.. _build:
Block Installation
******************
Source code and binary
======================
* Version 1.5
- Source code `Block v1.5.3 <https://github.com/pyscf/Block>`_,
- Binary `block.spin_adapted-1.5.3.gz <https://github.com/pyscf/Block/raw/master/bin/block.spin_adapted-1.5.3.gz>`_,
1.9 MB, compiled with GCC-4.8, Boost-1.55, OpenMPI-1.10.3, MKL-11
- Binary `block.spin_adapted-1.5.3-serial.gz <https://github.com/pyscf/Block/raw/master/bin/block.spin_adapted-1.5.3-serial.gz>`_
1.8 MB, compiled with GCC-4.8, Boost-1.55, MKL-11
* Version 1.1.1
- Binary `block.spin_adapted-1.1.1.gz <https://github.com/pyscf/Block/raw/master/bin/block.spin_adapted-1.1.1.gz>`_,
2.4 MB, compiled with GCC-4.8, Boost-1.55, OpenMPI-1.10.3, MKL-11
- Binary `block.spin_adapted-1.1.1-serial.gz <https://github.com/pyscf/Block/raw/master/bin/block.spin_adapted-1.1.1-serial.gz>`_
2.2 MB, compiled with GCC-4.8, Boost-1.55, MKL-11
* Version 1.1.0
- Binary `block.spin_adapted-1.1.0.gz <https://github.com/pyscf/Block/raw/master/bin/block.spin_adapted-1.1.0.gz>`_,
4.3 MB, compiled with GCC-4.8, Boost-1.55, OpenMPI-1.6.5, MKL-11
- Binary `block.spin_adapted-1.1.0-serial.gz <https://github.com/pyscf/Block/raw/master/bin/block.spin_adapted-1.1.0-serial.gz>`_
2.2 MB, compiled with GCC-4.8, Boost-1.55, MKL-11
Compile
=======
Building Block code requires C++11 compiler, BLAS, LAPACK and Boost libraries.
For distributed-memory parallel compilation, MPI and multi-threading
Boost-MPI libraries are needed. When you compile Boost-MPI, you can use
the following flags for ``b2`` the Boost built-in compilation tool to
generate the multi-threading ``-mt`` libraries.::
./b2 --layout=tagged link=static,shared threading=multi install
Note Boost and MPI libraries must be compiled using the same compiler as for compiling Block.
See also `boost documents <http://www.boost.org/doc/libs/1_60_0/doc/html/mpi/getting_started.html>`_
for details of the installation of Boost with the MPI components.
To compile Block code, the following customizations need to be made to
the makefile placed in the main directory.::
CXX = g++
BOOSTINCLUDE = /lib64/boost_1_55_0/include/
BOOSTLIB = /lib64/boost_1_55_0/lib/
OPENMP = yes
Please note that when choosing your compiler, either GNU or Intel, C++0x/C++11 standards must be appropriately supported,
as Block requires new features for some of the modules (eg, :mod:`npdm`, :mod:`nevpt2`, etc).
Here are our suggested `minimum` GNU/Intel compiler versions in order for the compiling process to be successful:
* GNU ``g++``: 4.8 or newer,
* or Intel ``icpc``: at least 14.0.1 (2013 SP1 Update 1) or newer.
Turn on the MPI support for Block code::
USE_MPI = yes
MPICXX = mpicxx
And supply MKL libraries::
USE_MKL = yes
MKLLIB = /opt/intel/composer_xe_2013_sp1.0.080/mkl/lib/intel64/``
MKLFLAGS = /opt/intel/composer_xe_2013_sp1.0.080/mkl/include``
For certain compilers, you may have error message::
error: ‘auto_ptr’ is deprecated (declared at /usr/include/c++/4.8.2/backward/auto_ptr.h:87) [-Werror=deprecated-declarations]
It is caused by the flag ``-Werror``. It is safe to remove this flag
from ``OPT`` variable. Some compiler/linker may issue errors if
``OPENMP = yes`` was specified in Makefile::
/usr/bin/ld: dmrg.o: undefined reference to symbol 'shm_openn@@GLIBC_2.2.5'
Appending ``-lpthread -lrt`` at the end of ``LIBS`` can solve this problem.
When the makefile is configured, run in the directory ``./Block``::
$ make
The successful compilation generates the executable ``block.spin_adapted``, static and shared DMRG libraries ``libqcdmrg.a`` and ``libqcdmrg.so``.
.. _pyscf-itrf:
Interface to PySCF package
--------------------------
The electronic structure Python module `PySCF <http://chemists.princeton.edu/chan/software/pyscf/>`_
provided an interface to run Block code. You need create a pyscf
config file ``/path/to/pyscf/future/dmrgscf/settings.py`` and add the
following settings in it::
BLOCKEXE = "/path/to/Block/block.spin_adapted"
BLOCKEXE_COMPRESS_NEVPT = "/path/to/serially/compiled/Block/block.spin_adapted"
BLOCKSCRATCHDIR = "/path/to/scratch"
MPIPREFIX = "mpirun"
``BLOCKEXE`` is the parallel Block program. Most DMRG calculations (DMRG-CASCI,
DMRG-CASSCF etc) will call this parallel executable through ``mpirun``
interface. ``BLOCKEXE_COMPRESS_NEVPT`` points to the **serially
compiled** Block executable. It is only needed by the compressed perturber
NEVPT2 method. Note the serial version of Block is slightly different to the
parallel Block with compiling flag ``USE_MPI=yes``. Specifically, NEVPT2
implementation in the serial code is not available in the parallelized code.
Although this Block executable file is not MPI-parallelized, the
DMRG-NEVPT2 program are efficiently parallelized in a different manner.
Note the parameter ``MPIPREFIX`` should be adjusted according to your
job scheduler, eg::
# For OpenPBS/Torque
MPIPREFIX = "mpirun"
# For SLURM
MPIPREFIX = "srun"
If calculation is carried out on interactive node, eg with 4 processors,
the setting looks like::
MPIPREFIX = "mpirun -n 4"
With the Block-PySCF interface, a simple DMRG-SCF calculation can be
input in Python interpereter::
>>> from pyscf import gto, scf, dmrgscf
>>> mf = gto.M(atom='C 0 0 0; C 0 0 1', basis='ccpvdz').apply(scf.RHF).run()
>>> mc = dmrgscf.dmrgci.DMRGSCF(mf, 6, 6)
>>> mc.run()
DMRG-NEVPT2 calculation can be applied::
>>> from pyscf import mrpt
>>> mrpt.NEVPT(mc).compress_approx().run()
Run Block in cmdline
====================
The standalone serial code can be executed running::
$ block.spin_adapted input.dat > output.dat
``input.dat`` is the input file and the output of the program is piped into the output file ``output.dat``.
The MPI parallel mode can be called running::
$ mpirun -np 4 block.spin_adapted input.dat > output.dat
Testjobs
=========
Tests are placed in the directory ``./Block/dmrg_tests``::
$ cd dmrg_tests
$ ./runtest
The tests require Python to be installed on the system.