dividing logs and building charts for cpu and memory consumption

graphs/cpu.py → graphs/cpu-core-mono.py

@@ -4,31 +4,16 @@
 
 files = [
     [
-        "../logs/oai/oai/iperf/cpu-ran.csv",
-        "../logs/srsran/oai/iperf/cpu-ran.csv",
+        "../logs/oai/oaicn/mono/cpu.csv",
+        "../logs/srsran/oaicn/mono/cpu.csv",
     ],
     [
-        "../logs/oai/open5gs/iperf/cpu-ran.csv",
-        "../logs/srsran/open5gs/iperf/cpu-ran.csv",
+        "../logs/oai/open5gs/mono/cpu.csv",
+        "../logs/srsran/open5gs/mono/cpu.csv",
     ],
     [
-        "../logs/oai/free5gc/iperf/cpu-ran.csv",
-        "../logs/srsran/free5gc/iperf/cpu-ran.csv",
-    ],
-]
-# how many samples to skip until the start of the experiment
-skip = [
-    [
-        15,
-        10,
-    ],
-    [
-        19,
-        14,
-    ],
-    [
-        14,
-        19,
+        "../logs/oai/free5gc/mono/cpu.csv",
+        "../logs/srsran/free5gc/mono/cpu.csv",
     ],
 ]
 
@@ -41,25 +26,25 @@
 ]
 
 def conv(x):
-    return float(x[:-1])
+    return float(x)*100
 
-def readfile(file: str, skip: int):
-    data = np.genfromtxt(file, delimiter=",", skip_header=skip, max_rows=40, usecols=[2], converters={2: conv})
+def readfile(file: str):
+    data = np.genfromtxt(file, delimiter=",", max_rows=11, usecols=[2], converters={2: conv})
     return data
 
 
 def build(save=True):
     # there are 40 measurements total. They were taken every 15s
     # so in total the test lasted 600s
-    x = np.arange(40) * 15 # the label locations
+    x = np.arange(11) * 30 # the label locations
 
     colors = ["#7EA16B", "#C3D898"]
     fig, axes = plt.subplots(1, 3, layout='constrained')
 
-    for tests, offsets, ax, core in zip(files, skip, axes, cores):
-        ax.set_ylim(0, 12)
-        for ran, color, test, offset in zip(rans, colors, tests, offsets):
-            data = readfile(test, offset)
+    for tests, ax, core in zip(files, axes, cores):
+        ax.set_ylim(0, 8)
+        for ran, color, test in zip(rans, colors, tests):
+            data = readfile(test)
             rects = ax.plot(x, data, label=ran, color=color)
         ax.set_xlabel(core, fontsize=12)
 

graphs/cpu-core-split.py

@@ -0,0 +1,66 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+
+files = [
+    [
+        "../logs/oai/oaicn/split/cpu.csv",
+        "../logs/srsran/oaicn/split/cpu.csv",
+    ],
+    [
+        "../logs/oai/open5gs/split/cpu.csv",
+        "../logs/srsran/open5gs/split/cpu.csv",
+    ],
+    [
+        "../logs/oai/free5gc/split/cpu.csv",
+        "../logs/srsran/free5gc/split/cpu.csv",
+    ],
+]
+
+rans = ["OAI RAN", "srsRAN"]
+
+cores = [
+    "OAI CN",
+    "Open5GS",
+    "Free5GC",
+]
+
+def conv(x):
+    return float(x)*100
+
+def readfile(file: str):
+    data = np.genfromtxt(file, delimiter=",", max_rows=11, usecols=[2], converters={2: conv})
+    return data
+
+
+def build(save=True):
+    # there are 40 measurements total. They were taken every 15s
+    # so in total the test lasted 600s
+    x = np.arange(11) * 30 # the label locations
+
+    colors = ["#7EA16B", "#C3D898"]
+    fig, axes = plt.subplots(1, 3, layout='constrained')
+
+    for tests, ax, core in zip(files, axes, cores):
+        ax.set_ylim(0, 8)
+        for ran, color, test in zip(rans, colors, tests):
+            data = readfile(test)
+            rects = ax.plot(x, data, label=ran, color=color)
+        ax.set_xlabel(core, fontsize=12)
+
+# Add some text for labels, title and custom x-axis tick labels, etc.
+    fig.supylabel('CPU Utilization (%)', fontsize=14)
+#axes[len(axes)//2].set_xlabel("Tempo (s)", fontsize=14)
+    axes[-1].legend(loc='upper right', ncols=2, fontsize=12)
+    fig.supxlabel("Time (s)", fontsize=14)
+
+#fig.set_tight_layout()
+    fig.set_size_inches(10.4, 4.2)
+#plt.show()
+    if save:
+        fig.savefig("figs/cpu.pdf", dpi=100)
+
+if __name__ == "__main__":
+    build(False)
+    mpl.use('QtAgg') 
+    plt.show()

