From 69e8f5a3fcc63814a4547ed6141ccfdcb6ebcb9a Mon Sep 17 00:00:00 2001 From: "T.Tian" Date: Sat, 23 Nov 2024 00:43:04 +0800 Subject: [PATCH] implement changes from Phanish --- paper/paper.md | 93 +++++++++++++++++--------------------------------- 1 file changed, 32 insertions(+), 61 deletions(-) diff --git a/paper/paper.md b/paper/paper.md index 844b0d77..b2da6071 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -76,40 +76,40 @@ real-space methods. # Statement of Need -DFT has unargubaly become one of the cornerstones -of electronic structure simulations in chemical and materials sciences due to -its simplicity and wide range of applicability. While -many researchers primarily associate DFT with the plane-wave -pseudopotential method, due to the maturity and wide availability of -such codes, these approaches do have limitations. One long-standing -challenge in DFT is to develop methods that overcomes the huge -computational cost for solving the Kohn-Sham equation, which scales -cubically with respect to the system size. This becomes -especially problematic in massively parallel computing environments, -where the extensive global communication required during Fourier -transformations limits the scalability, making it challenging to -efficiently simulate very large systems in plane-wave DFT. -In plane-wave methods, the global nature of the Fourier basis used limits the ability to -achieve linear scaling [@bowler_order_n_dft_2012]. Moreover, -the periodic nature of the Fourier basis enforces the use of periodic -boundary conditions, making the simulation setup of isolated and -semi-finite systems non-straightforward. A compelling -alternative to overcome these limitations is to solve the Kohn-Sham -equations using a finite-difference (FD) approach on real-space -grids. The locality of the FD method makes real-space DFT methods -inherently scalable, and paves the way for the development of -linearly-scaling solutions to the Kohn-Sham equations. -Real-space DFT also naturally supports both periodic and Dirichlet -boundary conditions, and combinations thereof, -allowing for the flexible treatment of systems in -any dimensionality. +DFT has unargubaly become one of the cornerstones of electronic +structure simulations in chemical and materials sciences due to its +simplicity and wide range of applicability. Among the various +numerical implementations of DFT, the plane-wave pseudopotential +method has gained significant popularity, owing to both its robustness +and the maturity of associated software packages. However, despite +their widespread use, plane-wave methods are not without limitations. +One long-standing challenge in DFT is to develop methods that +overcomes the huge computational cost for solving the Kohn-Sham +equation, which scales cubically with respect to the system size. +This becomes especially problematic in massively parallel computing +environments, where the extensive global communication required during +Fourier transformations limits the scalability, making it challenging +to efficiently simulate very large systems in plane-wave DFT. In +plane-wave methods, the global nature of the Fourier basis used limits +the ability to achieve linear scaling +[@bowler_order_n_dft_2012]. Moreover, the periodic nature of the +Fourier basis enforces the use of periodic boundary conditions, making +the simulation setup of isolated and semi-finite systems +non-straightforward. A compelling alternative to overcome these +limitations is to solve the Kohn-Sham equations using a +finite-difference (FD) approach on real-space grids. The locality of +the FD method makes real-space DFT methods inherently scalable, and +paves the way for the development of linearly-scaling solutions to the +Kohn-Sham equations. Real-space DFT also naturally supports both +periodic and Dirichlet boundary conditions, and combinations thereof, +allowing for the flexible treatment of systems in any dimensionality. In the past few years, the SPARC-X project ([https://github.com/SPARC-X](https://github.com/SPARC-X)) has led efforts to develop an open-source, real-space DFT code that is both user-friendly and competitive with state-of-the-art plane-wave codes. The philosophy of the SPARC-X project is to provide codes that -are highly efficient and portable (i.e. straightforward to install and +are highly efficient and portable (i.e., straightforward to install and use across various computational environments). The codes also seek to be user-friendly and developer-friendly to facilitate the implementation of new algorithms. In line with this, SPARC-X offers @@ -119,8 +119,8 @@ prototyping and small-system simulations, with no external dependencies other than Matlab itself, and 2) C/C++ based SPARC [@xu_sparc-1.0_2021; @zhang_sparc-2.0_2024] for large-scale production calculations that can accommodate a wide range of system sizes and -requires only MPI and MKL/BLAS for compilation. New development of -SPARC has covered topics including spin-orbit coupling, dispersion +requires only MPI and MKL/BLAS for compilation. New features of +SPARC include spin-orbit coupling, dispersion interactions, and advanced exchange-correlation (xc) functionals [@zhang_sparc-2.0_2024], linear-scaling Spectral Quadrature (SQ) method [@suryanarayana_sparc_sq_2018], cyclic/helical symmetry @@ -160,36 +160,7 @@ in a few key aspects, including 1) supporting SPARC-specific features in an ASE-comatible API, 2) a parameter validation mechanism based on SPARC's `LaTeX` documentation, and 3) a versatile socket communication layer for efficient high-throughput calculations. Details will be -discussed in the Features and Functionalities section. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - +discussed next. ![Overview of SPARC-X-API in the SPARC-X project system \label{fig:sparc-overview} @@ -395,7 +366,7 @@ The SPARC-X-API is released as source code in github repository and as a `conda-forge` package [`sparc-x-api`](https://anaconda.org/conda-forge/sparc-x-api). When installed using `conda-forge`, the package is bundled with the -optimized pseudopotentials [@shojaei_sparc_pseudopot_2023], and +optimized SPMS pseudopotentials [@shojaei_sparc_pseudopot_2023], and compatible with the [`sparc`](https://anaconda.org/conda-forge/sparc-x) package that contains the compiled SPARC binary.