Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/wavefunction91/GauXC
GauXC is a modern, modular C++ library for the evaluation of quantities related to the exchange-correlation (XC) energy (e.g. potential, etc) in the Gaussian basis set discretization of Kohn-Sham density function theory (KS-DFT) on heterogenous architectures.
https://github.com/wavefunction91/GauXC
dft gpu integrator
Last synced: 3 months ago
JSON representation
GauXC is a modern, modular C++ library for the evaluation of quantities related to the exchange-correlation (XC) energy (e.g. potential, etc) in the Gaussian basis set discretization of Kohn-Sham density function theory (KS-DFT) on heterogenous architectures.
- Host: GitHub
- URL: https://github.com/wavefunction91/GauXC
- Owner: wavefunction91
- License: other
- Created: 2020-07-23T19:10:41.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2024-07-30T21:31:05.000Z (4 months ago)
- Last Synced: 2024-07-31T01:44:58.803Z (4 months ago)
- Topics: dft, gpu, integrator
- Language: C++
- Homepage:
- Size: 8.95 MB
- Stars: 26
- Watchers: 8
- Forks: 18
- Open Issues: 26
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
Awesome Lists containing this project
README
# About
GauXC Copyright (c) 2020-2024, The Regents of the University of California,
through Lawrence Berkeley National Laboratory (subject to receipt of
any required approvals from the U.S. Dept. of Energy). All rights reserved.
If you have questions about your rights to use or distribute this software,
please contact Berkeley Lab's Intellectual Property Office at
[email protected].
NOTICE. This Software was developed under funding from the U.S. Department
of Energy and the U.S. Government consequently retains certain rights. As
such, the U.S. Government has been granted for itself and others acting on
its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the
Software to reproduce, distribute copies to the public, prepare derivative
works, and perform publicly and display publicly, and to permit others to do so.
# Synopsis
GauXC is a modern, modular C++ library for the evaluation of quantities related
to the exchange-correlation (XC) and exact-exchange (K) energy (e.g. potential, etc) in the Gaussian
basis set discretization of Kohn-Sham density function theory (KS-DFT). GauXC
provides efficient, scalable distributed memory XC and K integrators for both CPU and
accelerator-based (GPU) architectures. Currently, GPU support is provided through
the
[CUDA](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html) and
[HIP](https://rocmdocs.amd.com/en/latest/Programming_Guides/HIP-GUIDE.html)
frameworks to target NVIDIA and AMD GPUs, respectively.
Evaluation
of the XC functional CPU/accelerator architectures is provided by the
[ExchCXX](https://github.com/wavefunction91/ExchCXX) library. Quadratures are generated
by the [IntegratorXX](https://github.com/wavefunction91/IntegratorXX).
GauXC is a work in progress. Its development has been funded by the U.S.
Department of Energy Exascale Computing Project
([NWChemEx](https://github.com/NWChemEx-Project)).
# Design Goals
* Provide a stable, portable and high-performance implementation of numerical
integrators optimized for the evaluation of XC and K related quantities in Gaussian
basis set KS-DFT on CPU and accelerator based architectures.
* Develop a modern, modular, extensible C++ software infrastructure which allows
for flexible and agile development in the field of KS-DFT.
# Dependencies
* CMake (3.20+)
* BLAS (for CPU integrators)
* [ExchCXX](https://github.com/wavefunction91/ExchCXX)
* [IntegratorXX](https://github.com/wavefunction91/IntegratorXX)
* [Gau2Grid](https://github.com/dgasmith/gau2grid) (pregenerated source packaged with GauXC)
* MPI (Optional)
* OpenMP (CPU parallelism, Optional)
* [Cereal](https://github.com/USCiLab/cereal) (Optional)
* [HDF5](https://www.hdfgroup.org/solutions/hdf5/) (Optional)
* [Eigen3](https://eigen.tuxfamily.org/dox/) (Testing Only)
* [CUDA](https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html)/[cuBLAS](https://docs.nvidia.com/cuda/cublas/index.html) (Required only if CUDA enabled)
* [HIP](https://rocmdocs.amd.com/en/latest/Programming_Guides/HIP-GUIDE.html)/[ROCm](https://github.com/RadeonOpenCompute/ROCm) (Required only if HIP enabled)
* [MAGMA](https://icl.utk.edu/magma/) (Optional if CUDA/HIP enabled)
# Major Contributors
Primary Developer and Maintainer: David Williams-Young - LBNL (dbwy at lbl dot gov)
GauXC has received major contributions from the following developers (in no particular order):
* Thom Popovici (LBNL) - Optimized sn-K kernels for CPU and GPU architectures
* Teri Lambros (UW) - Unrestricted (UKS) and Generalized (GKS) DFT
* Daniel Mejia-Rodriguez (PNNL) - Meta-GGA DFT
We have also receieved significant support from industry collaborators:
* David Clark (NVIDIA) - Optimization of critical kernels for NVIDIA architectures
* Damon McDougall (AMD) - Optimization of critical kernels for AMDGPU architectures
# Publications
## GauXC
Please cite the following publications if GauXC was used in your publication:
```
% Distributed Memory Seminumerical Exact Exchange implementation
@article{williams2023distributed,
