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– --with-ext-linalg-path: Give the path of the other linear algebra
libraries (default = -L/usr/lib). Use the -L before the path(es).
• Accelarators:
– enable-cuda-gpu: Compile CUDA support for GPU computing.
– --with-cuda-path: Give the path to the NVIDIA CUDA tools (default is /usr/local/cuda).
– --with-nvcc-flags: Specify the flags for the NVIDIA CUDA Compiler.
– --enable-opencl: Compile OpenCL support for GPU computing (compatible with --enable-cuda-gpu).
– --with-ocl-path: Give the path to the OpenCL installation directory
(default is /usr).
• Optional libraries:
– --with-etsf-io: Use ETSF file format (binary based on NetCDF)
for densities, potentials and wavefunction files.
– --with-archives: Use compression (tar.bz2) for position files during
geometry optimisation.
• --prefix=DIR: Specify your installation directory (/usr/local is default).
An example of compilation using the MKL from Intel instead of basic BLAS
and LAPACK installation:
../configure --with-ext-linalg="-lmkl ia32 -lmkl lapack"
--with-ext-linalg-path="-L/opt/intel/mkl72/lib/32"
--prefix=/home/caliste/usr FC=ifort
An other example, compiling CUDA parts:
../../sources/bigdft-1.3.0-dev/configure
FC=mpif90 FCFLAGS="-O2 -assume 2underscores"
CC=icc CXX=icc CXXFLAGS="-O2 -I/applications/cuda-2.2/include/"
CFLAGS="-O2 -I/applications/cuda-2.2/include/"
--with-ext-linalg="-L/applications/intel/mkl/lib/em64t
-lmkl scalapack lp64 -lmkl blacs intelmpi20 lp64
-lmkl intel lp64 -lmkl lapack -lmkl sequential -lmkl core"
--enable-cuda-gpu --with-cuda-path=/applications/cuda-2.2
The other options available can be browsed via the --help option. Some of
them are listed here (and they can be of course combined with each other, when it
does make sense):
• --disable-mpi: Force not to use MPI during build. By default the configure will try to detect if the compiler has some native MPI capabilities. If not
MPI will be automatically disabled.
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