The question is inspired by OpenMP with BLAS
The motivation is, I want the Fortran source code to be flexible to the complier options related to serial/parallel BLAS. I may specify -mkl=parallel for mkl or USE_OPENMP=1 for lopenblas in the Makefile.
I may do make ifort or make gfortran or make blah blah to switch the libaries in the Makefile.
But,
a) If I use -mkl=parallel in the Makefile, I need to set call mkl_set_num_threads(numthreads) in the source code,
b) If I use OpenBLAS with USE_OPENMP=1, I may need openblas_set_num_threads(num_threads) in the source code
https://rdrr.io/github/wrathematics/openblasctl/man/openblas_set_num_threads.html#:~:text=threads%20to%20use.-,Details,t%20simply%20call%20R%27s%20Sys.
c) for the time being if there is only lblas and/or with -mkl=sequential, I have to manually configurate dgemm threads (as kind of block decomposition), regardless OMP_NUM_THREADS. That's ok, but I need to use if to control the source code goes in that way, if the source code has lines for a) and b)
The manually programming dgemm threads in c) is somehow universal. When I would like to exploit parallel blas from libraries, things can be complicated it seems such that I don't know how to switch in source code regarding the compiler options.
Addition, OMP_NUM_THREADS from enviroment file, .bashrc, is not preferable. (Sorry I should have mentioned this point earlier) The source code read an input file which specify the number of cores being used, and use omp_set_num_thread to set the targeted number of cores, than from the enviroment file.
Addition2, from my test on MKL, OMP_NUM_THREADS cannot surpress call mkl_set_num_threads. Namely, I have to specify call mkl_set_num_threads to work with -mkl=parallel flag.
There are at least two approaches to this.
Preprocessor variables
As explained in e.g. this question and this question, among others, you can pass variables from a Makefile directly to an appropriate preprocessor.
For example, in the branches of the Makefile where you set -mkl=parallel you could also set -DMKL_PARALLEL. Then, in your source code you could have a block which looks something like
#ifdef MKL_PARALLEL
call mkl_set_num_threads(numthreads)
#endif
Provided you compile your code with an appropriate preprocessor, this allows you to pass arbitrary information from your Makefile to your source code.
Separate files
Instead of using a preprocessor, you can have multiple copies of the same file, each with a different set of options, and only compile the correct file for the project.
A slightly nicer way of doing this is to have one module file, which is always the same regardless of options, and multiple submodules, each of which contains one set of options. This reduces the room for error arising from multiple files, and reduces compilation time if you need to change the options.
Most build systems, like autoconf/automake, allow the user to specify a target directory to install the various files needed to run a program. Usually this includes binaries, configuration files, auxilliary scripts, etc.
At the same time, many executables often need to read from a configuration file in order to allow a user to modify runtime settings.
Ultimately, a program (let's say, a compiled C or C++ program) needs to know where to look to read in a configuration file. A lot of times I will just hardcode the path as something like /etc/MYPROGAM/myprog.conf, which of course is not a great idea.
But in the autoconf world, the user might specify an install prefix, meaning that the C/C++ code needs to somehow be aware of this.
One solution would be to specify a C header file with a .in prefix, which simply is used to define the location of the config file, like:
const char* config_file_path = "#CONFIG_FILE_PATH#"; // `CONFIG_FILE_PATH` is defined in `configure.ac`.
This file would be named something like constants.h.in and it would have to be process by the configure.ac file to output an actual header file, which could then be included by whatever .c or .cpp files need it.
Is that the usual way this sort of thing is handled? It seems a bit cumbersome, so I wonder if there is a better solution.
There are basically two choices for how to handle this.
One choice is to do what you've mentioned -- compile the relevant paths into the resulting executable or library. Here it's worth noting that if files are installed in different sub-parts of the prefix, then each such thing needs its own compile-time path. That's because the user might specify --prefix separately from --bindir, separately from --libexecdir, etc. Another wrinkle here is that if there are multiple installed programs that refer to each other, then this process probably should take into account the program name transform (see docs on --program-transform-name and friends).
That's all if you want full generality of course.
The other approach is to have the program be relocatable at runtime. Many GNU projects (at least gdb and gcc) take this approach. The idea here is for the program to attempt to locate its data in the filesystem at runtime. In the projects I'm most familiar with, this is done with the libiberty function make_relative_prefix; but I'm sure there are other ways.
