I manage a very large project using CMake that I have done significant
restructuring to lower the CMake configure times. I will say the one thing
that surprised me the most is that for one piece of it where we have repeated
work done say “for each folder in this subdir build 11 executables with a ton
of code generation.” If I structure the build as such:
One top level CMakeLists.txt and one single line CMakeLists.txt in each subdir
containing do_work(${SUBDIR}):
foreach( SUBDIR ${LIST_OF_SUBDIRS} )
add_subdirectory(${SUBDIR})
endforeach()
Versus:
One top level CMakeLists.txt:
foreach( SUBDIR ${LIST_OF_SUBDIRS} )
do_work(${SUBDIR})
endforeach()
In short, the decision to do all the work in the same CMakeLists.txt file or do
I enter and leave a CMakeLists.txt for each directory causes a dramatic
performance and memory difference.
The add_subdirectory method saves many Gigs of RAM and reduces our configure
time from 30 minutes to 5 minutes. Please note I am writing this from memory
so my numbers may be a bit off but scale is accurate.
I don’t know if this is applicable to your case but it was the biggest saving
in my project and took a long time to figure out.
-Kris
From: CMake [mailto:[email protected]] On Behalf Of Isaiah Norton
Sent: Friday, May 04, 2018 7:51 PM
To: Patrick E Gartung <[email protected]>
Cc: [email protected]
Subject: Re: [CMake] Memory usage and configuration time for large project
As one ballpark datapoint: a "superbuild" of 3D Slicer
(slicer.org<http://slicer.org>) has a similar object and library count:
macbook-pro:s5nj inorton$ find ./ -name *.o | wc -l
14127
macbook-pro:s5nj inorton$ find ./ -name *.dylib -or -name *.so | wc -l
2158
Based on a few quick tests, the aggregate cmake time is probably about 6-8
minutes for the ninja generator, over the multi-hour build (each dependency is
configured and built as a separate sub-project via CMake's ExternalProject
mechanism) -- with the caveat that each of those cmake runs is doing lengthy
checks that should only be done once if your project strictly uses
`add_subdirectory`.
As a more concrete point of comparison, building VTK generates 5747 object
files, and a clean configure on my 2-core macbook takes about 90s.
Isaiah
On Fri, May 4, 2018 at 2:16 PM, Patrick E Gartung
<[email protected]<mailto:[email protected]>> wrote:
Just to be clear, the memory and time used are just to configure and generate
the makefiles or Ninja file. The build itself can take several hours.
On 4/30/18, 4:55 PM, "R0b0t1" <[email protected]<mailto:[email protected]>>
wrote:
On Mon, Apr 30, 2018 at 4:44 PM, Patrick E Gartung
<[email protected]<mailto:[email protected]>> wrote:
> Hi,
>
> We have a large c/c++/fortran project, CMSSW, that is built with a custom
tool, scram.
>
> https://github.com/cms-sw/cmssw
>
> The project might move to a cmake based build in the future. The scripts
to convert to CmakeLists.tx has been written
>
> https://github.com/cms-sw/cmssw2cmake
>
> Tests show that with the cmake files generated with this script,
configuring the project uses up to 1.5GB of ram and takes 11 minutes when using
-GMakefiles. Using -GNinja and using the latest cmake, this time can be reduced
to 8 minutes.
>
> The project builds 14k object files, 2.2k libraries, ~600 binaries, 500
generated source files with links to ~100 external libraries.
>
> Is this amount of memory usage and time typical for a project of this
size?
>
I'm inclined to say "yes" as many builds such as Firefox, its
supporting libraries, and Chrome all take lots of time and memory.
Chrome uses Ninja, I might add. But the issue is not CMake itself.
CMake tends to produce better builds.
As I am not intimately familiar with your project, I can't make good
concrete suggestions. You may enjoy reading
https://news.ycombinator.com/item?id=14733829 and searching for build
optimization strategies.
Keep in mind a lot of the blame falls on C++ and Windows, should you
be using Windows. If you aren't using Windows, then the advice in the
comments above should still be relevant, and give you something to go
on.
Cheers,
R0b0t1
> Patrick Gartung
> Fermilab
>
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