> GNU make has no built-in capability to use multiple machines:
How are the chances to integrate additional job submission systems?
> conceptually it may be a straightforward extension but the effort needed
> to communicate between multiple systems over a network, send and receive
> results reli
> We ran into similar things in Linux due to NFS, autofs, and NFS via
> apparmor not scaling well when 100 compilers are trying to search for
> header files through a long number of sourcedirs.
I suppose this can be mitigated by using #include "path/to/file.h" in
source, for paths relative to a sm
> Luckily, if you are building C or C++ code someone has already done all
> the necessary work for you. I recommend you investigate the distcc
> package: https://code.google.com/p/distcc/
Likewise the icecream project's icecc:
https://en.opensuse.org/Icecream
https://github.com/icecc/icecream
I'
Last time I looked at distcc, it still ran the c++ preprocessor on the main
machine (to eliminate the risk of different machines having different
configurations), and then sent the preprocessed files to the various machines
at its disposal. This, in my experience, still does a huge portion of t
Without wanting to turn this into a commercial/advert you might want to
consider trying the Electric Cloud Huddle beta since it works with multiple
machines in a convenient way and deals with the problems of getting correct
parallel builds. It is also free for now at least.
Sorry for that :)
On 29
On Wed, 2015-04-29 at 13:50 -0600, Ryan P. Steele wrote:
> The multithreaded version of make (-j#) is wonderful, and we have made
> great use of it. Because we're dealing with some very large code,
> however, it would be great to be able to parallelize compilation over
> multiple machines. I ca
Hi, folks -
I encountered a situation that I can't seem to resolve through the
"make" documentation...
The multithreaded version of make (-j#) is wonderful, and we have made
great use of it. Because we're dealing with some very large code,
however, it would be great to be able to paralleliz
