You have to purchase the Amber package -- see http://amber.scripps.edu/
See also: $AMBERHOME/INSTALL
A more complete description of the Amber 12 installation is given here: http://jswails.wikidot.com/installing-amber12-and-ambertools-12
-- under construction --
0. Install Prerequisites
You need a Fortran and C compiler, X11 development files and MPI development files. Amber also requires csh (or tcsh) and the patch tool for automatic updates. The GNU compilers are good starting options but commercial or otherwise optimized compilers can considerably speed up your eventual simulations.
See: Installing Compilers (probably outdated by now)
the following commands should get you up and running on Ubuntu:sudo apt-get install gfortran gcc g++ flex patch tcsh bison libbz2-dev sudo apt-get install xorg-dev sudo apt-get install mpi-default-dev mpi-default-bin
Obsolete requirement?: Ensure you have a yacc implementation installed (try 'yacc' at the command prompt).
1. unpack the AMBER and AMBER tools package:
cd /usr/local/lib tar xvfj Amber12.tar.bz2 tar xvfj AmberTools12.tar.bz export AMBERHOME=`pwd`/amber12
execute the above and following commands within a root shell. For example, by first calling 'sudo zsh' or 'sudo bash'. Otherwise it is going to be more difficult to define $AMBERHOME such that the sudo command can "see" it.
2. Apply bugfixes:
cd $AMBERHOME ./patch_amber.py --check-updates ./patch_amber.py --update-tree ./patch_amber.py --update-tree Repeat the last command until now further patches are found (this is owing to updates to the patch tool itself, which are blocking more recent updates).
3. single and MPI compilation:
GNU Fortran Compiler, single and MPI:
cd $AMBERHOME ./configure gnu make install ./configure -mpi gnu make install
4. Compilation for CUDA GPU computing on NVidia:
download CUDA tools from NVIDIA and then:
chmod +x cudatoolkit_4.2.9_linux_64_ubuntu11.04.run ./cudatoolkit_4.2.9_linux_64_ubuntu11.04.run
create file 'nvidia_cudatools.conf' in /etc/ld.so.conf.d:
# CUDA tools libraries /usr/local/cuda/lib64 /usr/local/cuda/lib
Compile Amber for CUDA:
cd $AMBERHOME export CUDA_HOME=/usr/local/cuda ./configure -cuda gnu make install
This didn't work for me on Ubuntu 12.04. Compilation broke with:
gputypes.cpp:(.text+0x1aa5): undefined reference to `cufftDestroy'
and many more errors. The following hint fixed the problem: http://archive.ambermd.org/201205/0847.html Change the PMEMD_CU_LIBS variable in config.h -- put the "./cuda/cuda.a" entry at the beginning of that list:
PMEMD_CU_LIBS=./cuda/cuda.a -L$(CUDA_HOME)/lib64 -L$(CUDA_HOME)/lib -lcurand -lcufft -lcudart
Compile Amber for CUDA + MPI:
cd $AMBERHOME export CUDA_HOME=/usr/local/cuda ./configure -mpi -cuda gnu make install
Again this didn't work for me on Ubuntu 12.04. Compilation broke with the compiler complaing that it could not find mpi.h. The following message provided help: http://archive.ambermd.org/201206/0030.html:
sudo apt-get install libmpich2-dev mpich2
Then edit the variable PMEMD_CU_INCLUDES in config.h and add the item:
Note: the previous compilations relied on openMPI rather than MPICH. Both systems should work. The open-mpi requirements are:
sudo apt-get install openmpi-bin libopenmpi-dev
5. Test AmberSuite:
cd $AMBERHOME/test make test
6. Permanently adapt environment (bash / zsh example):
Add these statements to your shell startup script (.bashrc, .zshenv, etc.):
export AMBERHOME=/usr/local/lib/amber12 export PATH=$PATH:$AMBERHOME/bin export CUDA_HOME=/usr/local/cuda
- see Biskit.Amber...