116 lines
3.2 KiB
Python
116 lines
3.2 KiB
Python
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)
|
|
|
|
|