title = {Distributed memory, GPU accelerated Fock construction for hybrid, Gaussian basis density functional theory},
author = {Williams-Young, David B. and Asadchev, Andrey and Popovici, Doru Thom and Clark, David and Waldrop, Jonathan and
Windus, Theresa L. and Valeev, Edward F. and de Jong, Wibe A.},
journal = {The Journal of Chemical Physics},
volume = {158},
number = {23},
pages = {234104},
year = {2023},
doi = {10.1063/5.0151070},
url = {https://doi.org/10.1063/5.0151070}
}
% Performance Portability (HIP/SYCL implementations)
@article{williams2021achieving,
title={Achieving performance portability in Gaussian basis set density functional
theory on accelerator based architectures in NWChemEx},
author={Williams-Young, David B and Bagusetty, Abhishek and de Jong, Wibe A and
Doerfler, Douglas and van Dam, Hubertus JJ and V{\'a}zquez-Mayagoitia, {\'A}lvaro and
Windus, Theresa L and Yang, Chao},
journal={Parallel Computing},
volume={108},
pages={102829},
year={2021},
doi={10.1016/j.parco.2021.102829},
url={https://www.sciencedirect.com/science/article/pii/S0167819121000776?via%3Dihub}
}
% CUDA and distributed memory implementation
@article{williams20on,
author={David B. Williams--Young and Wibe A. de Jong and Hubertus J.J. van Dam and
Chao Yang},
title={On the Efficient Evaluation of the Exchange Correlation Potential on
Graphics Processing Unit Clusters},
journal={Frontiers in Chemistry},
volume={8},
pages={581058},
year={2020},
doi={10.3389/fchem.2020.581058},
url={https://www.frontiersin.org/articles/10.3389/fchem.2020.581058/abstract},
preprint={https://arxiv.org/abs/2007.03143}
}
% Algorithm for XC potential assembly and shared-memory CPU implementation
@article{petrone18an,
author={Alessio Petrone and David B. Williams--Young and Shichao Sun and
Torin F. Stetina and Xiaosong Li},
title={An Efficient Implementation of Two-Component Relativistic Density
Functional Theory with Torque-Free Auxiliary Variables},
journal={The European Physical Journal B},
volume={91},
number={169},
pages={},
year={2018},
doi={10.1140/epjb/e2018-90170-1},
url={https://link.springer.com/article/10.1140/epjb/e2018-90170-1}
}
```
## Density functionals
If GauXC was used for the evaluation of exchange-correlation related
quantities in your publication, we request that you also cite
[Libxc](https://libxc.gitlab.io/) which provides the underlying
implementation of the exchange-correlation functionals used in GauXC
via the [ExchCXX](https://github.com/wavefunction91/ExchCXX) library:
```
% Actual Implementations of the Density Functionals
@article{lehtola2018libxc,
author = {Lehtola, Susi and Steigemann, Conrad and Oliveira, Micael J. T. and Marques, Miguel A. L.},
journal = {SoftwareX},
title = {Recent developments in {LIBXC}---a comprehensive library of functionals for density functional theory},
year = {2018},
pages = {1--5},
volume = {7},
doi = {10.1016/j.softx.2017.11.002},
}
```
# Build Instructions
GauXC provides a CMake build system with automatic dependency management (through [FetchContent](https://cmake.org/cmake/help/latest/module/FetchContent.html)).
As such, a simple CMake invocation will often suffice for most purposes
```
cmake -S /path/to/gauxc -B /path/to/build [GauXC configure options]
cmake --build /path/to/build
```
GauXC is linkable both as an installed library as well as a CMake subproject via `FetchContent`
```
# GauXC Discovery
find_package( gauxc REQUIRED )
target_link_libraries( my_target PUBLIC gauxc::gauxc )
```
```
# GauXC as CMake Subproject
include(FetchContent)
# Set GauXC CMake options (see below)
# Pull master branch of GauXC
FetchContent_Declare( gauxc
GIT_REPOSITORY https://github/com/wavefunction91/GauXC.git
GIT_TAG master
)
FetchContent_MakeAvailable( gauxc )
# Link to target
target_link_libraries( my_target PUBLIC gauxc::gauxc )
```
## Influential CMake Variables
| Variable Name | Description | Default |
|----------------------------|-----------------------------------------------------------|----------|
| `GAUXC_ENABLE_TESTS` | Enable Testing Framework (Catch2) | `ON` |
| `GAUXC_ENABLE_HOST` | Enable HOST integrators | `ON` |
| `GAUXC_ENABLE_CUDA` | Enable CUDA integrators | `OFF` |
| `GAUXC_ENABLE_HIP` | Enable HIP integrators | `OFF` |
| `GAUXC_ENABLE_MAGMA` | Enable MAGMA for batched BLAS (No effect if no GPU) | `ON` |
| `GAUXC_ENABLE_CUTLASS` | Enable CUTLASS for batched BLAS (No effect if no CUDA) | `OFF` |
| `GAUXC_ENABLE_NCCL` | Enable NCCL bindings for topology aware GPU reductions | `OFF` |
| `GAUXC_ENABLE_MPI` | Enable MPI Bindings | `ON` |
| `GAUXC_ENABLE_OPENMP` | Enable OpenMP Bindings | `ON` |
| `CMAKE_CUDA_ARCHITECTURES` | CUDA architechtures (e.g. 70 for Volta, 80 for Ampere) | -- |
| `BLAS_LIBRARIES` | Full BLAS linker. | -- |
| `MAGMA_ROOT_DIR` | Install prefix for MAGMA. | -- |
# Example Usage
Coming Soon.... See `test/standalone_driver.cxx` for an example end-to-end invocation of GauXC for various integrands.
# License
GauXC is made freely available under the terms of a modified 3-Clause BSD license. See
LICENSE.txt for details.
# Acknowledgments
The development of GauXC is supported by the Exascale Computing Project
(17-SC-20-SC), a collaborative effort of the U.S. Department of Energy Office
of Science and the National Nuclear Security Administration.