In the root library folder execute:
$ mkdir build
$ cd build
$ cmake ..
$ make check # (optional, runs unit tests)
$ make install
GTSAM requires the following libraries to be installed on your system:
BOOST version 1.65 or greater (install through Linux repositories or MacPorts). Please see Boost Notes.
Cmake version 3.0 or higher
Support for XCode 4.3 command line tools on Mac requires CMake 2.8.8 or higher
Optional dependent libraries:
GTSAM_WITH_TBB
(enabled by default) by providing
the argument -DGTSAM_WITH_TBB=OFF
to cmake
. On Ubuntu, TBB may be
installed from the Ubuntu repositories, and for other platforms it may be
downloaded from https://www.threadingbuildingblocks.org/GTSAM_WITH_EIGEN_MKL
and
GTSAM_WITH_EIGEN_MKL_OPENMP
to ON
; however, best performance is usually
achieved with MKL disabled. We therefore advise you to benchmark your problem
before using MKL.Tested compilers:
Tested systems:
GTSAM makes extensive use of debug assertions, and we highly recommend you work in Debug mode while developing (enabled by default). Likewise, it is imperative that you switch to release mode when running finished code and for timing. GTSAM will run up to 10x faster in Release mode! See the end of this document for additional debugging tips.
GTSAM has Doxygen documentation. To generate, run 'make doc' from your build directory.
The instructions below install the library to the default system install path and build all components. From a terminal, starting in the root library folder, execute commands as follows for an out-of-source build:
$ mkdir build
$ cd build
$ cmake ..
$ make check (optional, runs unit tests)
$ make install
This will build the library and unit tests, run all of the unit tests, and then install the library itself.
Versions of Boost prior to 1.65 have a known bug that prevents proper "deep" serialization of objects, which means that objects encapsulated inside other objects don't get serialized.
This is particularly seen when using clang
as the C++ compiler.
For this reason we require Boost>=1.65, and recommend installing it through alternative channels when it is not available through your operating system's primary package manager.
This section details how to build a GTSAM .sln
file using Visual Studio.
Open a local folder
and select the GTSAM source directory.Project -> CMake Settings
.
Configuration name
.Configuration type
.Toolset
to msvc_x64_x64
. If you know what toolset you require, then skip this step.Build root
to ${projectDir}\build\${name}
.Release
build.Show advanced settings
.CMake generator
, select a version which matches Visual Studio <Version> <Year> Win64
, e.g. Visual Studio 16 2019 Win64
.Project -> Generate Cache
. This will generate the CMake build files (as seen in the Output window).GTSAM.sln
file in the build
directory. At this point, GTSAM can be used as a regular Visual Studio project.GTSAM has a number of options that can be configured, which is best done with one of the following:
We support several build configurations for GTSAM (case insensitive)
- Debug (default) All error checking options on, no optimization. Use for development.
- Release Optimizations turned on, no debug symbols.
- Timing Adds ENABLE_TIMING flag to provide statistics on operation
- Profiling Standard configuration for use during profiling
- RelWithDebInfo Same as Release, but with the -g flag for debug symbols
#### CMAKE_INSTALL_PREFIX
The install folder. The default is typically `/usr/local/`.
To configure to install to your home directory, you could execute:
```cmake -DCMAKE_INSTALL_PREFIX:PATH=$HOME ..```
#### GTSAM_TOOLBOX_INSTALL_PATH
The Matlab toolbox will be installed in a subdirectory
of this folder, called 'gtsam'.
```cmake -DGTSAM_TOOLBOX_INSTALL_PATH:PATH=$HOME/toolbox ..```
#### GTSAM_BUILD_CONVENIENCE_LIBRARIES
This is a build option to allow for tests in subfolders to be linked against convenience libraries rather than the full libgtsam.
Set with the command line as follows:
```cmake -DGTSAM_BUILD_CONVENIENCE_LIBRARIES:OPTION=ON ..```
- ON (Default): This builds convenience libraries and links tests against them. This option is suggested for gtsam developers, as it is possible to build and run tests without first building the rest of the library, and speeds up compilation for a single test. The downside of this option is that it will build the entire library again to build the full libgtsam library, so build/install will be slower.
