A Distributed Front-end for GCC

format writes "distcc is a distributed front-end for GCC, meaning you can compile that big project across n number of machines and get it done almost n times as fast. The machines don't have to be identical or be running the exact same GCC version, but having the same OS is helpful." With the advent of faster hardware, I can't complain about kernel compile times anymore, but larger source trees could definitely benefit from this.

Comments

Not N

[Nashirak]

You can almost never achevie a speed up of N. You can acheive S(N) = T(1)/(T(1)*alpha+((1-alpha)*T(1))/N+T0) Where T(1) is the time it takes to run the task with 1 computer, alpha is the part of the task that cannot be parallelised (as in startup registers etc.) and T0 is the communications overhead of the task.

Just to clarify. :)

Re:hmmm

[stevey]

In that case you might like to look at ccache which is a compiler cache for a single machine.

It will cache the compiler options for each source file and the resultant object file generated. I use a lot when I'm building packages for software - which require multiple compilations. It works very nicely - I'd love to see how well it would integrate with distcc....

YES! N! Re:Not N

[angel'o'sphere]

You can almost never achevie a speed up of N. You can acheive S(N) = (1)/ (T(1)*alpha+((1-alpha)*T(1)) / N+T0) Where
T(1) is the time it takes to run the task with 1 computer, alpha is the part of the task that cannot be parallelised (as in startup registers etc.) and T0 is the communications overhead of the task.


This is the text book. Amdahls law, IIRC.

In reality, and also in most text books, there are exceptions where the solution scales with the number of processes.

And it should be easy enough to see: 5 machines compiling one source file each are 5 times as fast as one machine compiling 5 source files.

As long as you start gcc 5 times in a row you have
the same initialization overhead for EACH instance of gcc one after the other.

If you manage to start gcc with a couple of source files as argument to compile you save the laoding time of the binary at least. That would correspondend roughly to the alpha value.

Amdahls law is usefull for a single program/problem: try to paralelize gcc and you find the compiling source can't get speed up very much. So 5 processors running several threads of one gcc instance, those do not scale by 5.

However it says nothing about just solving the same problem multiple times in parallel.

Regards,
angel'o'sphere

Re:YES! N! Re:Not N

[joib]

That assumes you can divide the work equally. Consider that the number of source files probably aren't an integer*N, and that different source files take varying times to compile. Of course, as the number of source files approaches infinity, and if you have some load balancing scheme, this becomes a non-issue. Of course, in Real Life (TM) most projects don't have an infinite amount of source files.

Re:GCC version

[Anonymous Coward]

The binary incompatibility issue only exists for C++, but it is still very important. I took a brief look at the distcc manual, and it did mention (see this section) that you may want to use the same version of g++ on all machines if you are compiling C++. I would change "may" to "must"; you really don't want to take the risk of having incompatibility bugs.

Regardless of the language, if some of the machines are running a different OS, or have a different architecture, they will have to do cross-compilation and things will get more complicated.

Colin Howell

Re:Don't need the same version?

[Angry White Guy]

From the FAQ:

distcc doesn't care. However, in some circumstances, particularly for C++, gcc object files compiled with one version of gcc are not compatible with those compiled by another. This is true even if they are built on the same machine.
It is usually best to make sure that every compiler name maps to a reasonably similar version on every machine. You can either make sure that gcc is the same everywhere, or use a version-qualified compiler name, such as gcc-3.2 or gcc-3.2-x86-linux.

So in other words, keep them close, especially for gcc versions that break backwards capability.

Only true for C++

[FooBarWidget]

The C ABI between *all* GCC versions (and probably other compilers too) are compatible. You can compile libgnome using GCC 2.95.2 and Nautilus using GCC 3.2 and not have any problems at all.

Check out also ccache.samba.org

[GGarand]

From the ccache homepage, which is also a Samba hosted project :

ccache is a compiler cache.
It acts as a caching pre-processor to C/C++ compilers, using the -E compiler switch and a hash to detect when a compilation can be satisfied from cache.
This often results in a 5 to 10 times speedup in common compilations.

security?

