What strategies have you used to improve build times on large projects?

Question

I once worked on a C++ project that took about an hour and a half for a full rebuild. Small edit, build, test cycles took about 5 to 10 minutes. It was an unproductive nightmare.

What is the worst build times you ever had to handle?

What strategies have you used to improve build times on large projects?

Update:

How much do you think the language used is to blame for the problem? I think C++ is prone to massive dependencies on large projects, which often means even simple changes to the source code can result in a massive rebuild. Which language do you think copes with large project dependency issues best?

Answer 1

1. Forward declaration
2. pimpl idiom
3. Precompiled headers
4. Parallel compilation (e.g. MPCL add-in for Visual Studio).
5. Distributed compilation (e.g. Incredibuild for Visual Studio).
6. Incremental build
7. Split build in several "projects" so not compile all the code if not needed.

[Later Edit] 8. Buy faster machines.

Answer 2

My strategy is pretty simple - I don't do large projects. The whole thrust of modern computing is away from the giant and monolithic and towards the small and componentised. So when I work on projects, I break things up into libraries and other components that can be built and tested independantly, and which have minimal dependancies on each other. A "full build" in this kind of environment never actually takes place, so there is no problem.

Answer 3

1. Fiddle with the compiler optimisation flags,
2. use option -j4 for gmake for parallel compilation (multicore or single core)
3. if you are using clearmake , use winking
4. we can take out the debug flags..in extreme cases.
5. Use some powerful servers.

Answer 4

Powerful compilation machines and parallel compilers. We also make sure the full build is needed as little as possible. We don't alter the code to make it compile faster.

Efficiency and correctness is more important than compilation speed.

Answer 5

In Visual Studio, you can set number of project to compile at a time. Its default value is 2, increasing that would reduce some time.

This will help if you don't want to mess with the code.

Answer 6

This is the list of things we did for a development under Linux :

• As Warrior noted, use parallel builds (make -jN)
• We use distributed builds (currently icecream which is very easy to setup), with this we can have tens or processors at a given time. This also has the advantage of giving the builds to the most powerful and less loaded machines.
• We use ccache so that when you do a make clean, you don't have to really recompile your sources that didn't change, it's copied from a cache.
• Note also that debug builds are usually faster to compile since the compiler doesn't have to make optimisations.

Answer 7

1. Multi core compilation. Very fast with 8 cores compiling on the I7.
2. Incremental linking
3. External constants
4. Removed inline methods on C++ classes.

The last two gave us a reduced linking time from around 12 minutes to 1-2 minutes. Note that this is only needed if things have a huge visibility, i.e. seen "everywhere" and if there are many different constants and classes.

Cheers

Answer 8

We tried creating proxy classes once.

These are really a simplified version of a class that only includes the public interface, reducing the number of internal dependencies that need to be exposed in the header file. However, they came with a heavy price of spreading each class over several files that all needed to be updated when changes to the class interface were made.

Answer 9

One trick that sometimes helps is to include everything into one .cpp file. Since includes are processed once per file, this can save you a lot of time. (The downside to this is that it makes it impossible for the compiler to parallelize compilation)

You should be able to specify that multiple .cpp files should be compiled in parallel (-j with make on linux, /MP on MSVC - MSVC also has an option to compile multiple projects in parallel. These are separate options, and there's no reason why you shouldn't use both)

In the same vein, distributed builds (Incredibuild, for example), may help take the load off a single system.

SSD disks are supposed to be a big win, although I haven't tested this myself (but a C++ build touches a huge number of files, which can quickly become a bottleneck).

Precompiled headers can help too, when used with care. (They can also hurt you, if they have to be recompiled too often).

And finally, trying to minimize dependencies in the code itself is important. Use the pImpl idiom, use forward declarations, keep the code as modular as possible. In some cases, use of templates may help you decouple classes and minimize dependencies. (In other cases, templates can slow down compilation significantly, of course)

But yes, you're right, this is very much a language thing. I don't know of another language which suffers from the problem to this extent. Most languages have a module system that allows them to eliminate header files, which area huge factor. C has header files, but is such a simple language that compile times are still manageable. C++ gets the worst of both worlds. A big complex language, and a terrible primitive build mechanism that requires a huge amount of code to be parsed again and again.

Answer 10

Unity Builds

Incredibuild

Pointer to implementation

forward declarations

compiling "finished" sections of the proejct into dll's

Answer 11

IncrediBuild

Answer 12

In general large C++ projects that I've worked on that had slow build times were pretty messy, with lots of interdependencies scattered through the code (the same include files used in most cpps, fat interfaces instead of slim ones). In those cases, the slow build time was just a symptom of the larger problem, and a minor symptom at that. Refactoring to make clearer interfaces and break code out into libraries improved the architecture, as well as the build time. When you make a library, it forces you to think about what is an interface and what isn't, which will actually (in my experience) end up improving the code base. If there's no technical reason to have to divide the code, some programmers through the course of maintenance will just throw anything into any header file.

