Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms.. The current version is 3.1.3
To use the Eigen libraries, just untar and enter the source the directory
# tar -xvf eigen-3.1.3.tar
Copy the whole Eigen directory found in “eigen-eigen-2249f9c22fe8” folder to the /usr/local/include directory
# cd eigen-eigen-2249f9c22fe8/ # cp -Rv Eigen /usr/local/include
Taken from Cufflinks – Getting Started
SAM (Sequence Alignment/Map) format is a generic format for storing large nucleotide sequence alignments. SAM Tools provide various utilities for manipulating alignments in the SAM format, including sorting, merging, indexing and generating alignments in a per-position format.
SAMTools (0.1.19)
Step 1: – Download SAMTools
Step 2: – Unpack and compile the SAMTools
# tar -zxvf samtools-0.1.19 # make
Step 3: – Copy the compiled libraries to /usr/local/lib
# cp $SAMTOOLS_HOME/libbam.a /usr/local/lib
Step 4: Copy headers to /usr/local/include
# mkdir /usr/local/include/bam # cp $SAMTOOLS_HOME/*.h /usr/local/include/bam
Referenced from Cufflinks – Get started
Step 1 – Download Boost from Boost Website
Step 2 – Unpack the boost
# tar -zxvf boost_1_53_0.tar.gz
Step 3 – Run Bootstrap.sh
# ./bootstrap.sh Building Boost.Build engine with toolset gcc... .....
Step 4 – Run the binary b2
# ./b2 install --prefix=/usr/local/boost
It will take a while……
Step 5: Test that the compilation is working.
Compile the test case.
# cd $BOOST_ROOT/boost_1_53_0/tools/build/v2/example/hello
# $BOOST_ROOT/b2
You should see a binary file “hello” at
# $BOOST_ROOT/boost_1_53_0/tools/build/v2/example/hello/bin/gcc-4.4.6/debug
GAP is a system for computational discrete algebra, with particular emphasis on Computational Group Theory. GAP provides a programming language, a library of thousands of functions implementing algebraic algorithms written in the GAP language as well as large data libraries of algebraic The objects.
The information is taken from Compilation
Step 1: Download the GAP Software
Download the GAP Software at http://www.gap-system.org/Releases/index.html Current version at point of writing is 4.5.6
# tar -zxvf gap4r5p6_2012_11_04-18_46.tar.gz
# cd gap4r5p6
Step 2: Configure and Install (Default Installation)
#./configure
# make
Step 3: Optional Installation – GMP packages.
If you wish to use the GAP internal GMP Packges, then the version of GMP bundled with this GAP will be used. This is the default.
# ./configure --with-gmp=yes|no|system|"path"
Step 4: Optional Installation – Readline Editing for better command-line Editing.
If the argument you supply is yes, then GAP will look in standard locations for a Readline installed on your system. Or you can specify a path to a Readline installation.
# ./configure --with-readline=yes|no|"path"
For more information,
See INSTALL when you unpacked the GAP.
If you wish to compile AMBER 10 with the latest version of Intel XE and Intel and MKL 10, you will need to do a bit of tweaking of the
Standard installation of AMBER10
A. Setup of AmberTools environment.
1. Include AMBERHOME in your .bashrc
# vim .bashrc
export AMBERHOME=/usr/local/amber10
2. Configure the system for AmberTools. Assuming you are configuring for mpi, intel compiler, you will probably use the command
# cd $AMBERHOME/src # ./configure_at mpi icc
3. Make the file Makefile_at
# make -f Makefile_at
You will have something like for the output.
Completed installation of AmberTools, version 1.1
B. Setting up the basic AMBER distribution for OpenMPI, Intel
Here is where if you are using the more up-to-date MKL (version 10), things will fail to compile. It took me a while to solve the problem. But basically you have to replace the old dynamic linking flags with the new ones. According to the versions 10.x of Intel® MKL, Intel has re-architected Intel MKL and physically separated the interface, threading and computational components of the product.
