Fix generate-dfa-benchmark leaving out benchmark parts when splitting runs

2 files changed, 11 insertions, 8 deletions

diff --git a/bin/analyze-timing.py b/bin/analyze-timing.py
index 7e8174d..465932b 100755
--- a/bin/analyze-timing.py
+++ b/bin/analyze-timing.py
@@ -63,7 +63,7 @@ Options:
 --export-energymodel=<model.json>
     Export energy model. Requires --hwmodel.
 
---filter-param=<parameter name>=<parameter value>
+--filter-param=<parameter name>=<parameter value>[,<parameter name>=<parameter value>...]
     Only consider measurements where <parameter name> is <parameter value>
     All other measurements (including those where it is None, that is, has
     not been set yet) are discarded. Note that this may remove entire
@@ -192,7 +192,9 @@ if __name__ == '__main__':
             opts['corrcoef'] = False
 
         if 'filter-param' in opts:
-            opts['filter-param'] = opts['filter-param'].split('=')
+            opts['filter-param'] = list(map(lambda x: x.split('='), opts['filter-param'].split(',')))
+        else:
+            opts['filter-param'] = list()
 
     except getopt.GetoptError as err:
         print(err)
@@ -203,9 +205,9 @@ if __name__ == '__main__':
     preprocessed_data = raw_data.get_preprocessed_data()
     by_name, parameters, arg_count = pta_trace_to_aggregate(preprocessed_data, ignored_trace_indexes)
 
-    if 'filter-param' in opts:
-        param_index = parameters.index(opts['filter-param'][0])
-        param_value = soft_cast_int(opts['filter-param'][1])
+    for param_name_and_value in opts['filter-param']:
+        param_index = parameters.index(param_name_and_value[0])
+        param_value = soft_cast_int(param_name_and_value[1])
         names_to_remove = set()
         for name in by_name.keys():
             indices_to_keep = list(map(lambda x: x[param_index] == param_value, by_name[name]['param']))
diff --git a/bin/generate-dfa-benchmark.py b/bin/generate-dfa-benchmark.py
index 4fb8df4..9919d68 100755
--- a/bin/generate-dfa-benchmark.py
+++ b/bin/generate-dfa-benchmark.py
@@ -136,9 +136,10 @@ def run_benchmark(application_file: str, pta: PTA, runs: list, arch: str, app: s
     if needs_split:
         print('[MAKE] benchmark code is too large, splitting up')
         mid = len(runs) // 2
-        results = run_benchmark(application_file, pta, runs[:mid], arch, app, run_args, harness, sleep, repeat, run_offset = run_offset, runs_total = runs_total)
+        # Previously prepared trace data is useless
         harness.reset()
-        results.extend(run_benchmark(application_file, pta, runs[mid:], arch, app, run_args, harness, sleep, repeat, run_offset = run_offset + mid, runs_total = runs_total))
+        results = run_benchmark(application_file, pta, runs[:mid], arch, app, run_args, harness.copy(), sleep, repeat, run_offset = run_offset, runs_total = runs_total)
+        results.extend(run_benchmark(application_file, pta, runs[mid:], arch, app, run_args, harness.copy(), sleep, repeat, run_offset = run_offset + mid, runs_total = runs_total))
         return results
 
     runner.flash(arch, app, run_args)
@@ -242,7 +243,7 @@ if __name__ == '__main__':
         json_out = {
             'opt' : opt,
             'pta' : pta.to_json(),
-            'traces' : harness.traces,
+            'traces' : list(map(lambda x: x[1].traces, results)),
             'raw_output' : list(map(lambda x: x[2], results)),
         }
         with open(time.strftime('ptalog-%Y%m%d-%H%M%S.json'), 'w') as f: