1 files changed, 73 insertions, 0 deletions

diff --git a/smt_analysis/computeLCslowdown.py b/smt_analysis/computeLCslowdown.py
new file mode 100755
index 0000000..bcd22da
--- /dev/null
+++ b/smt_analysis/computeLCslowdown.py
@@ -0,0 +1,73 @@
+#!/usr/bin/python3
+import numpy as np
+import sys
+import plotille.plotille as plt
+from libSMT import *
+TIMING_ERROR = 1000 #ns
+ASYNC_FORMAT = False
+
+def print_usage():
+    print("This program takes in the all-pairs and baseline SMT data and computes the worst-case slowdown against any other task when SMT is enabled.", file=sys.stderr)
+    print("Level-A/B usage: {} <file -A> <file -B> <baseline file>".format(sys.argv[0]), file=sys.stderr)
+    print("Level-C usage: {} <continuous pairs> <baseline file>".format(sys.argv[0]), file=sys.stderr)
+
+# Check that we got the right number of parameters
+if len(sys.argv) < 3:
+    print_usage()
+    exit()
+
+if len(sys.argv) > 3:
+    print("Reading file using synchronous pair format...")
+    print("Are you sure you want to do this? For the RTAS'21 paper, L-A/-B pairs should use the other script.")
+    input("Press enter to continue, Ctrl+C to exit...")
+else:
+    print("Reading file using asynchronous pair format...")
+    ASYNC_FORMAT = True
+
+assert_valid_input_files(sys.argv[1:-1], print_usage)
+
+# Pull in the data
+if not ASYNC_FORMAT:
+    baseline_times, baseline_sample_cnt, baseline_max_times = load_baseline(sys.argv[3])
+    paired_times, paired_offsets, name_to_idx, idx_to_name = load_paired(sys.argv[1], sys.argv[2], len(list(baseline_times.keys())))
+    for key in baseline_times:
+        print(key,max(baseline_times[key]))
+else:
+    baseline_times, baseline_sample_cnt, baseline_max_times = load_baseline(sys.argv[2])
+    paired_times, name_to_idx, idx_to_name = load_fake_paired(sys.argv[1])
+
+# We work iff the baseline was run for the same set of benchmarks as the pairs were
+assert_base_and_pair_keys_match(baseline_times, name_to_idx)
+
+# Only consider benchmarks that are at least an order of magnitude longer than the timing error
+reliableNames = []
+for i in range(0, len(name_to_idx)):
+    benchmark = idx_to_name[i]
+    if min(baseline_times[benchmark]) > TIMING_ERROR * 10:
+        reliableNames.append(benchmark)
+
+# Compute worst-case SMT slowdown for each benchmark
+print("Bench           Mi")
+# Print rows
+sample_f = np.mean # Change this to np.mean to use mean values in Mi generation
+M_vals = []
+for b1 in reliableNames:
+    print("{:<14.14}:".format(b1), end=" ")
+    max_mi = 0
+    # Scan through everyone we ran against and find our maximum slowdown
+    for b2 in reliableNames:
+        time_with_smt = sample_f(paired_times[name_to_idx[b1]][name_to_idx[b2]])
+        time_wout_smt = sample_f(baseline_times[b1])
+        M = time_with_smt / time_wout_smt
+        max_mi = max(max_mi, M)
+    print("{:>10.3}".format(max_mi), end=" ")
+    M_vals.append(max_mi)
+    print("")
+# Print some statistics about the distribution
+print("Average: {:>5.3} with standard deviation {:>5.3} using `{}`".format(np.mean(M_vals), np.std(M_vals), sample_f.__name__))
+Ms = np.asarray(M_vals, dtype=np.float32)
+print(np.sum(Ms <= 1), "of", len(M_vals), "M_i values are at most one -", 100*np.sum(Ms <= 1)/len(M_vals), "percent")
+print(np.sum(Ms > 2), "of", len(M_vals), "M_i values are greater than two -", 100*np.sum(Ms > 2)/len(M_vals), "percent")
+M_vals_to_plot = Ms
+
+print(plt.hist(M_vals_to_plot, bins=10))