[gooofy]

looks like this one is not necessarily a good idea to run on a university workstation cluster...

1.4 Security Considerations

distcc should only be used on networks where all machines and all users are trusted.

The distcc daemon, distccd, allows other machines on the network to run arbitrary commands on the volunteer machine. Anyone that can make a connection to the volunteer machine can run essentially any command as the user running distccd.

distcc is suitable for use on a small to medium network of friendly developers. It's certainly not suitable for use on a machine connected to the Internet or a large (e.g. university campus) network without firewalling in place.

inetd or tcpwrappers can be used to impose access control rules, but this should be done with an eye to the possibility of address spoofing.

In summary, the security level is similar to that of old-style network protocols like X11-over-TCP, NFS or RSH.

Not a new idea, but a noble one anyway

[GeckoFood]

Once upon a time, Symantec had a C++ compiler, and with version 7.5 (1996), the build process could be spread all over a network. This did speed up compilation times as machines that were running the build service that were more or less idle would be sent files to compile, passing back the objects and binaries as oppropriate.

Oh, by the way, that compiler is now called Digital Mars C++.

That said, all the machines on the network had to be running Windows (and at that time, I think only Windows 95 or NT were the only choices available for that compiler). Further, all had to have the same version of the compiler.

For those of us that are running Linux boxes on a primarily Windows network, this system, whether GCC or something else, would be rather hard to implement without a cross-compiler. Additionally, even if all were Linux workstations (or BSD, or Solaris, etc etc etc) wouldn't binary compatibility be driven by not just the version of the compiler but the target OS as well?

It's a noble undertaking. I hope that the developers are putting thought into all the little things like this that will make it tough to pull off.

Re:So, is it better? - Quick answer from the site.

[panoplos]

From the Group Compiler [sic] (gecc) site:

gecc is a proof of concept. It is heavily inspired by ccache and distcc. You could chain these tools to achieve the same goals gecc tries to reach. Both tools are much more mature and work in production environments. gecc just started with a little different concept. gecc has a central component (distcc has not).

My idea is that gecc could better handle a varying set of compile nodes: if you have some machines that only from time to time could help in distributed compiling than this is nice.

With a central component it might be easier to monitor the compilation and distribute the compile jobs.

Right now gecc is only useful if you read the source.

Emphasis is mine.

I guess it all depends on whether or not you want to work with production quality code or not.

Re:No, NOT N

[angel'o'sphere]

Let's say it takes 50 msec to initialize gcc and 500 msec to compile the average source file. Then it takes 5.05 sec to compile ten files with one copy of gcc


Your calculation is wrong:

I explicitly said: you start gcc N times for N files.

So a call like gcc: 1.c 2.c 3.c ..... 10.c is not allowed.

Because that call falls under amdahls law(in so far as a common initialization time is needed which is divided amoung the ten compile tasks).

However 10 calls:
gcc 1.c
gcc 2.c
gcc 3.c ...
gcc 10.c

Those ten calls scale with 10! running those ten calls one after the other on 1 machine takes exactly ten times the time then running one of them each on its own machine.

I repeat: Amadahls law is about parallelizing one algorithm. It is not about starting the same algorithm on different problem sets (differnt c files) in parallel.

Where as the first one does not scale infinite and not scale with N, the second one does(of course with some limitations in RL, e.g. if all compilers use the same file server via NFS).

The interesting difference is this: under Amdahls law you have a maximum processors up to which the solution scales. Adding more processors does not make the problem solving faster. Very often it makes the problem solving slower indeed because of communication overhead. OTOH, by just duplicating the hardware and distributing the problem "identicaly" and not "divided and parallelized" you indeed get nearly infinite scale ups. You scale up to the point where the distributing and the gathering gets to expensive. (Distributing C sources from a CVS repository to compile farm machines and gathering the *.o files or better *.so during linking back)

angel'o'sphere