• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

使用多重网格降低执行插值可分离密度拟合的成本。

Use of Multigrids to Reduce the Cost of Performing Interpolative Separable Density Fitting.

作者信息

Smyser Kori E, White Alec, Sharma Sandeep

机构信息

Department of Chemistry, University of Colorado, Boulder, Colorado 80302, United States.

Quantum Simulation Technologies, Inc., Boston ,Massachusetts02135, United States.

出版信息

J Phys Chem A. 2024 Sep 5;128(35):7451-7461. doi: 10.1021/acs.jpca.4c02431. Epub 2024 Aug 26.

DOI:10.1021/acs.jpca.4c02431
PMID:39186251
Abstract

In this article, we present an interpolative separable density fitting (ISDF)-based algorithm to calculate the exact exchange in periodic mean field calculations. In the past, decomposing the two-electron integrals into the tensor hypercontraction (THC) form using ISDF was the most expensive step of the entire mean field calculation. Here, we show that by using a multigrid-ISDF algorithm, both the memory and the CPU cost of this step can be reduced. The CPU cost is brought down from cubic scaling to quadratic scaling with a low computational prefactor which reduces the cost by almost 2 orders of magnitude. Thus, in the new algorithm, the cost of performing ISDF is largely negligible compared to other steps. Along with the CPU cost, the memory cost of storing the factorized two-electron integrals is also reduced by a factor of up to 35. With the current algorithm, we can perform Hartree-Fock calculations on a diamond supercell containing more than 17,000 basis functions and more than 1500 electrons on a single node with no disk usage. For this calculation, the cost of constructing the exchange matrix is only a factor of 4 slower than the cost of diagonalizing the Fock matrix. Augmenting our approach with linear scaling algorithms can further speed up the calculations.

摘要

在本文中,我们提出了一种基于插值可分离密度拟合(ISDF)的算法,用于在周期性平均场计算中计算精确交换项。过去,使用ISDF将双电子积分分解为张量超收缩(THC)形式是整个平均场计算中最耗时的步骤。在此,我们表明,通过使用多重网格-ISDF算法,这一步骤的内存和CPU成本都可以降低。CPU成本从立方缩放降至二次缩放,且计算前置因子较低,成本降低了近两个数量级。因此,在新算法中,与其他步骤相比,执行ISDF的成本在很大程度上可以忽略不计。随着CPU成本的降低,存储分解后的双电子积分的内存成本也降低了多达35倍。使用当前算法,我们可以在单个节点上对包含超过17000个基函数和超过1500个电子的金刚石超胞进行Hartree-Fock计算,且无需使用磁盘。对于此计算,构建交换矩阵的成本仅比对Fock矩阵进行对角化的成本慢4倍。用线性缩放算法扩展我们的方法可以进一步加快计算速度。

相似文献

1
Use of Multigrids to Reduce the Cost of Performing Interpolative Separable Density Fitting.使用多重网格降低执行插值可分离密度拟合的成本。
J Phys Chem A. 2024 Sep 5;128(35):7451-7461. doi: 10.1021/acs.jpca.4c02431. Epub 2024 Aug 26.
2
Interpolative Separable Density Fitting Decomposition for Accelerating Hartree-Fock Exchange Calculations within Numerical Atomic Orbitals.用于在数值原子轨道内加速Hartree-Fock交换计算的插值可分离密度拟合分解
J Phys Chem A. 2020 Jul 9;124(27):5664-5674. doi: 10.1021/acs.jpca.0c02826. Epub 2020 Jun 24.
3
Interpolative Separable Density Fitting for Accelerating Two-Electron Integrals: A Theoretical Perspective.内插可分离密度拟合加速双电子积分:理论视角。
J Chem Theory Comput. 2023 Feb 14;19(3):679-693. doi: 10.1021/acs.jctc.2c00927. Epub 2023 Jan 24.
4
Machine Learning K-Means Clustering Algorithm for Interpolative Separable Density Fitting to Accelerate Hybrid Functional Calculations with Numerical Atomic Orbitals.用于内插可分离密度拟合以加速数值原子轨道混合泛函计算的机器学习K均值聚类算法
J Phys Chem A. 2020 Dec 3;124(48):10066-10074. doi: 10.1021/acs.jpca.0c06019. Epub 2020 Nov 17.
5
Machine Learning K-Means Clustering in Interpolative Separable Density Fitting Algorithm: Advancing Accurate and Efficient Cubic-Scaling Density Functional Perturbation Theory Calculations within Plane Waves.
J Phys Chem A. 2024 Mar 14;128(10):1913-1924. doi: 10.1021/acs.jpca.3c07159. Epub 2024 Mar 4.
6
Machine Learning K-Means Clustering of Interpolative Separable Density Fitting Algorithm for Accurate and Efficient Cubic-Scaling Exact Exchange Plus Random Phase Approximation within Plane Waves.用于平面波中精确且高效的立方标度精确交换加随机相位近似的插值可分离密度拟合算法的机器学习K均值聚类
J Chem Theory Comput. 2024 Mar 12;20(5):1944-1961. doi: 10.1021/acs.jctc.3c01157. Epub 2024 Feb 15.
7
Systematically Improvable Tensor Hypercontraction: Interpolative Separable Density-Fitting for Molecules Applied to Exact Exchange, Second- and Third-Order Møller-Plesset Perturbation Theory.系统可改进张量超收缩:分子的内插可分离密度拟合应用于精确交换、二阶和三阶 Møller-Plesset 微扰理论。
J Chem Theory Comput. 2020 Jan 14;16(1):243-263. doi: 10.1021/acs.jctc.9b00820. Epub 2019 Dec 19.
8
Accelerating Time-Dependent Density Functional Theory and GW Calculations for Molecules and Nanoclusters with Symmetry Adapted Interpolative Separable Density Fitting.利用对称适配插值可分离密度拟合加速分子和纳米团簇的含时密度泛函理论及GW计算
J Chem Theory Comput. 2020 Apr 14;16(4):2216-2223. doi: 10.1021/acs.jctc.9b01025. Epub 2020 Mar 5.
9
Low-Rank Approximations Accelerated Plane-Wave Hybrid Functional Calculations with k-Point Sampling.低秩近似加速含k点采样的平面波混合泛函计算
J Chem Theory Comput. 2022 Jan 11;18(1):206-218. doi: 10.1021/acs.jctc.1c00874. Epub 2021 Dec 17.
10
Even Faster Exact Exchange for Solids via Tensor Hypercontraction.通过张量超收缩实现固体的更快精确交换
J Chem Theory Comput. 2023 Sep 12;19(17):5773-5784. doi: 10.1021/acs.jctc.3c00407. Epub 2023 Aug 16.