- OFF: This will build all of libgtsam before any of the tests, and then link all of the tests at once. This option is best for users of GTSAM, as it avoids rebuilding the entirety of gtsam an extra time.
#### GTSAM_BUILD_UNSTABLE
Enable build and install for libgtsam_unstable library.
Set with the command line as follows:
```cmake -DGTSAM_BUILD_UNSTABLE:OPTION=ON ..```
ON: When enabled, libgtsam_unstable will be built and installed with the same options as libgtsam. In addition, if tests are enabled, the unit tests will be built as well. The Matlab toolbox will also be generated if the matlab toolbox is enabled, installing into a folder called `gtsam_unstable`.
OFF (Default) If disabled, no `gtsam_unstable` code will be included in build or install.
## Check
`make check` will build and run all of the tests. Note that the tests will only be
built when using the "check" targets, to prevent `make install` from building the tests
unnecessarily. You can also run `make timing` to build all of the timing scripts.
To run check on a particular module only, run `make check.[subfolder]`, so to run
just the geometry tests, run `make check.geometry`. Individual tests can be run by
appending `.run` to the name of the test, for example, to run testMatrix, run
`make testMatrix.run`.
MEX_COMMAND: Path to the mex compiler. Defaults to assume the path is included in your shell's PATH environment variable. mex is installed with matlab at `$MATLABROOT/bin/mex`
$MATLABROOT can be found by executing the command `matlabroot` in MATLAB
## Performance
Here are some tips to get the best possible performance out of GTSAM.
1. Build in `Release` mode. GTSAM will run up to 10x faster compared to `Debug` mode.
2. Enable TBB. On modern processors with multiple cores, this can easily speed up
optimization by 30-50%. Please note that this may not be true for very small
problems where the overhead of dispatching work to multiple threads outweighs
the benefit. We recommend that you benchmark your problem with/without TBB.
3. Add `-march=native` to `GTSAM_CMAKE_CXX_FLAGS`. A performance gain of
25-30% can be expected on modern processors. Note that this affects the portability
of your executable. It may not run when copied to another system with older/different
processor architecture.
Also note that all dependent projects *must* be compiled with the same flag, or
seg-faults and other undefined behavior may result.
4. Possibly enable MKL. Please note that our benchmarks have shown that this helps only
in very limited cases, and actually hurts performance in the usual case. We therefore
recommend that you do *not* enable MKL, unless you have benchmarked it on
your problem and have verified that it improves performance.
## Debugging tips
Another useful debugging symbol is _GLIBCXX_DEBUG, which enables debug checks and safe containers in the standard C++ library and makes problems much easier to find.
NOTE: The native Snow Leopard g++ compiler/library contains a bug that makes it impossible to use _GLIBCXX_DEBUG. MacPorts g++ compilers do work with it though.
NOTE: If _GLIBCXX_DEBUG is used to compile gtsam, anything that links against gtsam will need to be compiled with _GLIBCXX_DEBUG as well, due to the use of header-only Eigen.
## Installing MKL on Linux
Intel has a guide for installing MKL on Linux through APT repositories at <https://software.intel.com/en-us/articles/installing-intel-free-libs-and-python-apt-repo>.
After following the instructions, add the following to your `~/.bashrc` (and afterwards, open a new terminal before compiling GTSAM):
`LD_PRELOAD` need only be set if you are building the python wrapper to use GTSAM from python.
```sh
source /opt/intel/mkl/bin/mklvars.sh intel64
export LD_PRELOAD="$LD_PRELOAD:/opt/intel/mkl/lib/intel64/libmkl_core.so:/opt/intel/mkl/lib/intel64/libmkl_sequential.so"
To use MKL in GTSAM pass the flag -DGTSAM_WITH_EIGEN_MKL=ON
to cmake.
The LD_PRELOAD
fix seems to be related to a well known problem with MKL which leads to lots of undefined symbol errors, for example:
Failing to specify LD_PRELOAD
may lead to errors such as:
ImportError: /opt/intel/mkl/lib/intel64/libmkl_vml_avx2.so: undefined symbol: mkl_serv_getenv
or
Intel MKL FATAL ERROR: Cannot load libmkl_avx2.so or libmkl_def.so.
when importing GTSAM using the python wrapper.