Compiling with g++ using multiple cores

Question

Quick question: what is the compiler flag to allow g++ to spawn multiple instances of itself in order to compile large projects quicker (for example 4 source files at a time for a multi-core CPU)?

Antifouling

Will it really help? All my compile jobs are I/O bound rather than CPU bound. – Sabellian

Even if they are I/O bound you can probably keep the I/O load higher when the CPU heavy bits are happening (with just one g++ instance there will be lulls) and possibly gain I/O efficiencies if the scheduler has more choice about what to read from disk next. My experience has been that judicious use of make -j almost always results in some improvement. – Bradway

@BrianKnoblauch But on my machine(real one or in VirtualBox), it's CPU bound, I found that the CPU is busy through 'top' command when compiling. – Giro

Even if they are I/O bound, we can use gcc's flag '-pipe' to reduce pain. – Giro

just saw this in google: gcc.gnu.org/onlinedocs/libstdc++/manual/… – Theme

@JimMichaels That's completely unrelated: it's about parallel processing as part of the program at runtime, i.e. after compilation. The question is about compiling in parallel using multiple jobs. – Rositaroskes

david-smith.org/blog/2011/07/27/is-compilation-cpu-bound this fellow thinks cpu bound – Footle

Answer 1

You can do this with make - with gnu make it is the -j flag (this will also help on a uniprocessor machine).

For example if you want 4 parallel jobs from make:

make -j 4

You can also run gcc in a pipe with

gcc -pipe

This will pipeline the compile stages, which will also help keep the cores busy.

If you have additional machines available too, you might check out distcc, which will farm compiles out to those as well.

Smaragdine

You're -j number should be 1.5x the number of cores you have. – Augustin

yes, something like that makes sense given there is I/O as well - although may need some tuning if using -pipe as well – Smaragdine

Thanks. I kept trying to pass "-j#" to gcc via CFLAGS/CPPFLAGS/CXXFLAGS. I had completely forgotten that "-j#" was a parameter for GNU make (and not for GCC). – Pounce

Why does the -j option for GNU Make needs to be 1.5 x the number of CPU cores? – Aurochs

The 1.5 number is because of the noted I/O bound problem. It is a rule of thumb. About 1/3 of the jobs will be waiting for I/O, so the remaining jobs will be using the available cores. A number greater than the cores is better and you could even go as high as 2x. See also: Gnu make -j arguments – Vampire

make -j is broken, with mingw-w64 it will cause a long list of compilation errors whereas without project will compile fine. don't recommend it. I recommend submitting a bug report to the gnu make folk. – Theme

Will the Raspberry Pi 2 benefit from this flag? Will it be able to compile faster thanks to the new 4 core processor? – Ciceronian

@JimMichaels It could be because dependencies are badly set within your project, (a target starts building even if its dependencies are not ready yet) so that only a sequential build ends up being successful. – Numeration

-pipe is not pipeline, its to use pipes instead of temporary files. Uses more memory, but in some cases is faster. If your project is large, it might be worth trying. – Bower

Ok so this is quite a while after the original discussion, BUT: compiling Emacs git master on an AMD Threadripper 1950x with 16 cores using Fedora 27 completely breaks this 1.5x rule of thumb. There are 32 threads available, and 16 physical cores, yet make -j 12 is roughly fastest with approximately 1m15 to 1m20 user time. Increasing the arg to -j only increases build times. So in effect it's more like 3/4 x or 3/8 x depending on whether you want to count SMT "cores" or not. Of course it's entirely possible here that TR just rips through the parallellizable parts quickly... – Lith

How about make test? – Hymnody

Answer 2

There is no such flag, and having one runs against the Unix philosophy of having each tool perform just one function and perform it well. Spawning compiler processes is conceptually the job of the build system. What you are probably looking for is the -j (jobs) flag to GNU make, a la

make -j4

Or you can use pmake or similar parallel make systems.

Clubby

gnu.org/software/make/manual/html_node/Parallel.html also gnu.org/software/make/manual/html_node/… – Theme

"Unix pedantry is not helpful" Good thing it wasn't pedantry then, anonymous editor. Rolled back. Reviewers please pay more attention to what you're doing. – Meantime

despite the claim of non-pedantry, gcc is getting a flag -fparallel-jobs=N Better tell the GCC devs they're doing it wrong. – Macpherson

Answer 3

If using make, issue with -j. From man make:

  -j [jobs], --jobs[=jobs]
       Specifies the number of jobs (commands) to run simultaneously.  
       If there is more than one -j option, the last one is effective.
       If the -j option is given without an argument, make will not limit the
       number of jobs that can run simultaneously.