This approach is often touted as being nicer because it allows the program's install tree to be tared up and delivered to users; but in the days of distros it seems to me that it isn't as useful as it once was. I think the primary drawback of this approach is that it makes it very hard, if not impossible, to support both relocation and the full suite of configure install-time options.
Which one you pick depends, I think, on what your users want.
Also, to answer the above comment: I think changing the prefix between configure- and build time is not really supported, though it may work with some packages. Instead the usual way to handle this is either to require the choice at configure time, or to supported the somewhat more limited DESTDIR feature.
What techniques can be used to speed up C++ compilation times?
This question came up in some comments to Stack Overflow question C++ programming style, and I'm interested to hear what ideas there are.
I've seen a related question, Why does C++ compilation take so long?, but that doesn't provide many solutions.
Language techniques
Pimpl Idiom
Take a look at the Pimpl idiom here, and here, also known as an opaque pointer or handle classes. Not only does it speed up compilation, it also increases exception safety when combined with a non-throwing swap function. The Pimpl idiom lets you reduce the dependencies between headers and reduces the amount of recompilation that needs to be done.
Forward Declarations
Wherever possible, use forward declarations. If the compiler only needs to know that SomeIdentifier is a struct or a pointer or whatever, don't include the entire definition, forcing the compiler to do more work than it needs to. This can have a cascading effect, making this way slower than they need to be.
The I/O streams are particularly known for slowing down builds. If you need them in a header file, try #including <iosfwd> instead of <iostream> and #include the <iostream> header in the implementation file only. The <iosfwd> header holds forward declarations only. Unfortunately the other standard headers don't have a respective declarations header.
Prefer pass-by-reference to pass-by-value in function signatures. This will eliminate the need to #include the respective type definitions in the header file and you will only need to forward-declare the type. Of course, prefer const references to non-const references to avoid obscure bugs, but this is an issue for another question.
Guard Conditions
Use guard conditions to keep header files from being included more than once in a single translation unit.
#pragma once
#ifndef filename_h
#define filename_h
// Header declarations / definitions
#endif
By using both the pragma and the ifndef, you get the portability of the plain macro solution, as well as the compilation speed optimization that some compilers can do in the presence of the pragma once directive.
Reduce interdependency
The more modular and less interdependent your code design is in general, the less often you will have to recompile everything. You can also end up reducing the amount of work the compiler has to do on any individual block at the same time, by virtue of the fact that it has less to keep track of.
Compiler options
Precompiled Headers
These are used to compile a common section of included headers once for many translation units. The compiler compiles it once, and saves its internal state. That state can then be loaded quickly to get a head start in compiling another file with that same set of headers.
Be careful that you only include rarely changed stuff in the precompiled headers, or you could end up doing full rebuilds more often than necessary. This is a good place for STL headers and other library include files.
ccache is another utility that takes advantage of caching techniques to speed things up.
Use Parallelism
Many compilers / IDEs support using multiple cores/CPUs to do compilation simultaneously. In GNU Make (usually used with GCC), use the -j [N] option. In Visual Studio, there's an option under preferences to allow it to build multiple projects in parallel. You can also use the /MP option for file-level paralellism, instead of just project-level paralellism.
Other parallel utilities:
Incredibuild
Unity Build
distcc
Use a Lower Optimization Level
The more the compiler tries to optimize, the harder it has to work.
Shared Libraries
Moving your less frequently modified code into libraries can reduce compile time. By using shared libraries (.so or .dll), you can reduce linking time as well.
Get a Faster Computer
More RAM, faster hard drives (including SSDs), and more CPUs/cores will all make a difference in compilation speed.
I work on the STAPL project which is a heavily-templated C++ library. Once in a while, we have to revisit all the techniques to reduce compilation time. In here, I have summarized the techniques we use. Some of these techniques are already listed above:
Finding the most time-consuming sections
Although there is no proven correlation between the symbol lengths and compilation time, we have observed that smaller average symbol sizes can improve compilation time on all compilers. So your first goals it to find the largest symbols in your code.
Method 1 - Sort symbols based on size
You can use the nm command to list the symbols based on their sizes:
nm --print-size --size-sort --radix=d YOUR_BINARY
In this command the --radix=d lets you see the sizes in decimal numbers (default is hex). Now by looking at the largest symbol, identify if you can break the corresponding class and try to redesign it by factoring the non-templated parts in a base class, or by splitting the class into multiple classes.
