From 92df3dcae6747e4410574e7bf1f14dd1c07c3471 Mon Sep 17 00:00:00 2001
From: leochanj105 <leochanj@live.unc.edu>
Date: Fri, 29 Oct 2021 03:40:38 -0400
Subject: tmp 10/29

---
 smt_analysis/computeSMTslowdown.py | 13 ++++++++++++-
 smt_analysis/libSMT.py             | 10 ++++++----
 2 files changed, 18 insertions(+), 5 deletions(-)

(limited to 'smt_analysis')

diff --git a/smt_analysis/computeSMTslowdown.py b/smt_analysis/computeSMTslowdown.py
index d612ea6..cf09402 100755
--- a/smt_analysis/computeSMTslowdown.py
+++ b/smt_analysis/computeSMTslowdown.py
@@ -81,7 +81,7 @@ for b1 in reliableNames:
             else:
                 if not TIMES_ONLY: print("{:>10}".format("N/A"), end=" ")
 
-            if TIMES_ONLY and (not OK_PAIRS_ONLY or Cj * 10 > Ci):
+            if TIMES_ONLY:# and (not OK_PAIRS_ONLY or Cj * 10 > Ci):
                 print("{:>12}".format(Cij), end=" ")
             elif OK_PAIRS_ONLY and Cj * 10 <= Ci:
                 print("{:>12}".format("0"), end=" ")
@@ -93,6 +93,17 @@ for b1 in reliableNames:
             M_vals.append(M)
             print("{:>10.3}".format(M), end=" ")
     print("")
+
+# Output baselines
+print("Baselines          ", end=" ")
+print()
+# Print rows
+for b1 in reliableNames:
+    print("{:<14.14}:".format(b1), end=" ")
+    Ci = sample_f(baseline_times[b1])
+    print("{:>12}".format(Ci), end=" ")
+    print("")
+
 # Print some statistics about the distribution
 print("Overall average is {:>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)
diff --git a/smt_analysis/libSMT.py b/smt_analysis/libSMT.py
index c0b5178..881ef07 100755
--- a/smt_analysis/libSMT.py
+++ b/smt_analysis/libSMT.py
@@ -17,7 +17,7 @@ def assert_valid_input_files(names, on_fail):
 # @returns max_res May of benchmark to maximum execution time among all samples for that benchmark
 def load_baseline(f):
     # constants for columns of baseline data files
-    TOTAL_NS = 5
+    TOTAL_NS = 9
     BENCH_NAME = 0
     SAMPLES = 4
 
@@ -65,8 +65,8 @@ def load_paired(file1, file2, benchmarkCount):
     START_N = 6 # Start nanoseconds
     END_S = 7   # End seconds
     END_N = 8   # End nanoseconds
-    RUN_ID = 9
-    JOB_NUM = 10
+    RUN_ID = 10
+    JOB_NUM = 11
 
     with open(file1) as f1:
         numJobs = int(f1.readline().split()[TRIALS])
@@ -101,7 +101,9 @@ def load_paired(file1, file2, benchmarkCount):
             end2 = int(lineArr2[END_S]) * 10**9 + int(lineArr2[END_N])
             maxEnd = max(end1, end2)
             # Time actually co-scheduled is minEnd - maxStart, but Sims uses a different model
-            time[bench1][bench2][job_idx] = maxEnd - minStart
+            #time[bench1][bench2][job_idx] = maxEnd - minStart
+            time[bench1][bench2][job_idx] = end1-minStart
+            time[bench2][bench1][job_idx] = end2-minStart
             # Compute offset: if first job starts at t=0, when does second start?
             offset[bench1][bench2][job_idx] = abs(start2-start1)
             # Compute some running statistics
-- 
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