graphs/cpu-mono.py

@@ -0,0 +1,66 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+
+files = [
+    [
+        "../logs/oai/oaicn/mono/cpu-gnb.csv",
+        "../logs/srsran/oaicn/mono/cpu-gnb.csv",
+    ],
+    [
+        "../logs/oai/open5gs/mono/cpu-gnb.csv",
+        "../logs/srsran/open5gs/mono/cpu-gnb.csv",
+    ],
+    [
+        "../logs/oai/free5gc/mono/cpu-gnb.csv",
+        "../logs/srsran/free5gc/mono/cpu-gnb.csv",
+    ],
+]
+
+rans = ["OAI RAN", "srsRAN"]
+
+cores = [
+    "OAI CN",
+    "Open5GS",
+    "Free5GC",
+]
+
+def conv(x):
+    return float(x)*100
+
+def readfile(file: str):
+    data = np.genfromtxt(file, delimiter=",", max_rows=11, usecols=[2], converters={2: conv})
+    return data
+
+
+def build(save=True):
+    # there are 40 measurements total. They were taken every 15s
+    # so in total the test lasted 600s
+    x = np.arange(11) * 30 # the label locations
+
+    colors = ["#7EA16B", "#C3D898"]
+    fig, axes = plt.subplots(1, 3, layout='constrained')
+
+    for tests, ax, core in zip(files, axes, cores):
+        ax.set_ylim(0, 16)
+        for ran, color, test in zip(rans, colors, tests):
+            data = readfile(test)
+            rects = ax.plot(x, data, label=ran, color=color)
+        ax.set_xlabel(core, fontsize=12)
+
+# Add some text for labels, title and custom x-axis tick labels, etc.
+    fig.supylabel('CPU Utilization (%)', fontsize=14)
+#axes[len(axes)//2].set_xlabel("Tempo (s)", fontsize=14)
+    axes[-1].legend(loc='upper right', ncols=2, fontsize=12)
+    fig.supxlabel("Time (s)", fontsize=14)
+
+#fig.set_tight_layout()
+    fig.set_size_inches(10.4, 4.2)
+#plt.show()
+    if save:
+        fig.savefig("figs/cpu.pdf", dpi=100)
+
+if __name__ == "__main__":
+    build(False)
+    mpl.use('QtAgg') 
+    plt.show()

graphs/cpu-split-cu.py

@@ -0,0 +1,66 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+
+files = [
+    [
+        "../logs/oai/oaicn/split/cpu-cu.csv",
+        "../logs/srsran/oaicn/split/cpu-cu.csv",
+    ],
+    [
+        "../logs/oai/open5gs/split/cpu-cu.csv",
+        "../logs/srsran/open5gs/split/cpu-cu.csv",
+    ],
+    [
+        "../logs/oai/free5gc/split/cpu-cu.csv",
+        "../logs/srsran/free5gc/split/cpu-cu.csv",
+    ],
+]
+
+rans = ["OAI RAN", "srsRAN"]
+
+cores = [
+    "OAI CN",
+    "Open5GS",
+    "Free5GC",
+]
+
+def conv(x):
+    return float(x)*100
+
+def readfile(file: str):
+    data = np.genfromtxt(file, delimiter=",", max_rows=11, usecols=[2], converters={2: conv})
+    return data
+
+
+def build(save=True):
+    # there are 40 measurements total. They were taken every 15s
+    # so in total the test lasted 600s
+    x = np.arange(11) * 30 # the label locations
+
+    colors = ["#7EA16B", "#C3D898"]
+    fig, axes = plt.subplots(1, 3, layout='constrained')
+
+    for tests, ax, core in zip(files, axes, cores):
+        ax.set_ylim(0, 1)
+        for ran, color, test in zip(rans, colors, tests):
+            data = readfile(test)
+            rects = ax.plot(x, data, label=ran, color=color)
+        ax.set_xlabel(core, fontsize=12)
+
+# Add some text for labels, title and custom x-axis tick labels, etc.
+    fig.supylabel('CPU Utilization (%)', fontsize=14)
+#axes[len(axes)//2].set_xlabel("Tempo (s)", fontsize=14)
+    axes[-1].legend(loc='upper right', ncols=2, fontsize=12)
+    fig.supxlabel("Time (s)", fontsize=14)
+
+#fig.set_tight_layout()
+    fig.set_size_inches(10.4, 4.2)
+#plt.show()
+    if save:
+        fig.savefig("figs/cpu.pdf", dpi=100)
+
+if __name__ == "__main__":
+    build(False)
+    mpl.use('QtAgg') 
+    plt.show()

