Update latency numbers for camera2

Makefile

@@ -17,11 +17,11 @@ paper.pdf: paper.tex literature.bib $(FIGURES)
 figures/intra-copy.pdf:
 	@cd data && python intra-copy.py ../figures/intra-copy.pdf
 
-figures/latency.pdf: data/ipedirectgma/ipedirectgma.cpu.txt data/ipedirectgma/ipedirectgma.gpu.txt data/ipedirectgma/plot.py
-	@cd data/ipedirectgma && python plot.py && cp latency.pdf ../../figures
+figures/latency.pdf: data/latency/ipedirectgma.cpu.txt data/latency/ipedirectgma.gpu.txt data/latency/plot.py
+	@cd data/latency && python plot.py && cp latency.pdf ../../figures
 
-figures/latency-hist.pdf: data/ipedirectgma/ipedirectgma.1024.cpu.txt data/ipedirectgma/ipedirectgma.1024.gpu.txt data/ipedirectgma/latency-hist.py
-	@cd data/ipedirectgma && python latency-hist.py && cp latency-hist.pdf ../../figures
+figures/latency-hist.pdf: data/latency/ipedirectgma.1024.cpu.txt data/latency/ipedirectgma.1024.gpu.txt data/latency/latency-hist.py
+	@cd data/latency && python latency-hist.py && cp latency-hist.pdf ../../figures
 
 figures/throughput.pdf: data/throughput.cpu data/throughput.gpu data/throughput.py
 	@cd data && python throughput.py && cp throughput.pdf ../figures

data/ipedirectgma/plot.py

@@ -1,62 +0,0 @@
-# -*- coding: utf-8 -*-
-
-import numpy as np
-import matplotlib.pyplot as plt
-from mpl_toolkits.axes_grid.axislines import Subplot
-
-c = np.loadtxt('ipedirectgma.cpu.txt')
-g = np.loadtxt('ipedirectgma.gpu.txt')
-
-
-xs = np.arange(128, 4096 + 128, 128)
-yscm, yscs = [], []
-ysgm, ysgs = [], []
-
-def get_mean_std(data, size):
-    s = data[np.where(data[:,0] == size)][:,1]
-
-    # remove 2x std outliers
-    std = np.std(s)
-    outliers = s[np.abs(s - np.mean(s)) > 4 * np.std(s)]
-    s = s[np.abs(s - np.mean(s)) < 4 * np.std(s)]
-    return np.mean(s), np.std(s)
-
-
-for i in range(128, 4096 + 128, 128):
-    cm, cs = get_mean_std(c, i)
-    yscm.append(cm)
-    yscs.append(cs)
-    gm, gs = get_mean_std(g, i)
-    ysgm.append(gm)
-    ysgs.append(gs)
-
-
-#plt.rc('font', **dict(family='serif'))
-
-fig = plt.figure(1, (4,3))
-ax = Subplot(fig, 111)
-fig.add_subplot(ax)
-
-# plt.figure(figsize=(4, 4))
-plt.xlabel('Packet size in (B)')
-plt.ylabel('Latency (us)')
-# plt.errorbar(xs, yscm, yerr=yscs, label='CPU')
-# plt.errorbar(xs, ysgm, ls='dotted', yerr=ysgs, label='GPU')
-ax.plot(xs, ysgm, 'x-', label='GPU memory', color='#3b5b92')
-ax.plot(xs, yscm, 'o-', markersize=4, label='Main memory', color='#77DD77')
-plt.xticks([128, 1024, 2048, 2048+1024, 4096])
-plt.yticks([2,4,6,8])
-plt.xlim(0, 4200)
-ax.axis["right"].set_visible(False)
-ax.axis["top"].set_visible(False)
-plt.legend(loc='upper left', frameon=False)
-plt.savefig('latency.pdf', dpi=300, bbox_inches='tight')
-
-
-A = np.vstack([xs, np.ones(len(xs))]).T
-mc, cc = np.linalg.lstsq(A, yscm)[0]
-
-mg, cg = np.linalg.lstsq(A, ysgm)[0]
-
-print 100000000/ (100000000 * mc + cc)
-print 100000000/ (100000000 * mg + cg)

data/latency/ipecamera2.cpu.txt

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data/latency/plot.py

@@ -0,0 +1,68 @@
+# -*- coding: utf-8 -*-
+
+import numpy as np
+import matplotlib.pyplot as plt
+from mpl_toolkits.axes_grid.axislines import Subplot
+
+
+def get_mean_std(data, size):
+    s = data[np.where(data[:,0] == size)][:,1]
+
+    # remove 2x std outliers
+    std = np.std(s)
+    outliers = s[np.abs(s - np.mean(s)) > 4 * np.std(s)]
+    s = s[np.abs(s - np.mean(s)) < 4 * np.std(s)]
+    return np.mean(s), np.std(s)
+
+
+def read_data(fname):
+    data = np.loadtxt(fname)
+    ymean = []
+    ystd = []
+
+    for i in range(128, 4096 + 128, 128):
+        m, s = get_mean_std(data, i)
+        ymean.append(m)
+        ystd.append(s)
+
+    return ymean, ystd
+
+
+xs = np.arange(128, 4096 + 128, 128)
+dgma_cpu_mean, dgma_cpu_std = read_data('ipedirectgma.cpu.txt')
+dgma_gpu_mean, dgma_gpu_std = read_data('ipedirectgma.gpu.txt')
+cam2_cpu_mean, cam2_cpu_std = read_data('ipecamera2.cpu.txt')
+cam2_gpu_mean, cam2_gpu_std = read_data('ipecamera2.gpu.txt')
+
+
+plt.rc('font', **dict(family='serif'))
+
+fig = plt.figure(1, (4,3))
+ax = Subplot(fig, 111)
+fig.add_subplot(ax)
+
+plt.xlabel('Packet size in (B)')
+plt.ylabel('Latency (us)')
+
+ax.plot(xs, dgma_gpu_mean, 'x-', label='GPU memory (embedded)', color='#3b5b92')
+ax.plot(xs, dgma_cpu_mean, 'o-', markersize=4, label='Main memory (embedded)', color='#77DD77')
+
+ax.plot(xs, cam2_gpu_mean, '.-', label='GPU memory (workstation)', color='#3b5b92')
+ax.plot(xs, cam2_cpu_mean, '*-', markersize=4, label='Main memory (workstation)', color='#77DD77')
+
+plt.xticks([128, 1024, 2048, 2048+1024, 4096])
+# plt.yticks([2,4,6,8])
+plt.xlim(0, 4200)
+ax.axis["right"].set_visible(False)
+ax.axis["top"].set_visible(False)
+plt.legend(loc='upper left', frameon=False)
+plt.savefig('latency.pdf', dpi=300, bbox_inches='tight')
+
+
+# A = np.vstack([xs, np.ones(len(xs))]).T
+# mc, cc = np.linalg.lstsq(A, yscm)[0]
+
+# mg, cg = np.linalg.lstsq(A, ysgm)[0]
+
+# print 100000000/ (100000000 * mc + cc)
+# print 100000000/ (100000000 * mg + cg)