bench 2.7

Benchmark resources usage

Monitor Process Resources Usage

Bench aims to be a handy tool with these functions:

- Monitor CPU time (user time, sys time, real time)

- Monitor memory usage (vms usage, rss usage)

- Output to TSV(tab-delimited files)

- Output benchmarking metrics

- Visualize benchmarking over time

Examples

We showed several examples below. Please note that all output are tabularized manually.

• Example 1: simple command

  $> monitor.py sleep 2

  pid ppid utime stime rtime rss vms maxRss maxVms avgRss avgVms cwd cmd

  133692 133675 0.0 0.0 1.9368159771 774144 6066176 774144 6066176 774144.0 6066176.0 /home/zhanxw/mycode/bench/scripts sleep 2

• Example 2: complex shell commands with samping interval equaing 0.5 second

  $> monitor.py sh -c ‘sleep 2 & sleep 4 & seq 1000000 >/dev/null & wait’

  pid ppid utime stime rtime rss vms maxRss maxVms avgRss avgVms cwd cmd

  135004 134985 0.0 0.0 3.9532430172 798720 4558848 798720 4558848 798720.0 4558848.0 /home/zhanxw/mycode/bench/scripts sh -c sleep 2 & sleep 4 & seq 10000000 >/dev/null & wait

  135006 135004 0.0 0.0 3.95348381996 655360 6066176 655360 6066176 655360.0 6066176.0 /home/zhanxw/mycode/bench/scripts sleep 4

  135005 135004 0.0 0.0 1.83160495758 774144 6066176 774144 6066176 774144.0 6066176.0 /home/zhanxw/mycode/bench/scripts sleep 2

  135007 135004 0.05 0.0 0.0599648952484 720896 6090752 720896 6090752 720896.0 6090752.0 /home/zhanxw/mycode/bench/scripts seq 10000000

• Example 3: generate benmarking metrics to external file

The small program, burnCpu, will keep CPU running for several seconds. Its source code is under src/.

$> monitor.py -t -o burnCpu ./burnCpu
pid     ppid    utime  stime  rtime            rss      vms       cwd                                cmd
135471  135454  0.04   0.0    0.0441780090332  1449984  12984320  /home/zhanxw/mycode/bench/scripts  ../src/burnCpu
135471  135454  0.2    0.0    0.205282926559   1449984  12984320  /home/zhanxw/mycode/bench/scripts  ../src/burnCpu
135471  135454  0.38   0.0    0.381079912186   1449984  12984320  /home/zhanxw/mycode/bench/scripts  ../src/burnCpu
...

Additional result are stored in burnCpu.csv, burnCpu.trace.csv in the Comma-separated format (CSV).

burnCpu.csv content

pid,ppid,utime,stime,rtime,rss,vms,maxRss,maxVms,avgRss,avgVms,cwd,cmd
144433,144416,5.4,0.0,5.40555810928,1404928,12984320,1404928,12984320,1404928.0,12984320.0,/home/zhanxw/mycode/bench/scripts,../src/burnCpu

burnCpu.trace.csv content

pid,ppid,utime,stime,rtime,rss,vms,cwd,cmd
144433,144416,0.03,0.0,0.0423669815063,1404928,12984320,/home/zhanxw/mycode/bench/scripts,../src/burnCpu
144433,144416,0.19,0.0,0.20046210289,1404928,12984320,/home/zhanxw/mycode/bench/scripts,../src/burnCpu
144433,144416,0.36,0.0,0.373480081558,1404928,12984320,/home/zhanxw/mycode/bench/scripts,../src/burnCpu
...

By using the trace output file, burnCpu.trace.csv, you can draw benchmarking graphs, such as:

Notes

Shell (/bin/sh) can be used to execute commands. You can use “sh -c ‘command arg1 arg2 … ‘” (see Example 2).

Bench requires psutil to collect basic benchmarking metrics, and

requires numpy and pandas for statistical calculations. We used psutil version 3.1.1 in development.

Contact

Xiaowei Zhan<zhanxw[at]gmail.com