Method 2 - Sort symbols based on length
You can run the regular nm command and pipe it to your favorite script (AWK, Python, etc.) to sort the symbols based on their length. Based on our experience, this method identifies the largest trouble making candidates better than method 1.
Method 3 - Use Templight
"Templight is a Clang-based tool to profile the time and memory consumption of template instantiations and to perform interactive debugging sessions to gain introspection into the template instantiation process".
You can install Templight by checking out LLVM and Clang (instructions) and applying the Templight patch on it. The default setting for LLVM and Clang is on debug and assertions, and these can impact your compilation time significantly. It does seem like Templight needs both, so you have to use the default settings. The process of installing LLVM and Clang should take about an hour or so.
After applying the patch you can use templight++ located in the build folder you specified upon installation to compile your code.
Make sure that templight++ is in your PATH. Now to compile add the following switches to your CXXFLAGS in your Makefile or to your command line options:
CXXFLAGS+=-Xtemplight -profiler -Xtemplight -memory -Xtemplight -ignore-system
Or
templight++ -Xtemplight -profiler -Xtemplight -memory -Xtemplight -ignore-system
After compilation is done, you will have a .trace.memory.pbf and .trace.pbf generated in the same folder. To visualize these traces, you can use the Templight Tools that can convert these to other formats. Follow these instructions to install templight-convert. We usually use the callgrind output. You can also use the GraphViz output if your project is small:
$ templight-convert --format callgrind YOUR_BINARY --output YOUR_BINARY.trace
$ templight-convert --format graphviz YOUR_BINARY --output YOUR_BINARY.dot
The callgrind file generated can be opened using kcachegrind in which you can trace the most time/memory consuming instantiation.
Reducing the number of template instantiations
Although there are no exact solution for reducing the number of template instantiations, there are a few guidelines that can help:
Refactor classes with more than one template arguments
For example, if you have a class,
template <typename T, typename U>
struct foo { };
and both of T and U can have 10 different options, you have increased the possible template instantiations of this class to 100. One way to resolve this is to abstract the common part of the code to a different class. The other method is to use inheritance inversion (reversing the class hierarchy), but make sure that your design goals are not compromised before using this technique.
Refactor non-templated code to individual translation units
Using this technique, you can compile the common section once and link it with your other TUs (translation units) later on.
Use extern template instantiations (since C++11)
If you know all the possible instantiations of a class you can use this technique to compile all cases in a different translation unit.
For example, in:
enum class PossibleChoices = {Option1, Option2, Option3}
template <PossibleChoices pc>
struct foo { };
We know that this class can have three possible instantiations:
template class foo<PossibleChoices::Option1>;
template class foo<PossibleChoices::Option2>;
template class foo<PossibleChoices::Option3>;
Put the above in a translation unit and use the extern keyword in your header file, below the class definition:
extern template class foo<PossibleChoices::Option1>;
extern template class foo<PossibleChoices::Option2>;
extern template class foo<PossibleChoices::Option3>;
This technique can save you time if you are compiling different tests with a common set of instantiations.
NOTE : MPICH2 ignores the explicit instantiation at this point and always compiles the instantiated classes in all compilation units.
Use unity builds
The whole idea behind unity builds is to include all the .cc files that you use in one file and compile that file only once. Using this method, you can avoid reinstantiating common sections of different files and if your project includes a lot of common files, you probably would save on disk accesses as well.
As an example, let's assume you have three files foo1.cc, foo2.cc, foo3.cc and they all include tuple from STL. You can create a foo-all.cc that looks like:
#include "foo1.cc"
#include "foo2.cc"
#include "foo3.cc"
You compile this file only once and potentially reduce the common instantiations among the three files. It is hard to generally predict if the improvement can be significant or not. But one evident fact is that you would lose parallelism in your builds (you can no longer compile the three files at the same time).
Further, if any of these files happen to take a lot of memory, you might actually run out of memory before the compilation is over. On some compilers, such as GCC, this might ICE (Internal Compiler Error) your compiler for lack of memory. So don't use this technique unless you know all the pros and cons.