1. Retrieve the latest bug fixes for AMBER 10 from (http://ambermd.org/bugfixes.html)
# cd $AMBERHOME # chmod 700 apply_bugfix_all.x # ./apply_bugfix_all.x bugfix.all
2. Edit the configure_amber file to match Intel MKL 10.x linking libraries. Fore information, do look at Linking Applications with Intel MKL version 10
# vim $AMBERHOME/src/configure_amber
Go to line 464, replace the EM64T dynamic linking parameters
# EM64T dynamic linking of double-precision-LAPACK and kernels # loadlib="$loadlib -L$mkll -lvml -lmkl_lapack -lmkl -lguide -lpthread" loadlib="$loadlib -L$mkll -lguide -lpthread -lguide -lpthread -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core"
Go to line 617, replace the EM64T dynamic linking parameters, do the same
#loadlib="$loadlib -L$mkll -lvml -lmkl_lapack -lmkl -lguide -lpthread" loadlib="$loadlib -L$mkll -lguide -lpthread -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core"
3. Ensure the environmental varaiables are correct. You should have at least have the following. I’m also assuming you have compiled OpenMPI and has but it in the PATH
export AMBERHOME=/usr/local/amber10 export MPI_HOME=/usr/local/mpi/intel export MKL_HOME=/opt/intel/mkl/10.2.6.038
4. Compile the AMBER for parallel
# ./configure_amber -openmpi ifort
------ Configuring the netCDF libraries: -------- Configuring netcdf; (may be time-consuming) NETCDF configure succeeded. MPI_HOME is set to /usr/local/mpi/intel The configuration file, config_amber.h, was successfully created.
SCALAPACK requires BLAS and LAPACK, please read the tutorial
To compile the SCALAPACK,
# mkdir -p ~/src # wget http://www.netlib.org/scalapack/scalapack-2.0.1.tgz # tar -zxvf scalapack-2.0.1.tgz # cd scalapack-2.0.1 # cp SLmake.inc.example SLmake.inc
Edit the scalapack SLmake.inc file. At line 58 and line 59
BLASLIB = -lblas -L/usr/local/blas LAPACKLIB = -llapack -L/usr/local/lapack/lib
At the Linux Console again
# make # mv scalapack-2.0.1 /usr/local/
Update ane export your LD_LIBRARY_PATH
The reference resource can be found from Building LAPACK library from Netlib. The current latest version of LAPACK is dated 11th November 2011. The current latest version is lapack-3.4.0.tgz.
LAPACK relied on BLAS. See Building BLAS Library using Intel and GNU Compiler
# mkdir -p ~/src # wget http://www.netlib.org/lapack/lapack-3.4.0.tgz # tar -zxvf lapack-3.4.0.tgz # cd lapack-3.4.0.tgz # cp INSTALL/make.inc.ifort make.inc # make lapacklib # make clean # mkdir -p /usr/local/lapack # mv liblapack.a /usr/local/lapack/ # export LAPACK=/usr/local/lapack/liblapack.a
For gfortran 64-bits compiler
# cp INSTALL/make.inc.gfortran make.inc
Edit the make.inc
PLAT = _LINUX OPTS = -O2 -m64 -fPIC NOOPT = -m64 -fPIC
# make lapacklib # make clean # mkdir -p /usr/local/lapack # mv liblapack.a /usr/local/lapack/ # export LAPACK=/usr/local/lapack/liblapack.a
For more information on LAPACK, see LAPACK — Linear Algebra PACKage
The reference resource can be found from Building BLAS library from Netlib. The current latest version of BLAS is dated 14th April 2011.
1. For Intel XE Compiler
# mkdir -p ~/src/ # cd ~/src/ # wget http://www.netlib.org/blas/blas.tgz # tar -zxvf blas.tgz # cd BLAS # ifort -FI -w90 -w95 -cm -O3 -unroll -c *.f # ar r libfblas.a *.o # ranlib libfblas.a # rm -rf *.o # export BLAS=~/src/BLAS/libfblas.a # ln -s libfblas.a libblas.a # mv ~/src/BLAS /usr/local/
2. For 64-bits gfortran Compiler. Replace ” ifort -FI -w90 -w95 -cm -O3 -unroll -c *.f ” with
......... # gfortran -O3 -std=legacy -m64 -fno-second-underscore -fPIC -c *.f .........
