Build system

Elemental’s build system relies on CMake in order to manage a large number of configuration options in a platform-independent manner; it can be easily configured to build on Linux and Unix environments (including Darwin), and, at least in theory, various versions of Microsoft Windows. A relatively up-to-date C++11 compiler (e.g., gcc >= 4.7) is required in all cases.

Elemental’s main external dependencies are

  1. CMake
  2. MPI
  3. BLAS
  4. LAPACK.

Included within the project are

  1. PMRRR, which Elemental depends upon for parallel symmetric tridiagonal eigensolvers, which is included within the external/pmrrr folder, and
  2. METIS 5.1.0, which is used for graph partitioning and is included within the external/metis folder.

Furthermore, there are several optional external dependencies:

1. libFLAME is recommended for faster SVD’s due to its high-performance bidiagonal QR algorithm implementation, and 2. Qt5 is required for matrix visualization.



Elemental uses several new CMake modules, so it is important to ensure that version 2.8.8 or later is installed. Thankfully the installation process is extremely straightforward: either download a platform-specific binary from the downloads page, or instead grab the most recent stable tarball and have CMake bootstrap itself. In the simplest case, the bootstrap process is as simple as running the following commands:

make install

Note that recent versions of Ubuntu (e.g., version 13.10) have sufficiently up-to-date versions of CMake, and so the following command is sufficient for installation:

sudo apt-get install cmake

If you do install from source, there are two important issues to consider

  1. By default, make install attempts a system-wide installation (e.g., into /usr/bin) and will likely require administrative privileges. A different installation folder may be specified with the --prefix option to the bootstrap script, e.g.,:

    ./bootstrap --prefix=/home/your_username
    make install

    Afterwards, it is a good idea to make sure that the environment variable PATH includes the bin subdirectory of the installation folder, e.g., /home/your_username/bin.

  2. Some highly optimizing compilers will not correctly build CMake, but the GNU compilers nearly always work. You can specify which compilers to use by setting the environment variables CC and CXX to the full paths to your preferred C and C++ compilers before running the bootstrap script.

Basic usage

Though many configuration utilities, like autoconf, are designed such that the user need only invoke ./configure && make && make install from the top-level source directory, CMake targets out-of-source builds, which is to say that the build process occurs away from the source code. The out-of-source build approach is ideal for projects that offer several different build modes, as each version of the project can be built in a separate folder.

A common approach is to create a folder named build in the top-level of the source directory and to invoke CMake from within it:

mkdir build
cd build
cmake ..

The last line calls the command line version of CMake, cmake, and tells it that it should look in the parent directory for the configuration instructions, which should be in a file named CMakeLists.txt. Users that would prefer a graphical interface from the terminal (through curses) should instead use ccmake (on Unix platforms) or CMakeSetup (on Windows platforms). In addition, a GUI version is available through cmake-gui.

Though running make clean will remove all files generated from running make, it will not remove configuration files. Thus, the best approach for completely cleaning a build is to remove the entire build folder. On *nix machines, this is most easily accomplished with:

cd ..
rm -rf build

This is a better habit than simply running rm -rf * since, if accidentally run from the wrong directory, the former will most likely fail.


An implementation of the Message Passing Interface (MPI) is required for building Elemental. The two most commonly used implementations are

  1. MPICH2
  2. OpenMPI

If your cluster uses InfiniBand as its interconnect, you may want to look into MVAPICH2.

Each of the respective websites contains installation instructions, but, on recent versions of Ubuntu (such as version 12.04), MPICH2 can be installed with

sudo apt-get install libmpich2-dev

and OpenMPI can be installed with

sudo apt-get install libopenmpi-dev


The Basic Linear Algebra Subprograms (BLAS) and Linear Algebra PACKage (LAPACK) are both used heavily within Elemental. On most installations of Ubuntu, the following command should suffice for their installation:

sudo apt-get install libatlas-dev liblapack-dev

The reference implementation of LAPACK can be found at

and the reference implementation of BLAS can be found at

However, it is better to install an optimized version of these libraries, especialy for the BLAS. The most commonly used open source versions are ATLAS and OpenBLAS. Support for BLIS is planned in the near future.


PMRRR is a parallel implementation of the MRRR algorithm introduced by Inderjit Dhillon and Beresford Parlett for computing \(k\) eigenvectors of a tridiagonal matrix of size \(n\) in \(\mathcal{O}(nk)\) time. PMRRR was written by Matthias Petschow and Paolo Bientinesi and, while it is included within Elemental, it is also available at:

Note that PMRRR currently requires support for pthreads.


libFLAME is an open source library made available as part of the FLAME project. Its stated objective is to

...transform the development of dense linear algebra libraries from an art reserved for experts to a science that can be understood by novice and expert alike.

Elemental’s current implementation of parallel SVD is dependent upon a serial kernel for the bidiagonal SVD. A high-performance implementation of this kernel was recently introduced in “Restructuring the QR Algorithm for Performance”, by Field G. van Zee, Robert A. van de Geijn, and Gregorio Quintana-Orti. It can be found at

Installation of libFLAME is fairly straightforward. It is recommended that you download the latest nightly snapshot from

and then installation should simply be a matter of running:

make install


Qt is an open source cross-platform library for creating Graphical User Interfaces (GUIs) in C++. Elemental currently supports using version 5.1.1 of the library to display and save images of matrices.

