Block Installation¶
Source code and binary¶
- Version 1.5
- Source code block-1.5.3.tar.gz,
- Binary 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 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, 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 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, 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 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 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, npdm
, 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
.
Interface to PySCF package¶
The electronic structure Python module 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. 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.