Precompiled headers
Precompiled headers (PCHs) can save you a lot of time in compilation by compiling your header files to an intermediate representation recognizable by a compiler. To generate precompiled header files, you only need to compile your header file with your regular compilation command. For example, on GCC:
$ g++ YOUR_HEADER.hpp
This will generate a YOUR_HEADER.hpp.gch file (.gch is the extension for PCH files in GCC) in the same folder. This means that if you include YOUR_HEADER.hpp in some other file, the compiler will use your YOUR_HEADER.hpp.gch instead of YOUR_HEADER.hpp in the same folder before.
There are two issues with this technique:
You have to make sure that the header files being precompiled is stable and is not going to change (you can always change your makefile)
You can only include one PCH per compilation unit (on most of compilers). This means that if you have more than one header file to be precompiled, you have to include them in one file (e.g., all-my-headers.hpp). But that means that you have to include the new file in all places. Fortunately, GCC has a solution for this problem. Use -include and give it the new header file. You can comma separate different files using this technique.
For example:
g++ foo.cc -include all-my-headers.hpp
Use unnamed or anonymous namespaces
Unnamed namespaces (a.k.a. anonymous namespaces) can reduce the generated binary sizes significantly. Unnamed namespaces use internal linkage, meaning that the symbols generated in those namespaces will not be visible to other TU (translation or compilation units). Compilers usually generate unique names for unnamed namespaces. This means that if you have a file foo.hpp:
namespace {
template <typename T>
struct foo { };
} // Anonymous namespace
using A = foo<int>;
And you happen to include this file in two TUs (two .cc files and compile them separately). The two foo template instances will not be the same. This violates the One Definition Rule (ODR). For the same reason, using unnamed namespaces is discouraged in the header files. Feel free to use them in your .cc files to avoid symbols showing up in your binary files. In some cases, changing all the internal details for a .cc file showed a 10% reduction in the generated binary sizes.
Changing visibility options
In newer compilers you can select your symbols to be either visible or invisible in the Dynamic Shared Objects (DSOs). Ideally, changing the visibility can improve compiler performance, link time optimizations (LTOs), and generated binary sizes. If you look at the STL header files in GCC you can see that it is widely used. To enable visibility choices, you need to change your code per function, per class, per variable and more importantly per compiler.
With the help of visibility you can hide the symbols that you consider them private from the generated shared objects. On GCC you can control the visibility of symbols by passing default or hidden to the -visibility option of your compiler. This is in some sense similar to the unnamed namespace but in a more elaborate and intrusive way.
If you would like to specify the visibilities per case, you have to add the following attributes to your functions, variables, and classes:
__attribute__((visibility("default"))) void foo1() { }
__attribute__((visibility("hidden"))) void foo2() { }
__attribute__((visibility("hidden"))) class foo3 { };
void foo4() { }
The default visibility in GCC is default (public), meaning that if you compile the above as a shared library (-shared) method, foo2 and class foo3 will not be visible in other TUs (foo1 and foo4 will be visible). If you compile with -visibility=hidden then only foo1 will be visible. Even foo4 would be hidden.
You can read more about visibility on GCC wiki.
I'd recommend these articles from "Games from Within, Indie Game Design And Programming":
Physical Structure and C++ – Part 1: A First Look
Physical Structure and C++ – Part 2: Build Times
Even More Experiments with Includes
How Incredible Is Incredibuild?
The Care and Feeding of Pre-Compiled Headers
The Quest for the Perfect Build System
The Quest for the Perfect Build System (Part 2)
Granted, they are pretty old - you'll have to re-test everything with the latest versions (or versions available to you), to get realistic results. Either way, it is a good source for ideas.
One technique which worked quite well for me in the past: don't compile multiple C++ source files independently, but rather generate one C++ file which includes all the other files, like this:
// myproject_all.cpp
// Automatically generated file - don't edit this by hand!
#include "main.cpp"
#include "mainwindow.cpp"
#include "filterdialog.cpp"
#include "database.cpp"
Of course this means you have to recompile all of the included source code in case any of the sources changes, so the dependency tree gets worse. However, compiling multiple source files as one translation unit is faster (at least in my experiments with MSVC and GCC) and generates smaller binaries. I also suspect that the compiler is given more potential for optimizations (since it can see more code at once).
This technique breaks in various cases; for instance, the compiler will bail out in case two or more source files declare a global function with the same name. I couldn't find this technique described in any of the other answers though, that's why I'm mentioning it here.
