Anyone have a clean process for converting samples on macOS to FlameGraphs?
After a bit of fiddling I thought I could perhaps use a tool such as flamegraph-sample, but it seems to give me some trouble and so I thought perhaps there may be other more up-to-date options that I'm missing insomuch that this tool gives an error:
$ sudo sample PID -file ~/tmp/sample.txt -fullPaths 1
Sampling process 198 for 1 second with 1 millisecond of run time between samples
Sampling completed, processing symbols...
Sample analysis of process 35264 written to file ~/tmp/sample.txt
$ python stackcollapse-sample.py ~/tmp/sample.txt > ~/tmp/sample_collapsed.txt
$ flamegraph.pl ~/tmp/sample_collapsed.txt > ~/tmp/sample_collapsed_flamegraph.svg
Ignored 2335 lines with invalid format
ERROR: No stack counts found
Related
I have updated my build environment compiler from gcc 5.5.0 to gcc 9.3.0 and noticed coverage calculation performance regression.
It became 10 times slower (5 hours vs 48 hours for whole project).
My investigation shows that in gcov-9 they started to use json format instead of intermediate text format.
This slowed down intermediate gcov-files creation and parsing.
Minimal example below:
> time geninfo --gcov-tool gcov-5 test5/CPrimitiveLayerTest.cpp.gcno
Found gcov version: 5.5.0
Using intermediate gcov format
Processing test5/CPrimitiveLayerTest.cpp.gcno
Finished .info-file creation
real 0m0.351s
user 0m0.298s
sys 0m0.047s
> time geninfo --gcov-tool gcov-9 test9/CPrimitiveLayerTest.cpp.gcno
Found gcov version: 9.3.0
Using intermediate gcov format
Processing test9/CPrimitiveLayerTest.cpp.gcno
Finished .info-file creation
real 0m8.024s
user 0m7.929s
sys 0m0.084s
I didn't find the way to return to old format but maybe there are any workarounds or patches.
P.S. I know about gcov's argument --json-format, but lcov1.15 can process either json format or so-called intermediate text format. At the same time gcov9 can output either json format or so-called logfile format files
Further investigation shows that this is because of lcov 1.15 uses JSON:PP module for json parsing.
Replacing of JSON:PP to JSON:XS (fast parser) gives required speedup.
So I use next commands to reach it:
# patch geninfo to use fast json parser
> sudo sed -i 's/use JSON::PP/use JSON::XS/g' /usr/local/bin/geninfo
# install perl module
> sudo cpan install JSON:XS
I seem to be having trouble properly combining thousands of netCDF files (42000+) (3gb in size, for this particular folder/variable). The main variable that i want to combine has a structure of (6, 127, 118) i.e (time,lat,lon)
Im appending each file 1 by 1 since the number of files is too long.
I have tried:
for i in input_source/**/**/*.nc; do ncrcat -A -h append_output.nc $i append_output.nc ; done
but this method seems to be really slow (order of kb/s and seems to be getting slower as more files are appended) and is also giving a warning:
ncrcat: WARNING Intra-file non-monotonicity. Record coordinate "forecast_period" does not monotonically increase between (input file file1.nc record indices: 17, 18) (output file file1.nc record indices 17, 18) record coordinate values 6.000000, 1.000000
that basically just increases the variable "forecast_period" 1-6 n-times. n = 42000files. i.e. [1,2,3,4,5,6,1,2,3,4,5,6......n]
And despite this warning i can still open the file and ncrcat does what its supposed to, it is just slow, at-least for this particular method
I have also tried adding in the option:
--no_tmp_fl
but this gives an eror:
ERROR: nco__open() unable to open file "append_output.nc"
full error attached below
If it helps, im using wsl and ubuntu in windows 10.
Im new to bash and any comments would be much appreciated.
Either of these commands should work:
ncrcat --no_tmp_fl -h *.nc
or
ls input_source/**/**/*.nc | ncrcat --no_tmp_fl -h append_output.nc
Your original command is slow because you open and close the output files N times. These commands open it once, fill-it up, then close it.
I would use CDO for this task. Given the huge number of files it is recommended to first sort them on time (assuming you want to merge them along the time axis). After that, you can use
cdo cat *.nc outfile
I want to list all processes running on my Windows system using Ruby without installing any additional dependency or library that is not already part of Ruby. I have not found any way to do this online. Is there any clean way to do this from Ruby?
You can use the Kernal::system method to execute a command line argument. For example:
system("tasklist")
Image Name PID Session Name Session# Mem Usage
========================= ======== ================ =========== ============
System Idle Process 0 Services 0 24 K
...
ruby.exe 1336 Console 1 9,100 K
tasklist.exe 944 Console 1 5,332 K
Alternately--as points #Pavling out--you can use [Kernal::`](aka backtick), but some find it less readable. YMMV.
I am trying to use VTune command line to set maximum number of samples to be collected before the collection stops. For this I have using the -msc command but I get an error saying unknown command.
The command I am using is : "C:\Program Files\Intel\VTune Amplifier XE 2015\bin32\amplxe-cl" -collect general-exploration --duration 30 -msc 300
The above command gives me "Unknown command -msc" error
How can I solve this issue.
VTune command line tool can't do what you requested. VTune can't limit collection time based on number of collected samples
I can suggest to decrease collection time (-duration) or decrease amount of data to be collected using -data-limit option.
BTW
The list of supported options can be obtained by following command
amplxe-cl -help collect
List of supported analysis type specific knobs can be obtained this way
amplxe-cl -help collect general-exploration
For some reason I am having trouble with the make test statement while installing ```Vowpal Wabbit``. I am getting the following error:
RunTests: test 59: '/usr/bin/timeout 20 ../vowpalwabbit/vw -d train-sets/argmax_data -k -c --passes 20 --search_rollout oracle --search_alpha 1e-8 --search_task argmax --search 2 --holdout_off' failed (exitcode=1)
Anyone have a clue what this could be?
Just run the command which failed (in single quotes) directly from the test directory, and the reason would become obvious.
It is missing data file:
Reading datafile = test/train-sets/argmax_data
can't open: test/train-sets/argmax_data, error = No such file or directory
vw: std::exception
The issue was introduced in a recent check-in and should soon be fixed (hopefully).
Update (2014-05-31): fixed in the most recent commit.