196 lines
8.7 KiB
Markdown
196 lines
8.7 KiB
Markdown
# Quickstart
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In the root library folder execute:
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```sh
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$ mkdir build
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$ cd build
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$ cmake ..
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$ make check # (optional, runs unit tests)
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$ make install
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```
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## Important Installation Notes
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1. GTSAM requires the following libraries to be installed on your system:
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- BOOST version 1.58 or greater (install through Linux repositories or MacPorts)
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- Cmake version 3.0 or higher
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- Support for XCode 4.3 command line tools on Mac requires CMake 2.8.8 or higher
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Optional dependent libraries:
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- If TBB is installed and detectable by CMake GTSAM will use it automatically.
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Ensure that CMake prints "Use Intel TBB : Yes". To disable the use of TBB,
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disable the CMake flag GTSAM_WITH_TBB (enabled by default). On Ubuntu, TBB
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may be installed from the Ubuntu repositories, and for other platforms it
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may be downloaded from https://www.threadingbuildingblocks.org/
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- GTSAM may be configured to use MKL by toggling `GTSAM_WITH_EIGEN_MKL` and
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`GTSAM_WITH_EIGEN_MKL_OPENMP` to `ON`; however, best performance is usually
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achieved with MKL disabled. We therefore advise you to benchmark your problem
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before using MKL.
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Tested compilers:
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- GCC 4.2-7.3
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- OS X Clang 2.9-10.0
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- OS X GCC 4.2
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- MSVC 2010, 2012, 2017
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Tested systems:
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- Ubuntu 16.04 - 18.04
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- MacOS 10.6 - 10.14
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- Windows 7, 8, 8.1, 10
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Known issues:
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- MSVC 2013 is not yet supported because it cannot build the serialization module
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of Boost 1.55 (or earlier).
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2. GTSAM makes extensive use of debug assertions, and we highly recommend you work
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in Debug mode while developing (enabled by default). Likewise, it is imperative
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that you switch to release mode when running finished code and for timing. GTSAM
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will run up to 10x faster in Release mode! See the end of this document for
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additional debugging tips.
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3. GTSAM has Doxygen documentation. To generate, run 'make doc' from your
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build directory.
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4. The instructions below install the library to the default system install path and
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build all components. From a terminal, starting in the root library folder,
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execute commands as follows for an out-of-source build:
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```sh
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$ mkdir build
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$ cd build
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$ cmake ..
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$ make check (optional, runs unit tests)
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$ make install
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```
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This will build the library and unit tests, run all of the unit tests,
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and then install the library itself.
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## CMake Configuration Options and Details
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GTSAM has a number of options that can be configured, which is best done with
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one of the following:
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- ccmake the curses GUI for cmake
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- cmake-gui a real GUI for cmake
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### Important Options:
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#### CMAKE_BUILD_TYPE
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We support several build configurations for GTSAM (case insensitive)
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```cmake -DCMAKE_BUILD_TYPE=[Option] ..```
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- Debug (default) All error checking options on, no optimization. Use for development.
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- Release Optimizations turned on, no debug symbols.
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- Timing Adds ENABLE_TIMING flag to provide statistics on operation
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- Profiling Standard configuration for use during profiling
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- RelWithDebInfo Same as Release, but with the -g flag for debug symbols
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#### CMAKE_INSTALL_PREFIX
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The install folder. The default is typically `/usr/local/`.
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To configure to install to your home directory, you could execute:
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```cmake -DCMAKE_INSTALL_PREFIX:PATH=$HOME ..```
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#### GTSAM_TOOLBOX_INSTALL_PATH
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The Matlab toolbox will be installed in a subdirectory
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of this folder, called 'gtsam'.
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```cmake -DGTSAM_TOOLBOX_INSTALL_PATH:PATH=$HOME/toolbox ..```
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#### GTSAM_BUILD_CONVENIENCE_LIBRARIES
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This is a build option to allow for tests in subfolders to be linked against convenience libraries rather than the full libgtsam.
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Set with the command line as follows:
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```cmake -DGTSAM_BUILD_CONVENIENCE_LIBRARIES:OPTION=ON ..```
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- 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.
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- 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.
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#### GTSAM_BUILD_UNSTABLE
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Enable build and install for libgtsam_unstable library.
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Set with the command line as follows:
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```cmake -DGTSAM_BUILD_UNSTABLE:OPTION=ON ..```
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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`.
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OFF (Default) If disabled, no `gtsam_unstable` code will be included in build or install.
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## Check
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`make check` will build and run all of the tests. Note that the tests will only be
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built when using the "check" targets, to prevent `make install` from building the tests
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unnecessarily. You can also run `make timing` to build all of the timing scripts.
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To run check on a particular module only, run `make check.[subfolder]`, so to run
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just the geometry tests, run `make check.geometry`. Individual tests can be run by
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appending `.run` to the name of the test, for example, to run testMatrix, run
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`make testMatrix.run`.
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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 `$MATLABROOT/bin/mex`
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$MATLABROOT can be found by executing the command `matlabroot` in MATLAB
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## Performance
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Here are some tips to get the best possible performance out of GTSAM.
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1. Build in `Release` mode. GTSAM will run up to 10x faster compared to `Debug` mode.
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2. Enable TBB. On modern processors with multiple cores, this can easily speed up
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optimization by 30-50%. Please note that this may not be true for very small
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problems where the overhead of dispatching work to multiple threads outweighs
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the benefit. We recommend that you benchmark your problem with/without TBB.
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3. Add `-march=native` to `GTSAM_CMAKE_CXX_FLAGS`. A performance gain of
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25-30% can be expected on modern processors. Note that this affects the portability
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of your executable. It may not run when copied to another system with older/different
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processor architecture.
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Also note that all dependent projects *must* be compiled with the same flag, or
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seg-faults and other undefined behavior may result.
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4. Possibly enable MKL. Please note that our benchmarks have shown that this helps only
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in very limited cases, and actually hurts performance in the usual case. We therefore
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recommend that you do *not* enable MKL, unless you have benchmarked it on
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your problem and have verified that it improves performance.
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## Debugging tips
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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.
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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.
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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.
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## Installing MKL on Linux
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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>.
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After following the instructions, add the following to your `~/.bashrc` (and afterwards, open a new terminal before compiling GTSAM):
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`LD_PRELOAD` need only be set if you are building the python wrapper to use GTSAM from python.
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```sh
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source /opt/intel/mkl/bin/mklvars.sh intel64
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export LD_PRELOAD="$LD_PRELOAD:/opt/intel/mkl/lib/intel64/libmkl_core.so:/opt/intel/mkl/lib/intel64/libmkl_sequential.so"
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```
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To use MKL in GTSAM pass the flag `-DGTSAM_WITH_EIGEN_MKL=ON` to cmake.
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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:
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- <https://software.intel.com/en-us/forums/intel-math-kernel-library/topic/300857>
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- <https://software.intel.com/en-us/forums/intel-distribution-for-python/topic/628976>
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- <https://groups.google.com/a/continuum.io/forum/#!topic/anaconda/J3YGoef64z8>
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Failing to specify `LD_PRELOAD` may lead to errors such as:
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`ImportError: /opt/intel/mkl/lib/intel64/libmkl_vml_avx2.so: undefined symbol: mkl_serv_getenv`
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or
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`Intel MKL FATAL ERROR: Cannot load libmkl_avx2.so or libmkl_def.so.`
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when importing GTSAM using the python wrapper.
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