For what it's worth, the KDE Project used this exact same technique since 1999 to build optimized binaries (possibly for a release). The switch to the build configure script was called --enable-final. Out of archaeological interest I dug up the posting which announced this feature: http://lists.kde.org/?l=kde-devel&m=92722836009368&w=2
I will just link to my other answer: How do YOU reduce compile time, and linking time for Visual C++ projects (native C++)?. Another point I want to add, but which causes often problems is to use precompiled headers. But please, only use them for parts which hardly ever change (like GUI toolkit headers). Otherwise, they will cost you more time than they save you in the end.
Another option is, when you work with GNU make, to turn on -j<N> option:
-j [N], --jobs[=N] Allow N jobs at once; infinite jobs with no arg.
I usually have it at 3 since I've got a dual core here. It will then run compilers in parallel for different translation units, provided there are no dependencies between them. Linking cannot be done in parallel, since there is only one linker process linking together all object files.
But the linker itself can be threaded, and this is what the GNU gold ELF linker does. It's optimized threaded C++ code which is said to link ELF object files a magnitude faster than the old ld (and was actually included into binutils).
There's an entire book on this topic, which is titled Large-Scale C++ Software Design (written by John Lakos).
The book pre-dates templates, so to the contents of that book add "using templates, too, can make the compiler slower".
Once you have applied all the code tricks above (forward declarations, reducing header inclusion to the minimum in public headers, pushing most details inside the implementation file with Pimpl...) and nothing else can be gained language-wise, consider your build system. If you use Linux, consider using distcc (distributed compiler) and ccache (cache compiler).
The first one, distcc, executes the preprocessor step locally and then sends the output to the first available compiler in the network. It requires the same compiler and library versions in all the configured nodes in the network.
The latter, ccache, is a compiler cache. It again executes the preprocessor and then check with an internal database (held in a local directory) if that preprocessor file has already been compiled with the same compiler parameters. If it does, it just pops up the binary and output from the first run of the compiler.
Both can be used at the same time, so that if ccache does not have a local copy it can send it trough the net to another node with distcc, or else it can just inject the solution without further processing.
Here are some:
Use all processor cores by starting a multiple-compile job (make -j2 is a good example).
Turn off or lower optimizations (for example, GCC is much faster with -O1 than -O2 or -O3).
Use precompiled headers.
When I came out of college, the first real production-worthy C++ code I saw had these arcane #ifndef ... #endif directives in between them where the headers were defined. I asked the guy who was writing the code about these overarching things in a very naive fashion and was introduced to world of large-scale programming.
Coming back to the point, using directives to prevent duplicate header definitions was the first thing I learned when it came to reducing compiling times.
More RAM.
Someone talked about RAM drives in another answer. I did this with a 80286 and Turbo C++ (shows age) and the results were phenomenal. As was the loss of data when the machine crashed.
You could use Unity Builds.
Use
#pragma once
at the top of header files, so if they're included more than once in a translation unit, the text of the header will only get included and parsed once.
Use forward declarations where you can. If a class declaration only uses a pointer or reference to a type, you can just forward declare it and include the header for the type in the implementation file.
For example:
// T.h
class Class2; // Forward declaration
class T {
public:
void doSomething(Class2 &c2);
private:
Class2 *m_Class2Ptr;
};
// T.cpp
#include "Class2.h"
void Class2::doSomething(Class2 &c2) {
// Whatever you want here
}
Fewer includes means far less work for the preprocessor if you do it enough.
Just for completeness: a build might be slow because the build system is being stupid as well as because the compiler is taking a long time to do its work.
Read Recursive Make Considered Harmful (PDF) for a discussion of this topic in Unix environments.
Not about the compilation time, but about the build time:
Use ccache if you have to rebuild the same files when you are working
on your buildfiles
Use ninja-build instead of make. I am currently compiling a project
with ~100 source files and everything is cached by ccache. make needs
5 minutes, ninja less than 1.
You can generate your ninja files from cmake with -GNinja.
Upgrade your computer
Get a quad core (or a dual-quad system)
Get LOTS of RAM.
Use a RAM drive to drastically reduce file I/O delays. (There are companies that make IDE and SATA RAM drives that act like hard drives).
Then you have all your other typical suggestions
Use precompiled headers if available.
Reduce the amount of coupling between parts of your project. Changing one header file usually shouldn't require recompiling your entire project.
I had an idea about using a RAM drive. It turned out that for my projects it doesn't make that much of a difference after all. But then they are pretty small still. Try it! I'd be interested in hearing how much it helped.
