Initial plotting support for numa scan

analyze/config.py

@@ -11,3 +11,8 @@ colors = {
   "kernel polling (configuration)": "tab:purple",
   "irq packing": "tab:red",
 }
+
+patterns = {
+  "vanilla": "/",
+  "kernel polling (patched)": ".",
+}

analyze/memcached_numa_scan.py

+import os
+import util
+
+def parse_memcached_output(s):
+    lines = s.split('\n')
+    return int(float(lines[6].split(' ')[3]))
+
+def parse_memcached_stat(s, qps):
+    lines = s.split('\n')
+    inst = 0
+    cycle = 0
+    for line in lines:
+        if line.startswith('#'):
+            continue
+        split = line.strip().split()
+        if len(split) <= 1:
+            continue
+        if int(float(split[0])) != 25:
+            continue
+        if split[2] == 'instructions:u' or split[2] == 'instructions:k':
+            inst += int(split[1].replace(',', ''))
+        if split[2] == 'cycles:u' or split[2] == 'cycles:k':
+            cycle += int(split[1].replace(',', ''))
+    return (float(inst) / 5 / qps, float(inst) / cycle)
+
+def extract_numa_scan_exp(exp):
+    ret = ([], [], [], [], [], []) # QPS_mean, QPS_stddev, IPQ_mean, IPQ_stddev, IPC_mean, IPC_stddev
+
+    for t in [2, 4, 8, 16]:
+        f = 't' + str(t)
+        (qps_mean, qps_stddev) = \
+            util.extract_exp_avg_stddev(exp, f, parse_memcached_output)
+
+        stat = 'stat_' + f
+        ((ipq_mean, ipq_stddev), (ipc_mean, ipc_stddev)) = \
+            util.extract_exp_avg_stddev(exp, stat, parse_memcached_stat, qps_mean)
+
+        ret[0].append(qps_mean)
+        ret[1].append(qps_stddev)
+        ret[2].append(ipq_mean)
+        ret[3].append(ipq_stddev)
+        ret[4].append(ipc_mean)
+        ret[5].append(ipc_stddev)
+
+    return ret
+
+def collect_data(experiments):
+    ret = dict()
+
+    for exp in experiments:
+        ret[exp] = extract_numa_scan_exp(exp)
+
+    return ret

analyze/memcached_numa_scan_qps.py

+import matplotlib.pyplot as plt
+from memcached_numa_scan import collect_data
+import os
+from config import colors, patterns
+
+experiments = [
+    'memcached_numa_scan.5.15.79-peter', # vanilla
+    'memcached_numa_scan.5.15.79-peter.kernel_polling', # kernel_polling
+]
+
+labels = [
+    'vanilla',
+    'kernel polling (patched)',
+]
+
+def plot():
+    data = collect_data(experiments)
+    plt.cla()
+
+    plt.xticks([1, 2, 3, 4], ["1 + 1", "2 + 2", "4 + 4", "8 + 8"])
+    l = len(experiments)
+    for i in range(l):
+        offset = (0.4 * i + 0.2) - 0.4 * l / 2
+        exp = experiments[i]
+        plt.bar([1 + offset, 2 + offset, 3 + offset, 4 + offset], data[exp][0], 0.4, yerr = data[exp][1], capsize=4, label = labels[i], edgecolor = colors[labels[i]], hatch = patterns[labels[i]], fill = False)
+
+    plt.ylabel('Throughput')
+
+    plt.legend()
+    if os.getenv('SAVE_FIGURE') != 'true':
+        plt.rcParams.update({'font.size': 16})
+        plt.show()
+    else:
+        plt.savefig('../data/figs/memcached_numa_scan_qps.png', dpi = 192)
+
+plot()

analyze/util.py

 import os
 import math
 
-def extract_exp_avg_stddev(exp, datapoint, parser):
+def extract_exp_avg_stddev(exp, datapoint, parser, *parser_args):
     def my_parser(f):
         p = os.path.join(os.getcwd(), '../data/', exp, f + '.txt')
 
         if not os.path.exists(p):
             return None
         with open(p, 'r') as fi:
-            return parser(fi.read())
+            return parser(fi.read(), *parser_args)
 
     acc = []
     acc.append(my_parser(datapoint))