Move the DIS benchmarks up a directory and update hardcoded paths

Note that this repo does not attempt to keep a copy of the original
DIS benchmark distributions. UNC real-time has another repo for that.

1 files changed, 71 insertions, 0 deletions

diff --git a/dis/summarize.py b/dis/summarize.py
new file mode 100755
index 0000000..f8f6929
--- /dev/null
+++ b/dis/summarize.py
@@ -0,0 +1,71 @@
+#!/usr/bin/python3
+import sys
+
+f = sys.argv[1]
+res = {}
+mem_res = {}
+memw_res = {}
+samples = {}
+max_res = {}
+
+with open(f) as fp:
+    for line in fp:
+        s = line.split()
+        if s[0] not in res:
+#            print(s[0])
+            res[s[0]] = list([int(s[5])])#)int(s[5])
+            mem_res[s[0]] = int(s[8])
+            memw_res[s[0]] = int(s[9])
+            samples[s[0]] = int(s[4])
+            max_res[s[0]] = int(s[5])
+        else:
+            res[s[0]].append(int(s[5]))
+            mem_res[s[0]] += int(s[8])
+            memw_res[s[0]] += int(s[9])
+            max_res[s[0]] = max(int(s[5]), max_res[s[0]])
+## {{{ http://code.activestate.com/recipes/511478/ (r1)
+import math
+import functools
+
+def percentile(N, percent, key=lambda x:x):
+    """
+    Find the percentile of a list of values.
+
+    @parameter N - is a list of values. Note N MUST BE already sorted.
+    @parameter percent - a float value from 0.0 to 1.0.
+    @parameter key - optional key function to compute value from each element of N.
+
+    @return - the percentile of the values
+    """
+    if not N:
+        return None
+    k = (len(N)-1) * percent
+    f = math.floor(k)
+    c = math.ceil(k)
+    if f == c:
+        return key(N[int(k)])
+    d0 = key(N[int(f)]) * (c-k)
+    d1 = key(N[int(c)]) * (k-f)
+    return d0+d1
+## end of http://code.activestate.com/recipes/511478/ }}}
+"""
+print("Average times:")
+for r in res.keys():
+    print(res[r]/samples[r])
+
+print("Average memory read:")
+for r in mem_res.keys():
+    print(mem_res[r]/samples[r])
+
+print("Average memory write:")
+for r in memw_res.keys():
+    print(memw_res[r]/samples[r])
+
+print("Max times:")
+for r in max_res.keys():
+    print(max_res[r])
+"""
+print("Name\t\tAverage\t\tMax\t\t99th %\t\tAvg Mem Read\tAvg Mem Write\t")
+for r in res.keys():
+#    print(r + "\t\t" + str(res[r]/samples[r]) + "\t\t" + str(max_res[r]))
+    print("{:12}\t{:>12.0f}\t{:>12.0f}\t{:>12.0f}\t{:>12.0f}\t{:>12.0f}".format(r, sum(res[r])/len(res[r]), max(res[r]), percentile(sorted(res[r]), 0.99), mem_res[r]/samples[r], memw_res[r]/samples[r]))