84 lines
2.5 KiB
Python
84 lines
2.5 KiB
Python
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# CPU clock rate data from Wikipedia
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# https://en.wikipedia.org/wiki/Microprocessor_chronology
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# Table data extracted with: https://wikitable2csv.ggor.de/
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import numpy as np
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import matplotlib
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from matplotlib import pyplot as plt
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plt.style.use('ggplot')
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matplotlib.rcParams['font.size'] = 12
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matplotlib.rcParams['font.family'] = ['Exo 2', 'sans-serif']
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data = open('cpu_clock_rate.csv', 'rt')
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# first, remove units and rescale everything to MHz
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rescaled = []
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for line in data:
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date, raw = line.split(',')
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try:
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value, unit = raw.split()
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except ValueError:
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# there are lines with multiple units, for example
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# 550 MHz-1.3 GHz
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# take the left most one
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raw = raw.split('-')[1]
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value, unit = raw.split()
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# if value is in the form X-Y, just use the biggest, i.e. Y
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if '-' in value:
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value = value.split('-')[1]
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value = float(value)
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# rescale value
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if unit == 'kHz':
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value = value/1000
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elif unit == 'GHz':
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value = value*1000
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elif unit == 'MHz':
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pass
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else:
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raise ValueError(f'Unit not understood! {unit}')
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rescaled.append((date, value))
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dtype = [('year', np.float64), ('clock', np.float64)]
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rescaled = np.array(rescaled, dtype=dtype)
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# sort first by year and then by value
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rescaled.sort(order=['year', 'clock'])
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# add some jitter on values corresponding to the same year, so that the plot
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# looks more understandable
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old_year = rescaled[0][0]
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count = 0
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for row in range(rescaled.shape[0]):
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year = rescaled[row][0]
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count += 1
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if year != old_year:
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# add jitter to the values corresponding to the previous year
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prev_count = count-1
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if prev_count > 1:
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jitter = 1/prev_count
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for i in range(1, count):
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loc_year, loc_value = rescaled[row-count+i]
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rescaled[row-count+i] = (loc_year+(jitter*(i-1)), loc_value)
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# restart counting
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count = 1
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old_year = year
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# plot the thing
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plt.figure(figsize=(8.5,7.5))
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plt.semilogy(rescaled['year'], rescaled['clock'], 'o')
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# my laptop here
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plt.semilogy([2020], [4900], 'o')
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plt.grid(None)
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plt.grid(which='both', axis='both')
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plt.ylim(0.1, 10000)
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plt.xlim(1968, 2025)
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years = np.arange(1970, 2025, 5)
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plt.xticks(years, years)
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plt.yticks([0.1, 1,10,100,1000, 10000], ['1 kHz\n1 ms', '1 MHz\n1 µs', '10 MHz\n100 ns',
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'100 MHz\n10 ns', '1 GHz\n1 ns', '10 GHz\n0.1 ns'])
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plt.tick_params(labelright=True, top=True, right=True)
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plt.title('CPU clock rate')
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plt.savefig('cpu_clock_rate.svg')
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