Nanosystem Simulation Library

Nanosystem Simulation Library (NSL) implements statistical simulations for systems on the nanoscale.

This library provides a merge of the two software packages CNS and isle. Additional features become added to provide a self-containing simulation library for nanostructures such as

• Graphene
• Carbon Nanotubes

Installation

The default branch is the devel branch. Only tested and working features are merged into this. It is ment as a starting point for the development of new features. The main branch holds the newest major version of NSL. While each major version contains its separate branch as release/MajorVersionID.0. Subreleases, if they appear may contain bug fixes and can be found at release/MajorVersionID.n where n counts upwards from 1.

Quick Build

The quick build instruction assume that all prerequisites, detailed below, are already met.

1. Obtain a copy of the library

git clone [email protected]:Marcel-Rodekamp/NSL.git && cd NSL

2. Create a build directory and change into it

mkdir build && cd build

3. Call cmake (cmake version ≥ 3.18) to generate the build files
   • Possible build types:
     • Debug: Build for developing and debugging, turn on runtime assertions
     • Release: Build for production, turn off runtime assertions

cmake -DCMAKE_BUILD_TYPE=Debug ..

4. Build the directory (add -j 4 for parallel build on 4 cores)

make

Prerequisites

Sometimes a few things are needed before the build can work. We utilize features from C++20 which requires more recent compilers. Currently, NSL is tested to work with

1. g++ (GCC) 10.3.0
2. g++ (GCC) 11.1.0
3. clang++ 13.0.0 with targets:
   • x86_64-apple-darwin20.6.0
   • arm64-apple-darwin20.6.0

Additionally, the backend depends on PyTorch's C++ ABI libtorch which is automatically shipped with any PyTorch installation. Please ensure that PyTorch is installed on your system.

If PyTorch has been installed via pip3 and it is not installed in the system defaults (that is the default case with pip!) you are required to tell cmake where to find PyTorch. This can be done in step 3 of the quick build by specifying Torch_DIR, for example with

cmake -DTorch_DIR=$(pip3 show torch | grep Location | cut -d ' ' -f 2)/torch/share/cmake/Torch -DCMAKE_BUILD_TYPE=Debug ..

Here are some system specific details to install NSL

1. Linux

1.1 Arch Linux

Arch linux is rather flexible to obtain the newest versions of any software. This allows to install the newest g++ compilers & PyTorch via the package manager. For g++ this would mean

sudo pacman -S gcc 

Once g++ 11 is outdated and newer versions fail to build NSL (hopefully this never happens) one can fall back to a g++11 installation using the AUR. For more information visit the official arch linux documentation.

PyTorch can be installed in a similar way

sudo pacman -S python-pytorch

or with GPU support

sudo pacman -S python-pytorch-cuda

For (nvidia) GPU support also ensure that the cuda-toolkit is installed. For more details on nvidia on arch linux visit the official nvidia arch wiki as well as the nvidia installation documentation

If PyTorch is built with pip3, specify Torch_DIR as explained above.

1.2 Ubuntu

We tested NSL on an Ubuntu 20.04 system. Older versions might fail or this documentation does not cover the required details.

First, the default version of cmake is not sufficient and must be updated following the forum the following steps do the trick

1. Ensure the defaul cmake is removed

sudo apt remove --purge --auto-remove cmake
sudo apt update

2. Get the signin key

wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc 2>/dev/null | gpg --dearmor - | sudo tee /etc/apt/trusted.gpg.d/kitware.gpg >/dev/null

3. Add the repository for cmake (20.04 specific command)

sudo apt-add-repository 'deb https://apt.kitware.com/ubuntu/ focal main'
sudo apt update

4. Install cmake

sudo apt install cmake

To verify ensure that cmake --version returns a version larger or equal then 3.18

The next step is to install g++11, following this blog article

1. Install the gnu compiler with major version 11

sudo apt install gcc-11 g++-11

2. Make those the default choice WARNING! This could break dependencies.

sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-11 100 --slave  /usr/bin/g++ g++ /usr/bin/g++-11

Now you need to install PyTorch. Here it is recommended to use pip.

1. Install Python pip

sudo apt install python3-pip

2. Now install PyTorch:

sudo pip3 install torch torchvision torchaudio

This automatically detects weather GPU support is available and installs the correct pytorch version.

Now you can use the quick build to compile NSL, don't forget to specify Torch_DIR as explained above.

2. macOS

Ensure that your clang version matches one of the above.

PyTorch can be installed using pip3

pip3 install torch torchvision torchaudio

If PyTorch is build with pip3, specify Torch_DIR as explained above.

3. Windows

A build for windows is only given using the Windows Subsystem for Linux which can be installed through the powershell using

wsl --install

This should install an Ubuntu 20.04 kernel, hence further prerequisites can be found at section 1.2 Ubuntu.

Dependencies

• Pytorch
• Catch 2