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The Augmented Block Cimmino Distributed Solver

Note: Check http://abcd.enseeiht.fr for more details.

Tested plateforms

Working

  • Linux x86_64 with GNU 4.7 and 4.8 compilers,``MKL``, ACML, reference blas and lapack.

Not Working

  • Fujitsu FX with Fujitsu compilers:
    • PaToH is not compatible (users have to request a compatible version from the authors)
    • Our Logging library is not compatible with Fujitsu compilers, should work with GNU compilers.
  • Microsoft Windows:
    • MUMPS does not support Windows (there is an unofficial guide to compile it under Windows, but we do not provide any pre-compiled library for it)
    • PaToH is not compatible (users have to request a compatible version from the authors)

You can disable PaToH by running cmake with the option -DPATOH=OFF.

Not Tested

  • Mac OSX was not tested but should be fully compatible.

Obtaining the source code

The ABCD Solver depends on a few external libraries: MUMPS, Sparselib++ (custom), PaToH, lapack and Boost::MPI version 1.50 or higher.

  • A patched version of MUMPS is distributed with our solver in the lib/mumps/ directory. Only the headers and a compiled version (Linux x86_64, other version will be available uppon request) is distributed. When MUMPS 5.0 is released, it should be used instead.
  • Sparselib++ (custom): a modified version of SparseLib++ to suits our needs, is also distributed with our solver in the lib/sparselib directory. The library is compiled same as MUMPS, but you still can recompile it by running make all in lib/sparselib directory.
  • PaToH: Can be downloaded from the webpage of Ümit V. Çatalyürek (URL available in the following script). The file libpatoh.a has to be copied into the lib/ directory and the header patho.h has to be copied into the include directory.
  • BLAS and LAPACK are both mandatory. We provide configurations to build the solver using ACML and MKL.
  • BLACS and ScaLAPACK are required by MUMPS, therefore they are needed when you link your software with the solver. We explicitly require them so that we can build the examples.
  • Boost::MPI requires MPI and so does MUMPS. You can install it either from source or through your distribution repositories. The solver was tested with versions 1.47, 1.49 and 1.54. However, we recommend to use versions higher than 1.50.

The installation can be done by typing the following commands in your terminal

# download the latest stable version
# it will create a directory named abcd

git clone https://bitbucket.org/apo_irit/abcd.git

# download the appropriate version of patoh from
# http://bmi.osu.edu/~umit/software.html
# copy libpatoh.a to the lib/ directory
# copy patoh.h to the include/ directory

Now that everything is ready, we can compile the solver. To do so, we need a configuration file from the cmake.in directory, suppose we are going to use the ACML library that provides BLAS and LAPACK.

# get the appropriate configuration file

cp cmake.in/abcdCmake.in.ACML ./abcdCmake.in

To use MKL instead, copy the file abcdCmake.in.MKL:

# get the appropriate configuration file

cp cmake.in/abcdCmake.in.MKL ./abcdCmake.in

You can use the Intel® Math Kernel Library Link Line Advisor to customize the configuration.

Edit the file abcdCmake.in so that it reflects your configuration (path to libraries, file names, path to MPI, etc).

Building the library

The build process is done using cmake:

# create a building directory

mkdir build

# run cmake

cd build
cmake ..

# if everything went correctly you can run make

make

# the files will be in directory lib/

ls lib # gives libabcd.a

If cmake does not finish correctly, here are some possible reasons:

  • mpic++ is either not installed or there is an issue with mpi libraries, check also that you gave the right path in your abcdCmake.in file.
  • Boost is either not installed, or the version is too old. Check that Boost::MPI is installed.
  • The path to some libraries is not well defined in abcdCmake.in.

Running ABCD

You can run the solver without having to write a code (as we do in the next section). After building the library, a binary is created called abcd_run, it uses a configuration file that you will find in the directory test/src/config_file.info that you need to copy to your build directory.

cd build
cp ../config_file.info .

# to try ABCD on a provided small test matrix, without having to write any code,
# abcd_run looks by default for the file config_file.info in the current directory

mpirun -np 16 ./abcd_run

You can also give the executable the path to your configuration file:

mpirun -np 16 ./abcd_run /path/to/configuration_file

The configuration file incorporates comments with details about all possible options and how to use them.

Building an example (to call ABCD from C++ or C)

Once the library is built, you can compile the given examples (either C++ or C):

# the C++ example called `example.cpp` and the
# C example called `example.c` are in the examples directory

cd examples

# create a directory where to build your examples

mkdir build_example
cd build_example

# tell cmake where the abcd solver is located
# the current version supposes that the library was built within
# the directory ``build`` in a release mode
# if you get an error while running cmake, check that you gave the
# absolute path to the abcd solver directory

cmake .. -DABCD=/absolute/path/to/abcd/
make

# if everything went correctly, try to run the C++ example

mpirun -np 16 ./example

# or if you want to run the C example:

mpirun -np 16 ./example_c

Issue tracker

If you find any bug, didn't understand a step in the documentation, or if you have a feature request, submit your issue on our Issue Tracker by giving:

  • reproducible steps
  • a source code, or a snippet where you call the solver
  • a matrix file if possible.