NetSci
A Toolkit for High Performance Scientific Network Analysis Computation

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Overview

NetSci is a specialized toolkit designed for advanced network analysis in computational sciences. Utilizing the capabilities of modern GPUs, it offers a powerful and efficient solution for processing computationally demanding network analysis metrics while delivering state-of-the-art performance. For detailed installation instructions and tutorials, please visit NetSci User Documentation For API documentation and a general overview of C++/CUDA portions of the project, please visit the NetSci Developer Documentation.

Installation

Download Miniconda Installation Script:

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh

Execute the Installation Script:

bash Miniconda3-latest-Linux-x86_64.sh

Update Environment Settings:

source ~/.bashrc

Install Git with Conda:

conda install -c conda-forge git

Clone the NetSci Repository:

git clone https://github.com/netscianalysis/netsci.git

Navigate to the NetSci Root Directory:

cd netsci

Create NetSci Conda Environment:

conda env create -f netsci.yml

Activate NetSci Conda Environment:

conda activate netsci

Create CMake Build Directory:

mkdir build

Set NetSci Root Directory Variable:

NETSCI_ROOT=$(pwd)

Navigate to the CMake Build Directory:

cd ${NETSCI_ROOT}/build

Compile CUDA Architecture Script:

nvcc ${NETSCI_ROOT}/build_scripts/cuda_architecture.cu -o cuda_architecture

Set CUDA Architecture Variable:

CUDA_ARCHITECTURE=$(./cuda_architecture)

Configure the Build with CMake:

cmake .. -DCONDA_DIR=$CONDA_PREFIX -DCUDA_ARCHITECTURE=${CUDA_ARCHITECTURE}

Build NetSci:

cmake --build . -j

Build NetSci Python Interface:

make python

Test C++ and CUDA Backend:

ctest

Run Python Interface Tests::

cd ${NETSCI_ROOT}
pytest

Examples and Tutorials

Examples may be found in the examples/ subdirectory.

Detailed tutorials can be found at NetSci User Documentation.

Jupyter notebooks of tutorials can be found in the tutorials/ subdirectory.

Citing NetSci

If you use NetSci, please cite the following paper:

• NetSci: A Library for High Performance Biomolecular Simulation Network Analysis Computation Andrew M. Stokely, Lane W. Votapka, Marcus T. Hock, Abigail E. Teitgen, J. Andrew McCammon, Andrew D. McCulloch, and Rommie E. Amaro Journal of Chemical Information and Modeling 2024 64 (20), 7966-7976 DOI: 10.1021/acs.jcim.4c00899

Copyright

Copyright (c) 2024, Andy Stokely and Lane Votapka