add all materials

benchmark_low_level/plot.py

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+import os
+import sys
+import numpy as np
+import matplotlib
+import itertools
+from matplotlib import pyplot as plt
+plt.style.use('ggplot')
+matplotlib.rcParams['font.size'] = 12
+
+name = 't14'
+
+caches = (48*1024, 1280*1024, 12*1024*1024)
+
+def get_labels(x):
+    xlabels = []
+    for value in x:
+        b = int(2**value)
+        if b < 1024:
+            xlabels.append(f'{b}B')
+        elif b < 1048576:
+            xlabels.append(f'{b//1024}K')
+        elif b < 1073741824:
+            xlabels.append(f'{b//1024//1024}M')
+        else:
+            xlabels.append(f'{b//1024//1024//1024}G')
+    return xlabels
+
+
+# manually set ticks, to disable, set ticks = None
+
+line = np.linspace(1, 10, 9, endpoint=False)
+yticks = list(line)+list(line*10)+list(line[:2]*100)
+
+ylabels = {1 : '1 ns', 5 : '5 ns', 10 : '10 ns', 50 : '50 ns', 100: '100 ns'}
+ticks = {'l': (yticks, [ylabels[i] if i in ylabels else '' for i in yticks]),
+         'bw': (range(5,46,5), [f'{i} GB/s' for i in range(5,46,5)]),
+        }
+
+# manually set limits, to disable set to ylim = None
+
+ylim = {'l' : (1, 200),
+        'bw' : (5,45),
+       }
+
+for type_ in ('bw', 'l'):
+    if type_ == 'bw':
+        suffix = ('r', 'w')
+        ylabel = ''
+        title = f'Memory Bandwidth ({name}) [GB/s]'
+        legend1, legend2 = 'read', 'write'
+        pic = f'bandwidth-{name}.svg'
+        plt_func = plt.plot
+    else:
+        suffix = ('seq', 'rnd')
+        ylabel = ''
+        title = f'Memory Latency ({name}) [ns]'
+        legend1, legend2 = 'sequential access', 'random access'
+        pic = f'latency-{name}.svg'
+        plt_func = plt.semilogy
+
+
+    data1 = np.loadtxt(f'{name}-{type_}{suffix[0]}.csv', delimiter=',')
+    data2 = np.loadtxt(f'{name}-{type_}{suffix[1]}.csv', delimiter=',')
+
+    # convert to bytes and then to the corresponding power of two
+
+    if type_ == 'bw':
+        x1 = np.log2(data1[:,0]*1024*1024).round()
+        y1 = data1[:,1]/1024
+        x2 = np.log2(data2[:,0]*1024*1024).round()
+        y2 = data2[:,1]/1024
+    else:
+        x1 = np.log2(data1[::2,0]*1024*1024).round()
+        y1 = data1[::2,1]
+        x2 = np.log2(data2[::2,0]*1024*1024).round()
+        y2 = data2[::2,1]
+        ylabels = None
+
+
+    xlabel = 'block size'
+    xlabels = get_labels(x1)
+
+    plt.figure(figsize=(8.5,7.5))
+    if type_ == 'l':
+        # plot two empy plots so we advance the color cyle (bad trick)
+        _ = plt_func([],[])
+        _ = plt_func([],[])
+    p1, = plt_func(x1, y1, 'o')
+    plt.ylabel(ylabel)
+    plt.xlabel(xlabel)
+    p2, = plt_func(x2, y2, 'o')
+    if ylim and type_ in ylim:
+        plt.ylim(*ylim[type_])
+    plt.xticks(x1, xlabels, rotation=60)
+    if ticks and type_ in ticks:
+        plt.yticks(*ticks[type_])
+    plt.legend((p1, p2), (legend1, legend2))
+    if ylim and type_ in ylim:
+        miny, maxy = ylim[type_]
+    else:
+        miny = min(y1.min(), y2.min())
+        maxy = max(y1.max(), y2.max())
+    # caches
+    for idx, cache in enumerate(caches):
+        level = idx + 1
+        size = np.log2(cache)
+        plt.plot((size, size), (miny, maxy),
+                 color = 'darkblue', alpha=0.4)
+        plt.text(size-1, 2*miny, f'L{level}\n⟵',
+                 color='darkblue', verticalalignment='top')
+
+    plt.title(title)
+    plt.savefig(pic)
+
+