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make pgm | make pgm | ||
mpirun -n 4 ./pgm | mpirun -n 4 ./pgm | ||
| + | |||
| + | |||
| + | == Python installation instructions == | ||
| + | |||
| + | Even though Python modules are provided by SHARCNET, sometimes there may be a need to compile your own Python and Numpy. Here are instructions on how to do it (tested in September, 2014): | ||
| + | |||
| + | To get the source tarballs, do: | ||
| + | |||
| + | wget --no-check-certificate https://www.python.org/ftp/python/2.7.8/Python-2.7.8.tgz | ||
| + | wget http://sourceforge.net/projects/numpy/files/NumPy/1.8.2/numpy-1.8.2.tar.gz | ||
| + | |||
| + | and unpack these somewhere in your directories. | ||
| + | |||
| + | These were built under modules: | ||
| + | |||
| + | module unload intel | ||
| + | module unload mkl | ||
| + | module unload openmpi | ||
| + | module load gcc/4.8.2 | ||
| + | module load openmpi/gcc/1.8.1 | ||
| + | |||
| + | (openmpi is not necessary for this built, but I would suggest loading the gcc/1.8.1 anyway) | ||
| + | |||
| + | Python was built with: | ||
| + | |||
| + | ./configure --enable-shared --prefix=~/software_installs/python/2.7.8/gcc/installdir | ||
| + | make | ||
| + | make install | ||
| + | |||
| + | Numpy was built with: | ||
| + | |||
| + | unset LDFLAGS | ||
| + | python setup.py build --fcompiler=gnu95 | ||
| + | python setup.py install --prefix=~/software_installs/numpy/1.8.2/gcc/installdir | ||
| + | |||
| + | Also did: | ||
| + | |||
| + | ln -sf ~/software_installs/numpy/1.8.2/gcc/installdir/lib/python2.7/site-packages/numpy/core/include/numpy ~/software_installs/python/2.7.8/gcc/installdir/include/python2.7 | ||
| + | |||
| + | and finally | ||
| + | |||
| + | export PYTHONPATH=~/software_installs/numpy/1.8.2/gcc/installdir/lib/python2.7/site-packages/ | ||
Revision as of 09:28, 5 September 2014
Pawel Pomorski
High Performance Computing Programming Specialist
University of Waterloo
Contents
Software which I help maintain
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NAMD instructions
These instructions for monk, current as of Feb.2014, with default modules:
intel/12.1.3 cuda/5.5.22
Preliminaries:
module unload openmpi module load openmpi/intel/1.7.4 export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/sharcnet/intel/12.1.3/icc/composer_xe_2011_sp1.9.293/compiler/lib/intel64
OpenMPI 1.7.4 is compiled with CUDA support. Environment variable is needed to locate all the libraries at runtime.
Get all the required source files:
tar xvfz NAMD_2.9_Source.tar.gz cd NAMD_2.9_Source
Download and install precompiled TCL and FFTW libraries: (working in NAMD source directory)
wget http://www.ks.uiuc.edu/Research/namd/libraries/fftw-linux-x86_64.tar.gz tar xzf fftw-linux-x86_64.tar.gz mv linux-x86_64 fftw wget http://www.ks.uiuc.edu/Research/namd/libraries/tcl8.5.9-linux-x86_64.tar.gz wget http://www.ks.uiuc.edu/Research/namd/libraries/tcl8.5.9-linux-x86_64-threaded.tar.gz tar xzf tcl8.5.9-linux-x86_64.tar.gz tar xzf tcl8.5.9-linux-x86_64-threaded.tar.gz mv tcl8.5.9-linux-x86_64 tcl mv tcl8.5.9-linux-x86_64-threaded tcl-threaded
Compile charm, choosing which parallelization is to be used (threaded, MPI, MPI-SMP):
tar xvf charm-6.4.0.tar cd charm-6.4.0
Compile charm - MPI build:
env MPICXX=mpicxx ./build charm++ mpi-linux-x86_64 --no-build-shared --with-production
Compile charm - MPI-SMP build:
env MPICXX=mpicxx ./build charm++ mpi-linux-x86_64 smp --no-build-shared --with-production
Compile charm - threaded build:
./build charm++ multicore-linux64 --no-build-shared icc8 --with-production
Configure NAMD and compile (with CUDA support enabled) - replace CHARM_ARCHITECTURE with one of the three options above:
./config Linux-x86_64-icc --charm-arch CHARM_ARCHITECTURE --with-cuda --cuda-prefix /opt/sharcnet/cuda/5.5.22/toolkit/ cd Linux-x86_64-icc make
Test charm if needed:
From the directory charm is in,
cd architecture_directory/tests/charm++/megatest make pgm mpirun -n 4 ./pgm
Python installation instructions
Even though Python modules are provided by SHARCNET, sometimes there may be a need to compile your own Python and Numpy. Here are instructions on how to do it (tested in September, 2014):
To get the source tarballs, do:
wget --no-check-certificate https://www.python.org/ftp/python/2.7.8/Python-2.7.8.tgz wget http://sourceforge.net/projects/numpy/files/NumPy/1.8.2/numpy-1.8.2.tar.gz
and unpack these somewhere in your directories.
These were built under modules:
module unload intel module unload mkl module unload openmpi module load gcc/4.8.2 module load openmpi/gcc/1.8.1
(openmpi is not necessary for this built, but I would suggest loading the gcc/1.8.1 anyway)
Python was built with:
./configure --enable-shared --prefix=~/software_installs/python/2.7.8/gcc/installdir make make install
Numpy was built with:
unset LDFLAGS python setup.py build --fcompiler=gnu95 python setup.py install --prefix=~/software_installs/numpy/1.8.2/gcc/installdir
Also did:
ln -sf ~/software_installs/numpy/1.8.2/gcc/installdir/lib/python2.7/site-packages/numpy/core/include/numpy ~/software_installs/python/2.7.8/gcc/installdir/include/python2.7
and finally
export PYTHONPATH=~/software_installs/numpy/1.8.2/gcc/installdir/lib/python2.7/site-packages/