amp;&nbsp;training:&nbsp;</strong>Give students hands‑on experience with discrete PID control and demonstrate how load impacts performance.</li>
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<li><strong>Thermal&nbsp;/&nbsp;power analysis:&nbsp;</strong>Investigate heat dissipation and energy consumption under a controlled, steady workload.</li>
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</ul>
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</section>
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<!-- ===== PID Regulator ===== -->
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<section id="pid">
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<h2>PID regulator for controlling CPU load</h2>
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<img src="https://gaetanocarlucci.altervista.org/wp-content/uploads/2024/07/pid-1.png"
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alt="PID control diagram" loading="lazy">
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<p>
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The architecture uses two threads: a <em>Monitor Thread</em> that measures CPU
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utilisation and a <em>Controller Thread</em> that applies PI control to adjust
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the sleep time of a tight loop so the measured load matches the
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target.
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</p>
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<!-- ===== PID Regulator ===== -->
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<section id="pid">
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<h2>PID regulator for controlling CPU load</h2>
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<img src="https://gaetanocarlucci.altervista.org/wp-content/uploads/2024/07/pid-1.png"
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alt="PID control diagram" loading="lazy">
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<p>
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The architecture uses two threads: a <em>Monitor Thread</em> that measures CPU
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utilisation and a <em>Controller Thread</em> that applies PI control to adjust
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the sleep time of a tight loop so the measured load matches the
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target.
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</p>
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<h3>Monitor Thread</h3>
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<p>
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Samples CPU usage at a fixed interval via
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<code>psutil.cpu_percent(interval)</code>, filters the measurements with a
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first‑order filter and logs the results.
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</p>
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<h3>Monitor Thread</h3>
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<p>
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Samples CPU usage at a fixed interval via
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<code>psutil.cpu_percent(interval)</code>, filters the measurements with a
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first‑order filter and logs the results.
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</p>
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<h3>Controller Thread</h3>
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<p>
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Compares the target load (<em>set‑point</em>) and actual load, then computes the
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control signal using proportional (<code>K<sub>p</sub></code>) and integral
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(<code>K<sub>i</sub></code>) actions. The derivative term is not used.
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</p>
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<h3>Controller Thread</h3>
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<p>
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Compares the target load (<em>set‑point</em>) and actual load, then computes the
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control signal using proportional (<code>K<sub>p</sub></code>) and integral
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(<code>K<sub>i</sub></code>) actions. The derivative term is not used.
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</p>
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<pre><code># actuator snippet
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```python
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# actuator snippet
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def generate_load(self, sleep_time):
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interval = time.time() + self.period - sleep_time
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while time.time() &lt; interval:
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while time.time() < interval:
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pr = 213123 # busy‑work
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_ = pr * pr
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pr = pr + 1
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time.sleep(sleep_time)</code></pre>
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<pre><code># main PI control loop
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def run(self):
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def cpu_model(cpu_period):
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return self.period - cpu_period # maps period to sleep time
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self.shutdown_flag.clear()
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while not self.shutdown_flag.is_set():
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time.sleep(self.sampling_interval)
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with self.target_lock, self.cpu_lock:
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CT = self.CT # target load
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cpu = self.cpu # measured load
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self.err = CT - cpu * 0.01
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ts = time.time()
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samp_int = ts - self.last_ts
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self.int_err += self.err * samp_int
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self.last_ts = ts
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self.cpuPeriod = (self.kp * self.err +
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self.ki * self.int_err)
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# anti‑windup
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self.cpuPeriod = max(0, min(self.cpuPeriod, self.period))
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self.set_sleep_time(cpu_model(self.cpuPeriod))</code></pre>
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<h3>PI tuning insights</h3>
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<p>
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Raising <code>K<sub>p</sub></code> speeds up the response but risks overshoot; adding an
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integral term removes steady‑state error at the cost of sluggishness
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and potential oscillations, so anti‑windup is essential.
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</p>
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</section>
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<!-- ===== Results ===== -->
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<section id="results">
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<h2>Results</h2>
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<p>
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Quick test in a GitHub Codespace or local shell:
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<code>./CPULoadGenerator.py&nbsp;-c&nbsp;0&nbsp;-c&nbsp;3&nbsp;-l&nbsp;0.55&nbsp;-l&nbsp;0.12</code>
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</p>
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<p>Example 50 % target load on core 0 for 20 s:</p>
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<img src="https://gaetanocarlucci.altervista.org/wp-content/uploads/2024/07/50-Target-Load.png"
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alt="CPU‑load plot" loading="lazy">
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</section>
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</main>
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<footer>
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MIT License &bull; © 2025 Gaetano Carlucci
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</footer>
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</body>
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</html>
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time.sleep(sleep_time)

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