Please visit Qt Project’s download page for download and installation instructions. Note that, if Elemental is launched with the -no-gui command-line option, then Qt5 will be started without GUI support. This supports using Elemental on clusters whose compute nodes do not run display servers, but PNG’s of matrices need to be created using Qt5’s simple interface.

Getting Elemental’s source

There are two basic approaches:

  1. Download a tarball of a recent version from A new version is typically released every one to two months.

  2. Install git and check out a copy of the development repository by running

    git clone git://

Building Elemental

On *nix machines with BLAS, LAPACK, and MPI installed in standard locations, building Elemental can be as simple as:

cd elemental
mkdir build
cd build
cmake ..
make install

As with the installation of CMake, the default install location is system-wide, e.g., /usr/local. The installation directory can be changed at any time by running:

cmake -D CMAKE_INSTALL_PREFIX=/your/desired/install/path ..
make install

Though the above instructions will work on many systems, it is common to need to manually specify several build options, especially when multiple versions of libraries or several different compilers are available on your system. For instance, any C++, C, or Fortran compiler can respectively be set with the CMAKE_CXX_COMPILER, CMAKE_C_COMPILER, and CMAKE_Fortran_COMPILER variables, e.g.,

cmake -D CMAKE_CXX_COMPILER=/usr/bin/g++ \
      -D CMAKE_C_COMPILER=/usr/bin/gcc   \
      -D CMAKE_Fortran_COMPILER=/usr/bin/gfortran ..

It is also common to need to specify which libraries need to be linked in order to provide serial BLAS and LAPACK routines (and, if SVD is important, libFLAME). The MATH_LIBS variable was introduced for this purpose and an example usage for configuring with BLAS and LAPACK libraries in /usr/lib would be

cmake -D MATH_LIBS="-L/usr/lib -llapack -lblas -lm" ..

It is important to ensure that if library A depends upon library B, A should be specified to the left of B; in this case, LAPACK depends upon BLAS, so -llapack is specified to the left of -lblas.

If libFLAME is available at /path/to/libflame.a, then the above link line should be changed to

cmake -D MATH_LIBS="/path/to/libflame.a;-L/usr/lib -llapack -lblas -lm" ..

Elemental’s performance in Singular Value Decompositions (SVD’s) is greatly improved on many architectures when libFLAME is linked.

Build modes

Elemental currently has four different build modes:

  • PureDebug - An MPI-only build that maintains a call stack and provides more error checking.
  • PureRelease - An optimized MPI-only build suitable for production use.
  • HybridDebug - An MPI+OpenMP build that maintains a call stack and provides more error checking.
  • HybridRelease - An optimized MPI+OpenMP build suitable for production use.

The build mode can be specified with the CMAKE_BUILD_TYPE option, e.g., -D CMAKE_BUILD_TYPE=PureDebug. If this option is not specified, Elemental defaults to the PureRelease build mode.

Once the build mode is selected, one might also want to manually set the optimization level of the compiler, e.g., via the CMake option -D CXX_FLAGS="-O3".

Testing the installation

Once Elemental has been installed, it is a good idea to verify that it is functioning properly. An example of generating a random distributed matrix, computing its Singular Value Decomposition (SVD), and checking for numerical error is available in examples/lapack_like/SVD.cpp.

As you can see, the only required header is El.hpp, which must be in the include path when compiling this simple driver, SVD.cpp. If Elemental was installed in /usr/local, then /usr/local/conf/ElVars can be used to build a simple Makefile:

include /usr/local/conf/ElVars

SVD: SVD.cpp

As long as SVD.cpp and this Makefile are in the current directory, simply typing make should build the driver.

The executable can then typically be run with a single process (generating a \(300 \times 300\) distributed matrix, using

./SVD --height 300 --width 300

and the output should be similar to

||A||_max   = 0.999997
||A||_1     = 165.286
||A||_oo    = 164.116
||A||_F     = 173.012
||A||_2     = 19.7823

||A - U Sigma V^H||_max = 2.20202e-14
||A - U Sigma V^H||_1   = 1.187e-12
||A - U Sigma V^H||_oo  = 1.17365e-12
||A - U Sigma V^H||_F   = 1.10577e-12
||A - U Sigma V_H||_F / (max(m,n) eps ||A||_2) = 1.67825

The driver can be run with several processes using the MPI launcher provided by your MPI implementation; a typical way to run the SVD driver on eight processes would be:

mpirun -np 8 ./SVD --height 300 --width 300

You can also build a wide variety of example and test drivers (unfortunately the line is a little blurred) by using the CMake options:




Elemental as a subproject

Adding Elemental as a dependency into a project which uses CMake for its build system is relatively straightforward: simply put an entire copy of the Elemental source tree in a subdirectory of your main project folder, say external/elemental, and then create a CMakeLists.txt file in your main project folder that builds off of the following snippet:

cmake_minimum_required(VERSION 2.8.8)


# Build your project here
# e.g.,
#   add_library(foo ${LIBRARY_TYPE} ${FOO_SRC})
#   target_link_libraries(foo El)


If you run into build problems, please email and make sure to attach the file include/El/config.h, which should be generated within your build directory. Please only direct usage questions to, and development questions to