tools: sof_perf_analyzer: change module CPC calculation

In daily performance test, we have a high and abnormal peak
cycle for some module, recently, we find this abnormal peak
cycle is caused by IRQ.

Previously, module CPC is calculated by multiplying the mean
value of cpu_peak with a margin scalar. With further team
discussion based on the new finding, an agreement is reached
to use the product of module average cycle and a margin as
module CPC.

Signed-off-by: Baofeng Tian <[email protected]>

tools/sof_perf_analyzer.py

@@ -27,8 +27,14 @@
 
 import pandas as pd
 
-# currently, keep CPC = max(module peak) * CPC_MARGIN
-CPC_MARGIN = 1.1
+# CPC_MARGIN is set to 1.5, because there is some inactive code for some module
+# due to unmet condition. For example:
+# volume: ramp operation only run on volume change, but we don't do volume
+# change in our test.
+
+# So, we set a relative high margin for avg cycles.
+# CPC = AVG(module) * CPC_MARGIN
+CPC_MARGIN = 1.5
 
 @dataclass()
 class TraceItem:
@@ -243,7 +249,7 @@ def analyze_perf_info():
     perf_stats.columns = ['CPU_AVG(MIN)', 'CPU_AVG(AVG)', 'CPU_AVG(MAX)',
                           'CPU_PEAK(MIN)', 'CPU_PEAK(AVG)', 'CPU_PEAK(MAX)']
     perf_stats['PEAK(MAX)/AVG(AVG)'] = perf_stats['CPU_PEAK(MAX)'] / perf_stats['CPU_AVG(AVG)']
-    perf_stats['MODULE_CPC'] = perf_info.groupby('COMP_ID')['CPU_PEAK'].max() * CPC_MARGIN
+    perf_stats['MODULE_CPC'] = perf_info.groupby('COMP_ID')['CPU_AVG'].mean() * CPC_MARGIN
     # change data type from float to int
     perf_stats['MODULE_CPC'] = perf_stats['MODULE_CPC'].astype(int)