Dynamic linking (.so) can be much much faster than static linking (.a). Especially when you have a slow network drive. This is since you have all of the code in the .a file which needs to be processed and written out. In addition, a much larger executable file needs to be written out to the disk.
Where are you spending your time? Are you CPU bound? Memory bound? Disk bound? Can you use more cores? More RAM? Do you need RAID? Do you simply want to improve the efficiency of your current system?
Under gcc/g++, have you looked at ccache? It can be helpful if you are doing make clean; make a lot.
Starting with Visual Studio 2017 you have the capability to have some compiler metrics about what takes time.
Add those parameters to C/C++ -> Command line (Additional Options) in the project properties window:
/Bt+ /d2cgsummary /d1reportTime
You can have more informations in this post.
Faster hard disks.
Compilers write many (and possibly huge) files to disk. Work with SSD instead of typical hard disk and compilation times are much lower.
On Linux (and maybe some other *NIXes), you can really speed the compilation by NOT STARING at the output and changing to another TTY.
Here is the experiment: printf slows down my program
Networks shares will drastically slow down your build, as the seek latency is high. For something like Boost, it made a huge difference for me, even though our network share drive is pretty fast. Time to compile a toy Boost program went from about 1 minute to 1 second when I switched from a network share to a local SSD.
If you have a multicore processor, both Visual Studio (2005 and later) as well as GCC support multi-processor compiles. It is something to enable if you have the hardware, for sure.
First of all, we have to understand what so different about C++ that sets it apart from other languages.
Some people say it's that C++ has many too features. But hey, there are languages that have a lot more features and they are nowhere near that slow.
Some people say it's the size of a file that matters. Nope, source lines of code don't correlate with compile times.
But wait, how can it be? More lines of code should mean longer compile times, what's the sorcery?
The trick is that a lot of lines of code is hidden in preprocessor directives. Yes. Just one #include can ruin your module's compilation performance.
You see, C++ doesn't have a module system. All *.cpp files are compiled from scratch. So having 1000 *.cpp files means compiling your project a thousand times. You have more than that? Too bad.
That's why C++ developers hesitate to split classes into multiple files. All those headers are tedious to maintain.
So what can we do other than using precompiled headers, merging all the cpp files into one, and keeping the number of headers minimal?
C++20 brings us preliminary support of modules! Eventually, you'll be able to forget about #include and the horrible compile performance that header files bring with them. Touched one file? Recompile only that file! Need to compile a fresh checkout? Compile in seconds rather than minutes and hours.
The C++ community should move to C++20 as soon as possible. C++ compiler developers should put more focus on this, C++ developers should start testing preliminary support in various compilers and use those compilers that support modules. This is the most important moment in C++ history!
Although not a "technique", I couldn't figure out how Win32 projects with many source files compiled faster than my "Hello World" empty project. Thus, I hope this helps someone like it did me.
In Visual Studio, one option to increase compile times is Incremental Linking (/INCREMENTAL). It's incompatible with Link-time Code Generation (/LTCG) so remember to disable incremental linking when doing release builds.
Using dynamic linking instead of static one make you compiler faster that can feel.
If you use t Cmake, active the property:
set(BUILD_SHARED_LIBS ON)
Build Release, using static linking can get more optimize.
From Microsoft: https://devblogs.microsoft.com/cppblog/recommendations-to-speed-c-builds-in-visual-studio/
Specific recommendations include:
DO USE PCH for projects
DO include commonly used system, runtime and third party headers in
PCH
DO include rarely changing project specific headers in PCH
DO NOT include headers that change frequently
DO audit PCH regularly to keep it up to date with product churn
DO USE /MP
DO Remove /Gm in favor of /MP
DO resolve conflict with #import and use /MP
DO USE linker switch /incremental
DO USE linker switch /debug:fastlink
DO consider using a third party build accelerator
How do YOU reduce compile time, and linking time for VC++ projects (native C++)?
Please specify if each suggestion applies to debug, release, or both.
It may sound obvious to you, but we try to use forward declarations as much as possible, even if it requires to write out long namespace names the type(s) is/are in:
// Forward declaration stuff
namespace plotter { namespace logic { class Plotter; } }
// Real stuff
namespace plotter {
namespace samples {
class Window {
logic::Plotter * mPlotter;
// ...
