workload: support multiple energy models, show energy distribution between models

1 files changed, 56 insertions, 30 deletions

diff --git a/bin/workload.py b/bin/workload.py
index c9d4e76..c0a03c7 100755
--- a/bin/workload.py
+++ b/bin/workload.py
@@ -5,39 +5,65 @@ import sys
 from utils import human_readable
 from lex import TimedSequence, TimedWord, Workload
 
-ptafile, raw_word = sys.argv[1:]
+args = sys.argv[1:]
 
 # TODO loops im raw_word:
 # init(); repeat { foo(); sleep(5m); bar(); ... } o.ä.
 # - Zeitangaben mit Einheit in sleep
 # - Ausgabe in Gesamt, Init und Schleifeninhalt aufdröseln
 
-pta = PTA.from_file(ptafile)
-timedword = TimedSequence(raw_word)
-
-print('Input: {}\n'.format(timedword))
-
-prev_state = 'UNINITIALIZED'
-prev_param = None
-for trace_part in timedword:
-    print('Trace Part {}'.format(trace_part))
-    if type(trace_part) is TimedWord:
-        result = pta.simulate(trace_part, orig_state=prev_state, orig_param=prev_param)
-    elif type(trace_part) is Workload:
-        result = pta.simulate(trace_part.word, orig_state=prev_state, orig_param=prev_param)
-        if prev_state != result.end_state:
-            print('Warning: loop starts in state {}, but terminates in {}'.format(prev_state, result.end_state.name))
-        if prev_param != result.parameters:
-            print('Warning: loop starts with parameters {}, but terminates with {}'.format(prev_param, result.parameters))
-
-    print('    Duration: ' + human_readable(result.duration, 's'))
-    if result.duration_mae:
-        print(u'    ± {}  /  {:.0f}%'.format(human_readable(result.duration_mae, 's'), result.duration_mape))
-    print('    Energy: ' + human_readable(result.energy, 'J'))
-    if result.energy_mae:
-        print(u'    ± {}  /  {:.0f}%'.format(human_readable(result.energy_mae, 'J'), result.energy_mape))
-    print('    Mean Power: ' + human_readable(result.mean_power, 'W'))
-    print('')
-
-    prev_state = result.end_state
-    prev_param = result.parameters
+loops = dict()
+ptafiles = list()
+loop_names = set()
+
+
+def simulate_word(timedword):
+    prev_state = 'UNINITIALIZED'
+    prev_param = None
+    ret = dict()
+    for trace_part in timedword:
+        print('Trace Part {}'.format(trace_part))
+        if type(trace_part) is TimedWord:
+            result = pta.simulate(trace_part, orig_state=prev_state, orig_param=prev_param)
+        elif type(trace_part) is Workload:
+            result = pta.simulate(trace_part.word, orig_state=prev_state, orig_param=prev_param)
+            if prev_state != result.end_state:
+                print('Warning: loop starts in state {}, but terminates in {}'.format(prev_state, result.end_state.name))
+            if prev_param != result.parameters:
+                print('Warning: loop starts with parameters {}, but terminates with {}'.format(prev_param, result.parameters))
+            ret[trace_part.name] = result
+            loop_names.add(trace_part.name)
+
+        print('    Duration: ' + human_readable(result.duration, 's'))
+        if result.duration_mae:
+            print(u'    ± {}  /  {:.0f}%'.format(human_readable(result.duration_mae, 's'), result.duration_mape))
+        print('    Energy: ' + human_readable(result.energy, 'J'))
+        if result.energy_mae:
+            print(u'    ± {}  /  {:.0f}%'.format(human_readable(result.energy_mae, 'J'), result.energy_mape))
+        print('    Mean Power: ' + human_readable(result.mean_power, 'W'))
+        print('')
+
+        prev_state = result.end_state
+        prev_param = result.parameters
+
+    return ret
+
+
+for i in range(len(args) // 2):
+    ptafile, raw_word = args[i * 2], args[i * 2 + 1]
+    ptafiles.append(ptafile)
+    pta = PTA.from_file(ptafile)
+    timedword = TimedSequence(raw_word)
+    print('Input: {}\n'.format(timedword))
+    loops[ptafile] = simulate_word(timedword)
+
+for loop_name in sorted(loop_names):
+    result_set = list()
+    total_power = 0
+    for ptafile in sorted(ptafiles):
+        if loop_name in loops[ptafile]:
+            result_set.append(loops[ptafile][loop_name])
+            total_power += loops[ptafile][loop_name].mean_power
+    print('{}: total mean power is {}'.format(loop_name, human_readable(total_power, 'W')))
+    for i, result in enumerate(result_set):
+        print('    {:.0f}% {} (period: {})'.format(result.mean_power * 100 / total_power, ptafiles[i], human_readable(result.duration, 's')))