CMake Options for NEST

Before compiling and installing NEST, the source code has to be configured with cmake. In the simplest case, the commands:

cmake <nest_source_dir>
make
make install

will build NEST and install it to the site-packages of your Python environment.

Note

If you want to specify an alternative install location, use -DCMAKE_INSTALL_PREFIX:PATH=<nest_install_dir>. It needs to be writable by the user running the install command.

Choice of compiler

We systematically test NEST using the GNU gcc and the Clang compiler suites. Compilation with other up-to-date compilers should also work, but we do not regularly test against those compilers and can thus only provide limited support.

To select a specific compiler, please add the following flags to your cmake command line:

-DCMAKE_C_COMPILER=<C-compiler> -DCMAKE_CXX_COMPILER=<C++-compiler>

Options for configuring NEST

NEST allows for several configuration options for custom builds:

Minimal configuration

NEST can be compiled without any external packages; such a configuration may be useful for initial porting to a new supercomputer. However, this implies several restrictions:

• Some neuron and synapse models will not be available, as they depend on ODE solvers from the GNU Scientific Library.

• The Python extension will not be available

• Multi-threading and parallel computing facilities will be disabled.

To configure NEST for compilation without external packages, use the following command:

cmake -DCMAKE_INSTALL_PREFIX:PATH=<nest_install_dir> \
      -Dwith-python=OFF \
      -Dwith-gsl=OFF \
      -Dwith-readline=OFF \
      -Dwith-ltdl=OFF \
      -Dwith-openmp=OFF \
      </path/to/nest/source>

See the CMake Options to further adjust settings for your system.

Select built-in models

By default, NEST will compile and register all neuron and synapse models that are shipped in the source distribution. This is very convenient for an explorative development of simulation scripts, but leads to quite long compilation times and is often not necessary.

There are two ways to restrict the set of built-in models to tailor NEST to your needs:

-Dwith-modelset=<modelset>	Specify the modelset to include. Sample configurations are in the modelsets directory in the top-level of the source tree. A modelset is just a file listing one model header files (without the .h filename extension) to scan for models. This option is mutually exclusive with -Dwith-models. [default=full].
-Dwith-models=[<modellist>|OFF]	Specify the models to include as a semicolon-separated list of model header files (without the .h filename extension) that are to be scanned for models. This option is mutually exclusive with -Dwith-modelset. [default=OFF].

Use Python to build PyNEST

-Dwith-python=[OFF|ON]	Build PyNEST [default=ON].
-Dcythonize-pynest=[OFF|ON]	Use Cython to cythonize pynestkernel.pyx [default=ON]. If OFF, PyNEST has to be build from a pre-cythonized pynestkernel.pyx.

For more details, see the Python binding section below.

Maximize performance, reduce energy consumption

The following options help to optimize NEST for maximal performance and thus reduced energy consumption.

-Dwith-optimize="-O3 -march=native"	Activate most compiler options that do not affect compliance with IEEE754 numerics and optimize for CPU type used
-Dwith-defines=-DNDEBUG	Disable all assert() statements in NEST

Note

• In our experience, gains from these optimizations are not very large. It can still be sensible to test them, especially if you are going to perform a large number of simulations.

• Your particular use case may contain edge cases during NEST execution that our extensive test suite has not covered. Internal consistency tests in NEST in the form of assert() statements can help to detect such edge cases. Using the optimization options above removes these internal checks and thus increases the risk that NEST will produce incorrect results. Therefore, use these options only after you have performed multiple simulations of your specific model with default optimization settings (i.e., -O2), which leaves the assertions in place.

• Using -march=native requires that you build NEST on the same CPU architecture as you will use to run it.

• For the technically minded: Even just using -O3 removes some assert() statements from NEST since we have wrapped some of them in functions, which get eliminated due to interprocedural optimization.

Select parallelization scheme

-Dwith-mpi=[OFF|ON]	Build with MPI parallelization [default=OFF].
-Dwith-openmp=[OFF|ON|<OpenMP-Flag>]	Build with OpenMP multi-threading [default=ON]. Optionally set OMP compiler flags.

See also the section on building with MPI below.

