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Created gh-images branch for storing images

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Christopher Haster
2019-03-31 20:42:17 -05:00
commit 405c1ab6e3
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file-cost.py Executable file
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#!/usr/bin/env python
import matplotlib
matplotlib.use('SVG')
import matplotlib.pyplot as plt
import numpy as np
matplotlib.rc('font', family='sans-serif', size=11)
matplotlib.rc('axes', titlesize='medium', labelsize='medium')
matplotlib.rc('xtick', labelsize='small')
matplotlib.rc('ytick', labelsize='small')
fig, ax = plt.subplots(figsize=(6, 3.5))
ax.set_title('File storage cost')
# multiplicative cost of inline files
def inline_cost(n, B):
#return 4+n-n
return np.full_like(n, 4)
# multiplicative cost of ctz skip-list files
def ctz_cost(n, B):
return (np.ceil(n/B)*B) / n
# combined multiplicative cost
def file_cost(n, B):
return np.where(n < B/4, inline_cost(n, B), ctz_cost(n, B))
t = np.arange(0.0, 80.0, 0.25)
ax.plot(t, file_cost(t, 16))
t1 = np.arange(0.0, 16.0/4.0 + 0.5, 0.25)
t2 = np.arange(16.0/4.0, 80.0, 0.25)
ax.plot(t1, ctz_cost(t1, 16), color='C0', linestyle=(2.65, (3.65,1.65)))
ax.plot(t2, inline_cost(t2, 16), color='C0', linestyle=(3.65, (3.65,1.65)))
ax.text(70.5, 4.15, 'inline file', size='small')
ax.text(3.3, 5.85, 'ctz skip-list', rotation=-85, size='small')
ax.set_xlabel('file size')
ax.set_xlim(0, 80)
ax.set_ylabel('multiplicative cost')
ax.set_ylim(0, 6)
xticks = np.arange(0, 80+1, 16)
ax.set_xticks(xticks)
ax.set_xticklabels(['%dKiB' % ((t*(4096/16))/1024) for t in xticks])
yticks = np.arange(0, 6+1, 2)
ax.set_yticks(yticks)
ax.set_yticklabels(['%dx' % t for t in yticks])
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
fig.tight_layout()
plt.savefig('file-cost.svg', bbox_inches="tight")

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file-cost.svg Normal file
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metadata-cost.py Executable file
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#!/usr/bin/env python
import matplotlib
matplotlib.use('SVG')
import matplotlib.pyplot as plt
import numpy as np
matplotlib.rc('font', family='sans-serif', size=11)
matplotlib.rc('axes', titlesize='medium', labelsize='medium')
matplotlib.rc('xtick', labelsize='small')
matplotlib.rc('ytick', labelsize='small')
fig, ax = plt.subplots(figsize=(6, 3.5))
ax.set_title('Metadata pair update cost')
# multiplicative cost of metadata
def cost(r, n, size):
cost = n + n*(r*(size/n) / ((1-r)*(size/n) + 1))
return cost / n
t = np.arange(0.0, 1.0, 0.01)
ax.plot(t, cost(t, 100, 4096))
ax.set_xlabel('% full')
ax.set_xlim(0, 1)
ax.set_ylabel('multiplicative cost')
ax.set_ylim(0, 12)
xticks = np.arange(0.0, 1+0.1, 0.2)
ax.set_xticks(xticks)
ax.set_xticklabels(['%d%%' % (100*t) for t in xticks])
yticks = np.arange(0, 12+1, 2)
ax.set_yticks(yticks)
ax.set_yticklabels(['%dx' % t for t in yticks])
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
fig.tight_layout()
plt.savefig('metadata-cost.svg', bbox_inches="tight")

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wear-distribution.py Executable file
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#!/usr/bin/env python
import matplotlib
matplotlib.use('SVG')
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import numpy as np
matplotlib.rc('font', family='sans-serif', size=11)
matplotlib.rc('axes', titlesize='medium', labelsize='medium')
matplotlib.rc('xtick', labelsize='small')
matplotlib.rc('ytick', labelsize='small')
np.random.seed(map(ord, "hello"))
gs = gridspec.GridSpec(nrows=2, ncols=2, height_ratios=[1, 2],
wspace=0.25, hspace=0.25)
fig = plt.figure(figsize=(7, 5.5))
ax1 = fig.add_subplot(gs[0, 0])
ax2 = fig.add_subplot(gs[0, 1], sharex=ax1, sharey=ax1)
ax3 = fig.add_subplot(gs[1, :])
# Convolution (I think?) of two types of uniform distributions under modulo
w1 = np.random.randint(0, 100, 30)
w2 = np.arange(0, 30, 1)
w3 = np.array([w2 + i for i in w1]).flatten() % 100
ax1.hist(w1, bins=100, range=(0,100), histtype='stepfilled')
ax2.hist(w2, bins=100, range=(0,100), histtype='stepfilled')
ax3.hist(w3, bins=100, range=(0,100), histtype='stepfilled')
ax1.set_title('Random offset')
ax2.set_title('Linear allocation')
ax3.set_title('Cumulative allocation')
ax1.set_ylabel('wear')
ax1.set_yticks(np.arange(0, 3))
ax3.set_ylabel('wear')
ax3.set_xlabel('block address')
for ax in [ax1,ax2,ax3]:
ax.set_xlim(0, 100)
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)
ax1.text(109.25, 1, '$\\ast$')
fig.tight_layout()
plt.savefig('wear-distribution.svg', bbox_inches="tight")

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wear-distribution.svg Normal file
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