graphs/cpu-split-du.py

@@ -0,0 +1,66 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+
+files = [
+    [
+        "../logs/oai/oaicn/split/cpu-du.csv",
+        "../logs/srsran/oaicn/split/cpu-du.csv",
+    ],
+    [
+        "../logs/oai/open5gs/split/cpu-du.csv",
+        "../logs/srsran/open5gs/split/cpu-du.csv",
+    ],
+    [
+        "../logs/oai/free5gc/split/cpu-du.csv",
+        "../logs/srsran/free5gc/split/cpu-du.csv",
+    ],
+]
+
+rans = ["OAI RAN", "srsRAN"]
+
+cores = [
+    "OAI CN",
+    "Open5GS",
+    "Free5GC",
+]
+
+def conv(x):
+    return float(x)*100
+
+def readfile(file: str):
+    data = np.genfromtxt(file, delimiter=",", max_rows=11, usecols=[2], converters={2: conv})
+    return data
+
+
+def build(save=True):
+    # there are 40 measurements total. They were taken every 15s
+    # so in total the test lasted 600s
+    x = np.arange(11) * 30 # the label locations
+
+    colors = ["#7EA16B", "#C3D898"]
+    fig, axes = plt.subplots(1, 3, layout='constrained')
+
+    for tests, ax, core in zip(files, axes, cores):
+        ax.set_ylim(0, 16)
+        for ran, color, test in zip(rans, colors, tests):
+            data = readfile(test)
+            rects = ax.plot(x, data, label=ran, color=color)
+        ax.set_xlabel(core, fontsize=12)
+
+# Add some text for labels, title and custom x-axis tick labels, etc.
+    fig.supylabel('CPU Utilization (%)', fontsize=14)
+#axes[len(axes)//2].set_xlabel("Tempo (s)", fontsize=14)
+    axes[-1].legend(loc='upper right', ncols=2, fontsize=12)
+    fig.supxlabel("Time (s)", fontsize=14)
+
+#fig.set_tight_layout()
+    fig.set_size_inches(10.4, 4.2)
+#plt.show()
+    if save:
+        fig.savefig("figs/cpu.pdf", dpi=100)
+
+if __name__ == "__main__":
+    build(False)
+    mpl.use('QtAgg') 
+    plt.show()

graphs/ram-core-mono.py

@@ -0,0 +1,51 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+
+mpl.use('QtAgg') 
+files = [
+    "../logs/oai/oaicn/mono/mem.csv",
+    "../logs/oai/open5gs/mono/mem.csv",
+    "../logs/oai/free5gc/mono/mem.csv",
+    "../logs/srsran/oaicn/mono/mem.csv",
+    "../logs/srsran/open5gs/mono/mem.csv",
+    "../logs/srsran/free5gc/mono/mem.csv",
+]
+# how many samples to skip until the start of the experiment
+labels = [
+        "OAI CN",
+        "Open5Gs",
+        "Free5Gc",
+]
+
+rans = ["OAI", "srsRAN"]
+
+def conv(x):
+    return int(x)/1024/1024/1024
+
+def readfile(file: str):
+    data = np.genfromtxt(file, delimiter=",", max_rows=11, usecols=[2], converters={2: conv})
+    return np.average(data)
+
+
+x = np.arange(len(labels))  # the label locations
+width = 0.33  # the width of the bars
+multiplier = 0
+
+colors = ["#7EA16B", "#C3D898"]
+fig, ax = plt.subplots(layout='constrained')
+
+for i in range(len(rans)):
+    offset = width * multiplier
+    data = (readfile(files[i]), readfile(files[i+2]), readfile(files[i+4]))
+    rects = ax.bar(x + offset, data, width, label=rans[i], color=colors[i])
+    ax.bar_label(rects, padding=2)
+    multiplier += 1
+
+# Add some text for labels, title and custom x-axis tick labels, etc.
+ax.set_ylabel('Comsumo de memória no núcleo (GB)', fontsize=14)
+ax.set_xticks(x + width/2, labels, fontsize=12)
+ax.set_ylim(0, 4)
+ax.legend(loc='upper right', ncols=2, fontsize=12)
+
+plt.show()