And most notably, if you want to script or identify the number of cores you have available (depending on your environment, and if you run in many environments, this can change a lot) you may use ubiquitous Python function cpu_count():

https://docs.python.org/3/library/multiprocessing.html#multiprocessing.cpu_count

Like this:

make -j $(python3 -c 'import multiprocessing as mp; print(int(mp.cpu_count() * 1.5))')

If you're asking why 1.5 I'll quote user artless-noise in a comment above:

The 1.5 number is because of the noted I/O bound problem. It is a rule of thumb. About 1/3 of the jobs will be waiting for I/O, so the remaining jobs will be using the available cores. A number greater than the cores is better and you could even go as high as 2x.

Cella

Most Linux users will likely prefer the shorter: make -j`nproc` with nproc in GNU Coreutils. – Tartuffe

If you're using an SSD, I/O isn't going to be as much of an issue. Just to build on Ciro's comment above, you can do this: make -j $(( $(nproc) + 1 )) (make sure you put spaces where I have them). – Gait

Nice suggestion using python, on systems where nproc isn't available, e.g. in manylinux1 containers, it saves additional time by avoiding running yum update/yum install. – Mcgruder

Answer 4

make will do this for you. Investigate the -j and -l switches in the man page. I don't think g++ is parallelizable.

Misgive

+1 for mentioning -l option ( does not start a new job unless all previous jobs did terminate ). Otherwise it seems that the linker job begins with not all object files built (as some compilations are still ongoing), so that the linker job fails. – Irrupt

Answer 5

People have mentioned make but bjam also supports a similar concept. Using bjam -jx instructs bjam to build up to x concurrent commands.

We use the same build scripts on Windows and Linux and using this option halves our build times on both platforms. Nice.

Confront

Answer 6

distcc can also be used to distribute compiles not only on the current machine, but also on other machines in a farm that have distcc installed.

Liege

+1, distcc is a useful tool to have in one's arsenal for large builds. – Bradway

Looks like there are a few that work "like" distcc as well: https://mcmap.net/q/129443/-distributed-make/… – Coplin

Answer 7

You can use make -j$(nproc) . This command is used to build a project using the make build system with multiple jobs running in parallel.

For example, if your system has 4 CPU cores, running make -j$(nproc) would instruct make to run 4 jobs concurrently, one on each CPU core, speeding up the build process.

You can also see how many cores you have with run this command; echo $(nproc)

Tele

Note that nproc doesn't always yield optimal performance. My machine has four cores but compilation runs faster with -j2. – Stableboy

Answer 8

I'm not sure about g++, but if you're using GNU Make then "make -j N" (where N is the number of threads make can create) will allow make to run multple g++ jobs at the same time (so long as the files do not depend on each other).

Fatality

no N ist not the number of threads! Many people misunderstand that, but -j N tells make how many processes at once should be spawned, not threads. That's the reason why it is not as performant as MS cl -MT(really multithreaded). – Thankless

what happens if N is too large? E.g. can -j 100 break the system or is N merely an upper bound that is not required to achieve? – Carven

Answer 9

GNU parallel

I was making a synthetic compilation benchmark and couldn't be bothered to write a Makefile, so I used:

sudo apt-get install parallel
ls | grep -E '\.c$' | parallel -t --will-cite "gcc -c -o '{.}.o' '{}'"

Explanation:

• {.} takes the input argument and removes its extension
• -t prints out the commands being run to give us an idea of progress
• --will-cite removes the request to cite the software if you publish results using it...

parallel is so convenient that I could even do a timestamp check myself:

ls | grep -E '\.c$' | parallel -t --will-cite "\
  if ! [ -f '{.}.o' ] || [ '{}' -nt '{.}.o' ]; then
    gcc -c -o '{.}.o' '{}'
  fi
"

xargs -P can also run jobs in parallel, but it is a bit less convenient to do the extension manipulation or run multiple commands with it: Calling multiple commands through xargs

Parallel linking was asked at: Can gcc use multiple cores when linking?

TODO: I think I read somewhere that compilation can be reduced to matrix multiplication, so maybe it is also possible to speed up single file compilation for large files. But I can't find a reference now.

Tested in Ubuntu 18.10.

Tartuffe