Build documentation

-Dwith-devdoc=[OFF|ON]	Build the developer (doxygen) documentation [default=OFF]
-Dwith-userdoc=[OFF|ON]	Build the user (Sphinx) documentation [default=OFF]

If either documentation build is toggled to ON, you can then run make docs if you only want to build the docs.

See also the documentation workflow for user-facing and technical docs.

External libraries

-Dwith-libneurosim=[OFF|ON|</path/to/libneurosim>]	Build with libneurosim [default=OFF]. Optionally give the directory where libneurosim is installed.
-Dwith-music=[OFF|ON|</path/to/music>]	Build with MUSIC [default=OFF]. Optionally give the directory where MUSIC is installed.
-Dwith-sionlib=[OFF|ON|</path/to/sionlib>]	Build with sionlib [default=OFF]. Optionally give the directory where sionlib is installed.
-Dwith-boost=[OFF|ON|</path/to/boost>]	Build with Boost [default=ON]. To set a specific Boost installation, give the install path.
-Dwith-readline=[OFF|ON|</path/to/readline>]	Build with GNU Readline library [default=ON]. To set a specific library, give the install path.
-Dwith-ltdl=[OFF|ON|</path/to/ltdl>]	Build with ltdl library [default=ON]. To set a specific ltdl, give the install path. NEST uses ltdl for dynamic loading of external user modules.
-Dwith-gsl=[OFF|ON|</path/to/gsl>]	Build with the GSL library [default=ON]. To set a specific library, give the install path.
-Dwith-hdf5=[OFF|ON|</path/to/hdf5>]	Build with HDF5 library [default=OFF]. To set a specific library, give the install path. HDF5 is required for SONATA support, see NEST SONATA guide.

NEST properties

-Dtics_per_ms=[number]	Specify elementary unit of time [default=1000 tics per ms].
-Dtics_per_step=[number]	Specify resolution [default=100 tics per step].
-Dwith-threaded-timers=[OFF|ON]	Build with one internal timer per thread [default=ON]. Multi-threaded timers can affect the performance.
-Dwith-detailed-timers=[OFF|ON] | Build with detailed internal time measurements [default=OFF]. Detailed timers can affect the performance.
-Dwith-mpi-sync-timer=[OFF|ON] | Build with mpi synchronization barrier and timer [default=OFF]. Can affect the performance.
-Dtarget-bits-split=['standard'|'hpc']	Split of the 64-bit target neuron identifier type [default=’standard’]. ‘standard’ is recommended for most users. If running on more than 262144 MPI processes or more than 512 threads, change to ‘hpc’.
-Dwith-full-logging=[OFF|ON]	Write debug output to file dump_<num_ranks>_<rank>.log [default=OFF]. Developers should wrap debugging output in macro FULL_LOGGING_ONLY() and call kernel().write_dump()` from inside it. The macro can contain almost any valid code.

Generic build configuration

-Dstatic-libraries=[OFF|ON]	Build static executable and libraries [default=OFF].
-Dwith-optimize=[OFF|ON|<list;of;flags>]	Enable user defined optimizations [default=ON (uses ‘-O2’)]. When OFF, no ‘-O’ flag is passed to the compiler. Explicit compiler flags can be given; separate multiple flags by ‘;’.”
-Dwith-warning=[OFF|ON|<list;of;flags>]	Enable user defined warnings [default=ON (uses ‘-Wall’)]. Separate multiple flags by ‘;’.
-Dwith-debug=[OFF|ON|<list;of;flags>]	Enable user defined debug flags [default=OFF]. When ON, ‘-g’ is used. Separate multiple flags by ‘;’.
-Dwith-intel-compiler-flags=[OFF|<list;of;flags>]	User defined flags for the Intel compiler [default=’-fp-model strict’]. Separate multiple flags by ‘;’.
-Dwith-cpp-std=[<C++ standard>]	C++ standard to use for compilation [default=’c++17’].
-Dwith-libraries=[OFF|<list;of;libraries>]	Link additional libraries [default=OFF]. Give full path. Separate multiple libraries by ‘;’.
-Dwith-includes=[OFF|<list;of;includes>]	Add additional include paths [default=OFF]. Give full path without ‘-I’. Separate multiple include paths by ‘;’.
-Dwith-defines=[OFF|<list;of;defines>]	Additional defines, e.g. ‘-DXYZ=1’ [default=OFF]. Separate multiple defines by ‘;’.
-Dwith-version-suffix=[string]	Set a user defined version suffix [default=’’].

