From cae4dc18b6d246f140a51dd814d5bb854fb9702f Mon Sep 17 00:00:00 2001
From: Dominic Kempf <dominic.kempf@iwr.uni-heidelberg.de>
Date: Thu, 19 Jan 2017 11:39:30 +0100
Subject: [PATCH] Adjust the process_measurements script
---
bin/process_measurements.py | 27 ++++++++++++---------------
1 file changed, 12 insertions(+), 15 deletions(-)
diff --git a/bin/process_measurements.py b/bin/process_measurements.py
index 945687f9..2790a32e 100755
--- a/bin/process_measurements.py
+++ b/bin/process_measurements.py
@@ -15,36 +15,33 @@ def join_csv_files():
def calculate_floprate():
- frame = pandas.read_csv('timings.csv', header=None, names=('rank', 'exec', 'kernel', 'what', 'value'), delimiter=' ')
+ frame = pandas.read_csv('timings.csv', header=None, names=('rank', 'ident', 'kernel', 'what', 'value'), delimiter=' ')
time = frame[frame.what == "time"]
ops = frame[frame.what != "time"]
- time = time.groupby(('rank', 'exec', 'kernel'))['value'].min().to_frame().reset_index().groupby(('exec', 'kernel'))['value'].max()
- ops = ops.groupby(('rank', 'exec', 'kernel'))['value'].max().to_frame().reset_index().groupby(('exec', 'kernel'))['value'].max()
+ time = time.groupby(('rank', 'ident', 'kernel'))['value'].min().to_frame().reset_index().groupby(('ident', 'kernel'))['value'].max()
+ ops = ops.groupby(('rank', 'ident', 'kernel'))['value'].max().to_frame().reset_index().groupby(('ident', 'kernel'))['value'].max()
with open('floprates.csv', 'w') as out:
for key in time.keys():
- exe, kernel = key
- if "nonopcount" in exe and kernel != "total":
- opexe = exe.replace("nonopcount", "opcount")
- degree = re.match(".*deg([0-9]*).*", exe).group(1)
- out.write(" ".join([exe, degree, kernel, str((ops[opexe][kernel] / time[exe][kernel]) / 1e9)]) + "\n")
+ ident, kernel = key
+ degree = re.match(".*deg([0-9]*).*", ident).group(1)
+ out.write(" ".join([ident, degree, kernel, str((ops[ident][kernel] / time[ident][kernel]) / 1e9)]) + "\n")
def calculate_doftimes():
- frame = pandas.read_csv('timings.csv', header=None, names=('rank', 'exec', 'kernel', 'what', 'value'), delimiter=' ')
+ frame = pandas.read_csv('timings.csv', header=None, names=('rank', 'ident', 'kernel', 'what', 'value'), delimiter=' ')
dofs = frame[frame.what == "dofs"]
time = frame[frame.what == "time"]
- dofs = dofs.groupby(('rank', 'exec', 'kernel'))['value'].max().to_frame().reset_index().groupby(('exec', 'kernel'))['value'].max()
- time = time.groupby(('rank', 'exec', 'kernel'))['value'].min().to_frame().reset_index().groupby(('exec', 'kernel'))['value'].max()
+ dofs = dofs.groupby(('rank', 'ident', 'kernel'))['value'].max().to_frame().reset_index().groupby(('ident', 'kernel'))['value'].max()
+ time = time.groupby(('rank', 'ident', 'kernel'))['value'].min().to_frame().reset_index().groupby(('ident', 'kernel'))['value'].max()
with open('doftimes.csv', 'w') as out:
for key in time.keys():
- exe, kernel = key
- degree = re.match(".*deg([0-9]*).*", exe).group(1)
- if "nonopcount" in exe:
- out.write(" ".join([exe, degree, kernel, str(dofs[exe]["dofs"] / time[exe][kernel] / 1e6)]) + "\n")
+ ident, kernel = key
+ degree = re.match(".*deg([0-9]*).*", ident).group(1)
+ out.write(" ".join([ident, degree, kernel, str(dofs[ident]["dofs"] / time[ident][kernel] / 1e6)]) + "\n")
if __name__ == '__main__':
--
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