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diff --git a/src/performance_measurement/figures/amdahl_speedup.pdf b/src/performance_measurement/figures/amdahl_speedup.pdf
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index 0000000..9eaeb94
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diff --git a/src/performance_measurement/figures/amdahl_speedup.py b/src/performance_measurement/figures/amdahl_speedup.py
new file mode 100644
index 0000000..18da16d
--- /dev/null
+++ b/src/performance_measurement/figures/amdahl_speedup.py
@@ -0,0 +1,38 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+
+def speedup(n: np.ndarray, parallel_frac: float) -> np.ndarray:
+    return 1.0 / (1.0 - parallel_frac + parallel_frac / n)
+
+n = np.array([2**i for i in range(11)])
+parallel_fracs = np.array([0.5, 0.75, 0.9, 0.95, 0.99])
+max_speedups = 1.0 / (1.0 - parallel_fracs)
+
+fig, ax = plt.subplots(figsize=(10, 7))
+ax.loglog(n, n, 'k--', alpha=0.4, label='Ideal scaling')
+for i, (frac, max_speedup) in enumerate(zip(parallel_fracs, max_speedups)):
+    ax.loglog(n, speedup(n, frac), label=f'p = {frac:.2f}')
+    ax.text(900, 1.1*max_speedup,
+            f'{max_speedup:.0f}',
+            color=f'C{i}',
+            ha='right',
+            fontsize=11,
+            fontweight='bold',
+            )
+
+ax.set_xlim([n[0], n[-1]])
+ax.set_ylim([n[0], n[-1]])
+ax.set_xlabel('Number of processors')
+ax.set_ylabel('Speedup')
+ax.set_title("Amdahl's law")
+
+ticks = [1, 10, 100, 1000]
+ax.set_xticks(ticks)
+ax.set_xticklabels(ticks)
+ax.set_yticks(ticks)
+ax.set_yticklabels(ticks)
+
+plt.legend()
+plt.savefig('amdahl_speedup.pdf')
+plt.show()