Configuring NEST for Distributed Simulation with MPI

NEST supports distributed simulations using the Message Passing Interface (MPI). Depending on your setup, you have to use one of the following steps in order to add support for MPI:

1. Try -Dwith-mpi=ON as argument for cmake.

2. If 1. does not work, or you want to use a non-standard MPI, try -Dwith-mpi=/path/to/my/mpi. The mpi directory should contain the include, lib and bin subdirectories of the MPI installation.

3. IfO 2. does not work, but you know the correct compiler wrapper for your installation, try adding the following to the invocation of cmake:

   -DMPI_CXX_COMPILER=myC++_CompilerWrapper \
   -DMPI_C_COMPILER=myC_CompilerWrapper -Dwith-mpi=ON
   

When running large-scale parallel simulations and recording from many neurons, writing to ASCII files might become prohibitively slow due to the large number of resulting files. By installing the SIONlib library and supplying its installation path to the -Dwith-sionlib=<path> option when calling cmake, you can enable the recording backend for binary files, which solves this problem.

In order to run the distributed tests upon make installcheck, NEST needs to know how to execute the launcher of your MPI implementation. CMake is usually able to detect the command line for this, but you can customize it using the follwing configuration variables (common defaults are shown below):

-DMPIEXEC=/usr/bin/mpirun
-DMPIEXEC_NUMPROCS_FLAG=-np
-DMPIEXEC_PREFLAGS=
-DMPIEXEC_POSTFLAGS=

The final command line is composed in the following way:

$MPIEXEC $MPIEXEC_NUMPROC_FLAG <np> $MPIEXEC_PREFLAGS <prog> $MPIEXEC_POSTFLAGS <args>

For details on setting specific flags for your MPI launcher command, see the CMake documentation.

See the Guide to parallel computing to learn how to execute threaded and distributed simulations with NEST.

Support for libneurosim

In order to allow NEST to create connections using external libraries, it provides support for the Connection Generator Interface from libneurosim. To request the use of libneurosim, you have to use the follwing switch for the invocation of cmake. It expects either ON or OFF, or the directory where libneurosim is installed:

-Dwith-libneurosim=[OFF|ON|</path/to/libneurosim>]

For details on how to use the Connection Generator Interface, see the guide on connection generation.

Python Binding (PyNEST)

Note that since NEST 3.0, support for Python 2 has been dropped. Please use Python 3 instead.

cmake usually autodetects your Python installation. In some cases cmake might not be able to localize the Python interpreter and its corresponding libraries correctly. To circumvent such a problem following cmake built-in variables can be set manually and passed to cmake:

 PYTHON_EXECUTABLE ..... path to the Python interpreter
 PYTHON_LIBRARY ........ path to libpython
 PYTHON_INCLUDE_DIR .... two include ...
 PYTHON_INCLUDE_DIR2 ... directories

e.g.: Please note ``-Dwith-python=ON`` is the default::
 cmake -DCMAKE_INSTALL_PREFIX=<nest_install_dir> \
       -DPYTHON_EXECUTABLE=/usr/bin/python3 \
       -DPYTHON_LIBRARY=/usr/lib/x86_64-linux-gnu/libpython3.4m.so \
       -DPYTHON_INCLUDE_DIR=/usr/include/python3.4 \
       -DPYTHON_INCLUDE_DIR2=/usr/include/x86_64-linux-gnu/python3.4m \
       <nest_source_dir>

Compiler-specific options

NEST has reasonable default compiler options for the most common compilers.

Intel compiler

To ensure that computations obey the IEEE754 standard for floating point numerics, the -fp-model strict flag is used by default, but can be overridden with

-Dwith-intel-compiler-flags="<intel-flags>"

Portland compiler

Use the -Kieee flag to ensure that computations obey the IEEE754 standard for floating point numerics.