Answer 13

The best suggestion is to build makefiles that actually understand dependencies and do not automatically rebuild the world for a small change. But, if a full rebuild takes 90 minutes, and a small rebuild takes 5-10 minutes, odds are good that your build system already does that.

Can the build be done in parallel? Either with multiple cores, or with multiple servers?

Checkin pre-compiled bits for pieces that really are static and do not need to be rebuilt every time. 3rd party tools/libraries that are used, but not altered are a good candidate for this treatment.

Limit the build to a single 'stream' if applicable. The 'full product' might include things like a debug version, or both 32 and 64 bit versions, or may include help files or man pages that are derived/built every time. Removing components that are not necessary for development can dramatically reduce the build time.

Does the build also package the product? Is that really required for development and testing? Does the build incorporate some basic sanity tests that can be skipped?

Finally, you can re-factor the code base to be more modular and to have fewer dependencies. Large Scale C++ Software Design is an excellent reference for learning to decouple large software products into something that is easier to maintain and faster to build.

EDIT: Building on a local filesystem as opposed to a NFS mounted filesystem can also dramatically speed up build times.

Answer 14

ccache & distcc (for C/C++ projects) -

ccache caches compiled output, using the pre-processed file as the 'key' for finding the output. This is great because pre-processing is pretty quick, and quite often changes that force recompile don't actually change the source for many files. Also, it really speeds up a full re-compile. Also nice is the instance where you can have a shared cache among team members. This means that only the first guy to grab the latest code actually compiles anything.

distcc does distributed compilation across a network of machines. This is only good if you HAVE a network of machines to use for compilation. It goes well with ccache, and only moves the pre-processed source around, so the only thing you have to worry about on the compiler engine systems is that they have the right compiler (no need for headers or your entire source tree to be visible).

Answer 15

This book Large-Scale C++ Software Design has very good advice I've used in past projects.

Answer 16

Full build is about 2 hours. I try to avoid making modification to the base classes and since my work is mainly on the implementation of these base classes I only need to build small components (couple of minutes).

Answer 17

Cătălin Pitiș covered a lot of good things. Other ones we do:

• Have a tool that generates reduced Visual Studio .sln files for people working in a specific sub-area of a very large overall project
• Cache DLLs and pdbs from when they are built on CI for distribution on developer machines
• For CI, make sure that the link machine in particular has lots of memory and high-end drives
• Store some expensive-to-regenerate files in source control, even though they could be created as part of the build
• Replace Visual Studio's checking of what needs to be relinked by our own script tailored to our circumstances

Answer 18

It's a pet peeve of mine, so even though you already accepted an excellent answer, I'll chime in:

In C++, it's less the language as such, but the language-mandated build model that was great back in the seventies, and the header-heavy libraries.

The only thing that is wrong about Cătălin Pitiș' reply: "buy faster machines" should go first. It is the easyest way with the least impact.

My worst was about 80 minutes on an aging build machine running VC6 on W2K Professional. The same project (with tons of new code) now takes under 6 minutes on a machine with 4 hyperthreaded cores, 8G RAM Win 7 x64 and decent disks. (A similar machine, about 10..20% less processor power, with 4G RAM and Vista x86 takes twice as long)

Strangely, incremental builds are most of the time slower than full rebuuilds now.

Answer 19

Create some unit test projects to test individual libraries, so that if you need to edit low level classes that would cause a huge rebuild, you can use TDD to know your new code works before you rebuild the entire app. The John Lakos book as mentioned by Themis has some very practical advice for restructuring your libraries to make this possible.

Answer 20

1. Minimize your public API
2. Minimize inline functions in your API. (Unfortunately this also increases linker requirements).
3. Maximize forward declarations.
4. Reduce coupling between code. For instance pass in two integers to a function, for coordinates, instead of your custom Point class that has it's own header file.
5. Use Incredibuild. But it has some issues sometimes.
6. Do NOT put code that get exported from two different modules in the SAME header file.
7. Use the PImple idiom. Mentioned before, but bears repeating.
8. Use Pre-compiled headers.
9. Avoid C++/CLI (i.e. managed c++). Linker times are impacted too.
10. Avoid using a global header file that includes 'everything else' in your API.
11. Don't put a dependency on a lib file if your code doesn't really need it.
12. Know the difference between including files with quotes and angle brackets.