};
}
}
It greatly reduces the time for compiling also on others compilers. Indeed it applies to all configurations :)
Use the Handle/Body pattern (also sometimes known as "pimpl", "adapter", "decorator", "bridge" or "wrapper"). By isolating the implementation of your classes into your .cpp files, they need only be compiled once. Most changes do not require changes to the header file so it means you can make fairly extensive changes while only requiring one file to be recompiled. This also encourages refactoring and writing of comments and unit tests since compile time is decreased. Additionally, you automatically separate the concerns of interface and implementation so the interface of your code is simplified.
If you have large complex headers that must be included by most of the .cpp files in your build process, and which are not changed very often, you can precompile them. In a Visual C++ project with a typical configuration, this is simply a matter of including them in stdafx.h. This feature has its detractors, but libraries that make full use of templates tend to have a lot of stuff in headers, and precompiled headers are the simplest way to speed up builds in that case.
These solutions apply to both debug and release, and are focused on a codebase that is already large and cumbersome.
Forward declarations are a common solution.
Distributed building, such as with Incredibuild is a win.
Pushing code from headers down into source files can work. Small classes, constants, enums and so on might start off in a header file simply because it could have been used in multiple compilation units, but in reality they are only used in one, and could be moved to the cpp file.
A solution I haven't read about but have used is to split large headers. If you have a handful of very large headers, take a look at them. They may contain related information, and may also depend on a lot of other headers. Take the elements that have no dependencies on other files...simple structs, constants, enums and forward declarations and move them from the_world.h to the_world_defs.h. You may now find that a lot of your source files can now include only the_world_defs.h and avoid including all that overhead.
Visual Studio also has a "Show Includes" option that can give you a sense of which source files include many headers and which header files are most frequently included.
For very common includes, consider putting them in a pre-compiled header.
I use Unity Builds (Screencast located here).
The compile speed question is interesting enough that Stroustrup has it in his FAQ.
We use Xoreax's Incredibuild to run compilation in parallel across multiple machines.
Also an interesting article from Ned Batchelder: http://nedbatchelder.com/blog/200401/speeding_c_links.html (about C++ on Windows).
Our development machines are all quad-core and we use Visual Studio 2008 supports parallel compiling. I am uncertain as to whether all editions of VS can do this.
We have a solution file with approximately 168 individual projects, and compile this way takes about 25 minutes on our quad-core machines, compared to about 90 minutes on the single core laptops we give to summer students. Not exactly comparable machines but you get the idea :)
With Visual C++, there is a method, some refer to as Unity, that improves link time significantly by reducing the number of object modules.
This involves concatenating the C++ code, usually in groups by library. This of course makes editing the code much more difficult, and you will run into namespace collisions unless you use them well. It keeps you from using "using namespace foo";
Several teams at our company have elaborate systems to take the normal C++ files and concatenate them at compile time as a build step. The reduction in link times can be enormous.
Another useful technique is blobbing. I think it is something similar to what was described by Matt Shaw.
Simply put, you just create one cpp file in which you include other cpp files. You may have two different project configurations, one ordinary and one blob. Of course, blobbing puts some constrains on your code, e.g. class names in unnamed namespaces may clash.
One technique to avoid recompiling the whole code in a blob (as David Rodríguez mentioned) when you change one cpp file - is to have your "working" blob which is created from files modified recently and other ordinary blobs.
We use blobbing at work most of the time, and it reduces project build time, especially link time.
Compile Time:
If you have IncrediBuild, compile time won't be a problem. If you don't have a IncrediBuild, try the "unity build" method. It combine multiple cpp files to a single cpp file so the whole compile time is reduced.
Link Time:
The "unity build" method also contribute to reduce the link time but not much. How ever, you can check if the "Whole global optimization" and "LTCG" are enabled, while these flags make the program fast, they DO make the link SLOW.
Try turning off the "Whole Global Optimization" and set LTCG to "Default" the link time might be reduced by 5/6. (LTCG stands for Link Time Code Generation)
We have project which uses gcc and make files. Project also contains of one big subproject (SDK) and a lot of relatively small subprojects which use that SDK and some shared framework.
We use precompiled headers, but that helps only for re-compilation to be faster.
Is there any known techniques and tools to help with build-time optimizations? Or maybe you know some articles/resources about this or related topics?
You can tackle the problem from two sides: refactor the code to reduce the complexity the compiler is seeing, or speed up the compiler execution.