The rest remains the same.
3. For 64-bits g77 Compiler. Replace ” ifort -FI -w90 -w95 -cm -O3 -unroll -c *.f ” with
............ # g77 -O3 -m64 -fno-second-underscore -fPIC -c *.f ............
The rest remains the same.
This tutorial is an extension of Installing ALPS 2.0 from source on CentOS 5 The installation can apply on CentOS 6 as well. For this tutorial, we will be installing.
I’m trying to refrain for installing as much by source compiling and rely on repository for this tutorial. As such the packages will be behind
Step 1: Install blas and lapack packages from CentOS Base Repositories
# yum install lapack* blas*
================================================================================ Package Arch Version Repository Size ================================================================================ Installing: blas x86_64 3.2.1-4.el6 base 321 k blas-devel x86_64 3.2.1-4.el6 base 133 k lapack x86_64 3.2.1-4.el6 base 4.3 M lapack-devel x86_64 3.2.1-4.el6 base 4.5 M Transaction Summary ================================================================================ Install 4 Package(s) Total download size: 9.2 M Installed size: 26 M Is this ok [y/N]: y
Step 2: Install numpy numpy-f2py python-matplotlib
# yum install numpy numpy-f2py python-matplotlib
================================================================================ Package Arch Version Repository Size ================================================================================ Installing: numpy x86_64 1.3.0-6.2.el6 base 1.6 M numpy-f2py x86_64 1.3.0-6.2.el6 base 430 k python-matplotlib x86_64 0.99.1.2-1.el6 base 3.2 M Transaction Summary ================================================================================ Install 3 Package(s) Total download size: 5.3 M Installed size: 22 M Is this ok [y/N]: y
Step 3: Install h5py
# yum install h5py
================================================================================ Package Arch Version Repository Size ================================================================================ Installing: h5py x86_64 1.3.1-6.el6 epel 650 k Installing for dependencies: hdf5-mpich2 x86_64 1.8.5.patch1-7.el6 epel 1.4 M liblzf x86_64 3.6-2.el6 epel 20 k mpich2 x86_64 1.2.1-2.3.el6 base 3.7 M Transaction Summary ================================================================================ Install 4 Package(s) Total download size: 5.7 M Installed size: 17 M Is this ok [y/N]: y
Step 4: Install scipy
# yum install scipy
================================================================================ Package Arch Version Repository Size ================================================================================ Installing: scipy x86_64 0.7.2-5.el6 epel 5.8 M Installing for dependencies: suitesparse x86_64 3.4.0-2.el6 epel 782 k Transaction Summary ================================================================================ Install 2 Package(s) Total download size: 6.5 M Installed size: 29 M Is this ok [y/N]: y
Here is a write-up of my computing platform and applications:
First thing first, just make sure your cluster has the necessary components. Here are some of the preliminary you may want to take a look
Assuming you are done, you may want to download the NWChem 6.1 from NWChem Website. You may also want to take a look at instruction set for Compiling NWChem
