add all materials

architecture/memory.py

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+# RAM clock rate and transfer rate data from Wikipedia
+# https://en.wikipedia.org/wiki/DDR_SDRAM
+# Table data extracted with: https://wikitable2csv.ggor.de/
+import numpy as np
+import pandas
+import matplotlib
+from matplotlib import pyplot as plt
+plt.style.use('ggplot')
+matplotlib.rcParams['font.size'] = 12
+matplotlib.rcParams['font.family'] = ['Exo 2', 'sans-serif']
+
+
+data = pandas.read_csv('memory.csv')
+#data = data.sort_values('Memory clock (MHz)')
+_types = list(data['Type'])
+_transfers = list(data['Data rate (MT/s)'])
+_cycle_times = list(data['Cycle time (ns)'])
+_latencies = list(data['Eighth word (ns)'])
+
+# remove redundant data
+types = []
+transfers = []
+cycle_times = []
+latencies = []
+for idx, typ in enumerate(_types):
+    # just select the first occurence of this type
+    if typ in types:
+        continue
+    # filter DDR4 inferior to DDR4-3333
+    prefix = 'DDR4-'
+    if typ.startswith(prefix) and int(typ.removeprefix(prefix)) < 3333:
+        continue
+    types.append(typ)
+    transfers.append(_transfers[idx])
+    cycle_times.append(_cycle_times[idx])
+    latencies.append(_latencies[idx])
+
+# transform transfers from MT/s to GB/s
+transfers = np.array(transfers, dtype='float64')*8/1024
+plt.figure(figsize=(8.5,7.5))
+plt.title('Memory Bandwidth [GB/s] (1995-2023)')
+# my laptop first
+me = types.index('DDR5-5200')
+plt.plot(range(len(types)), transfers, 'o')
+plt.plot(me, transfers[me], 'o')
+plt.xticks(range(len(types))[::3], types[::3], rotation=30, ha='right')
+yticks = range(0,56)
+ylabels = []
+for t in yticks:
+    if not t%5:
+        ylabels.append(str(t))
+    else:
+        ylabels.append('')
+plt.yticks(yticks, ylabels)
+plt.ylabel('GB/s')
+plt.tick_params(axis='y', which='both', reset=True, labelright=True, right=True)
+plt.savefig('memory_bandwidth.svg')
+
+plt.figure(figsize=(8.5,7.5))
+plt.title('Memory Cycle Time [ns] (1995-2023)')
+# my laptop first
+me = types.index('DDR5-5200')
+plt.semilogy(range(len(types)), cycle_times, 'o')
+plt.semilogy(me, cycle_times[me], 'o')
+plt.xticks(range(len(types))[::3], types[::3], rotation=30, ha='right')
+plt.ylim(0.1, 11)
+line = np.arange(0,10).astype('float64')
+yticks = list(line[1:]*0.1)+list(line[1:])+list(line[1:2]*10)
+ylabels = []
+for value in yticks:
+    if value in (0.1, 0.5, 1., 1.5, 5., 10.):
+        ylabels.append(f'{value} ns')
+    else:
+        ylabels.append('')
+plt.yticks(yticks, ylabels)
+plt.tick_params(axis='y', which='both', reset=True, labelright=True, right=True)
+plt.savefig('memory_clock.svg')
+
+# transform transfers from MT/s to GB/s
+plt.figure(figsize=(8.5,7.5))
+plt.title('Memory Latency [ns] (1998-2023)')
+# my laptop first
+me = types.index('DDR5-5200')
+mel = latencies[me]
+y = latencies[2:]
+x = types[2:]
+plt.plot(range(len(x)), y, 'o')
+plt.plot(me, mel, 'o')
+plt.xticks(range(len(x))[::3], x[::3], rotation=30, ha='right')
+plt.ylim(8,40)
+yticks = range(8,41)
+ylabels = []
+for t in yticks:
+    if not t%5:
+        ylabels.append(str(t)+' ns')
+    else:
+        ylabels.append('')
+plt.yticks(yticks, ylabels)
+plt.tick_params(axis='y', which='both', reset=True, labelright=True, right=True)
+plt.savefig('memory_latency.svg')
+