Without touching the code, you can add more compilation power into it. Use ccache to avoid recompiling files you have already compiled and distcc to distribute the build time among more machines. Use make -j where N is the number of cores+1 if you compile locally, or a bigger number for distributed builds. That flag will run more than one compiler in parallel.
Refactoring the code. Prefer forward declaration to includes (simple). Decouple as much as you can to avoid dependencies (use the PIMPL idiom).
Template instantiation is expensive, they are recompiled in every compilation unit that uses them. If you can refactor your templates as to forward declare them and then instantiate them in only one compilation unit.
The best I can think of with make is the -j option. This tells make to run as many jobs as possible in parallel:
make -j
If you want to limit the number of concurrent jobs to n you can use:
make -j n
Make sure the dependencies are correct so make doesn't run jobs it doesn't have to.
Another thing to take into account is optimizations that gcc does with the -O switch. You can specify various levels of optimization. The higher the optimization, the longer the compile and link times. A project I work with runs takes 2 minutes to link with -O3, and half a minute with -O1. You should make sure you're not optimizing more than you need to. You could build without optimization for development builds and with optimization for deployment builds.
Compiling with debug info (gcc -g) will probably increase the size of your executable and may impact your build time. If you don't need it, try removing it to see if it affects you.
The type of linking (static vs. dynamic) should make a difference. As far as I understand static linking takes longer (though I may be wrong here). You should see if this affects your build.
From the description of the project I guess that you have one Makefile per directory and are using recursive make a lot. In that case techniques from "Recursive Make Considered Harmful" should help very much.
If you have multiple computers available gcc is well distributed by distcc.
You can also use ccache in addition.
All this works with very little changes of the makefiles.
Also, you'll probably want to keep your source code files as small and self-contained as possible/feasible, i.e. prefer many smaller object files over one huge single object file.
This will also help avoid unnecessary recompilations, in addition you can have one static library with object files for each source code directory or module, basically allowing the compiler to reuse as much previously compiled code as possible.
Something else, which wasn't yet mentioned in any of the previous responses, is making symbol linkage as 'private' as possible, i.e. prefer static linkage (functions, variables) for your code if it doesn't have to be visible externally.
In addition, you may also want to look into using the GNU gold linker, which is much more efficient for compiling C++ code for ELF targets.
Basically, I'd advise you to carefully profile your build process and check where the most time is spend, that'll give you some hints as to how to optimize your build process or your projects source code structure.
You could consider switching to a different build system (which obviously won't work for everyone), such as SCons. SCons is much smarter than make. It automatically scans header dependencies, so you always have the smallest set of rebuild dependencies. By adding the line Decider('MD5-timestamp') to your SConstruct file, SCons will first look at the time stamp of a file, and if it's newer than the previously built time stamp, it will use the MD5 of the file to make sure you actually changed something. This works not just on source files but object files as well. This means that if you change a comment, for instance, you don't have to re-link.
The automatic scanning of header files has also ensured that I never have to type scons --clean. It always does the right thing.
If you have a LAN with developer machines, perhaps you should try implementing a distributed compiler solution, such as distcc.
This might not help if all of the time during the build is spent analyzing dependencies, or doing some single serial task. For the raw crunch of compiling many source files into object files, parallel building obviously helps, as suggested (on a single machine) by Nathan. Parallelizing across multiple machines can take it even further.
http://ccache.samba.org/ speeds up big time.
I work on a middle sized project, and that's the only thing we do to speed up the compile time.
You can use distcc distributed compiler to reduce the build time if you have access to several machines.
Here's an article from from IBM developerWorks related to distcc and how you can use it:
http://www.ibm.com/developerworks/linux/library/l-distcc.html
Another method to reduce build time is to use precompiled headers. Here's a starting point for gcc.
Also don't forget to use -j when building with make if your machine has more than one cpu/core(2x the number of cores/cpus is just fine).
Using small files may not always be a good recommendation. A disk have a 32 or 64K min sector size, with a file taking at least a sector. So 1024 files of 3K size (small code inside) will actually take 32 or 64 Meg on disk, instead of the expected 3 meg. 32/64 meg that needs to be read by the drive. If files are dispersed around on the disk you increase read time even more with seek time. This is helped with Disk Cache obviously, to a limit. pre-compiled header can also be of good help alleviating this.
So with due respect to coding guidelines, there is no point in going out of them just to place each strcuct, typedef or utility class into separate files.