# tar -zxvf Nwchem-6.1-2012-Feb-10.tar.gz # cd nwchem-6.1
Create a script so that all these “export” parameter can be typed once only and kept. The script I called it nwchem_script_Feb2012.sh. Make sure that the ssh key are exchanged between the nodes. To have idea an of SSH key exchange, see blog entry Auto SSH Login without Password
Here is my nwchem_script_Feb2012.sh. For more details information, see Compiling NWChem for details on some of the parameters
export TCGRSH=/usr/bin/ssh export NWCHEM_TOP=/root/nwchem-6.1 export NWCHEM_TARGET=LINUX64 export ARMCI_NETWORK=OPENIB export IB_INCLUDE=/usr/include export IB_LIB=/usr/lib64 export IB_LIB_NAME="-libumad -libverbs -lpthread" export MSG_COMMS=MPI export USE_MPI=y export USE_MPIF=y export USE_MPIF4=y export MPI_LOC=/usr/local/mpi/intel export MPI_LIB=$MPI_LOC/lib export MPI_INCLUDE=$MPI_LOC/include export LIBMPI="-L/usr/local/mpi/intel/lib -lmpi_f90 -lmpi_f77 -lmpi -lpthread" export NWCHEM_MODULES=all export LARGE_FILES=TRUE export FC=ifort export CC=icc cd $NWCHEM_TOP/src make clean make 64_to_32 make USE_64TO32=y HAS_BLAS=yes BLASOPT="-L/opt/intel/mkl/10.2.4.032/lib/em64t -lmkl_intel_ilp64 -lmkl_sequential -lmkl_core -lpthread" make FC=ifort CC=icc nwchem_config >& make.log
Do note that if you are compiling with proprietary BLAS libraries like MKL, note the instruction from Compiling NWChem
WARNING: In the case of 64-bit platforms, most vendors optimized BLAS libraries cannot be used. This is due to the fact that while NWChem uses 64-bit integers (i.e. integer*8) on 64-bit platforms, most of the vendors optimized BLAS libraries used 32-bit integers. BLAS libraries not supporting 64-bit integers (at least in their default options/installations) include CXML (DECOSF), ESSL (LAPI64), MKL (LINUX64/ia64 and x86_64), ACML(LINUX64/x86_64), and GotoBLAS2(LINUX64). The same holds for the ScaLAPACK libraries, which internally use 32-bit integers.
cd $NWCHEM_TOP/src make clean make 64_to_32 make USE_64TO32=y HAS_BLAS=yes BLASOPT="-L/opt/intel/mkl/10.2.4.032/lib/em64t -lmkl_intel_ilp64 -lmkl_sequential -lmkl_core -lpthread"
General Site Installation
Determine the local storage path for the install files. (e.g., /usr/local/NWChem).
Make directories
# mkdir /usr/local/nwchem-6.1 # mkdir /usr/local/nwchem-6.1/bin # mkdir /usr/local/nwchem-6.1/data
Copy binary
# cp $NWCHEM_TOP/bin/${NWCHEM_TARGET}/nwchem /usr/local/nwchem-6.1/bin
# cd /usr/local/nwchem-6.1/bin
# chmod 755 nwchem
Copy libraries
# cd $NWCHEM_TOP/src/basis # cp -r libraries /usr/local/nwchem-6.1/data # cd $NWCHEM_TOP/src/ # cp -r data /usr/local/nwchem-6.1 # cd $NWCHEM_TOP/src/nwpw # cp -r libraryps /usr/local/nwchem-6.1/data
The Final Lap (From Compiling NWChem)
Each user will need a .nwchemrc file to point to these default data files. A global one could be put in /usr/local/nwchem-6.1/data and a symbolic link made in each users $HOME directory is probably the best plan for new installs. Users would have to issue the following command prior to using NWChem: ln -s /usr/local/nwchem-6.1/data/default.nwchemrc $HOME/.nwchemrc
Contents of the default.nwchemrc file based on the above information should be:
nwchem_basis_library /usr/local/nwchem-6.1/data/libraries/ nwchem_nwpw_library /usr/local/nwchem-6.1/data/libraryps/ ffield amber amber_1 /usr/local/nwchem-6.1/data/amber_s/ amber_2 /usr/local/nwchem-6.1/data/amber_q/ amber_3 /usr/local/nwchem-6.1/data/amber_x/ amber_4 /usr/local/nwchem-6.1/data/amber_u/ spce /usr/local/nwchem-6.1/data/solvents/spce.rst charmm_s /usr/local/nwchem-6.1/data/charmm_s/ charmm_x /usr/local/nwchem-6.1/data/charmm_x/
The Linux Cluster 