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Collaborative Research: Frameworks: Scalable Modular Software and Methods for High-Accuracy Materials and Condensed Phase Chemistry Simulation

Collaborative Research: Frameworks: Scalable Modular Software and Methods for High-Accuracy Materials and Condensed Phase Chemistry Simulation
合作研究:框架:用于高精度材料和凝聚相化学模拟的可扩展模块化软件和方法
批准号:
1931258
负责人:
Edgar Solomonik
金额:
$95.48万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-10-01 至 2024-09-30

项目摘要

项目成果

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中文摘要
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英文摘要
How electrons are arranged in materials gives rise to a large variety of different behaviors. We can observe these behaviors and use them in various technologies. However, the prediction of these behaviors is a serious challenge. This makes the successful design of new materials harder. The goal of the Materials Genome Initiative is to use computer simulations to model electrons according to the laws of quantum physics. This will allow researchers to design new materials with desired properties. This project aims to build fast and accurate computer programs which simulate those new materials. These programs combine advances in computer science, quantum chemistry, and condensed-matter physics. They will be implemented in an open-source Python-based community code. This distribution model allows other researchers to use this code and to contribute new features.This research addresses gaps in existing software cyberinfrastructure in quantum materials simulation, by developing novel parallel implementations of low-scaling, high-accuracy methods. In particular, new techniques for mean-field calculations will be developed, which will act as groundwork for periodic coupled-cluster and quantum Monte Carlo methods. State-of-the-art techniques in sparsity and tensor decomposition will be employed to achieve good system-size scaling while retaining accuracy within each of these numerical schemes. Critically, the methods will be developed using efficient high-level software abstractions, implemented as Python-level modules within PySCF that leverage the Cyclops library for massively-parallel execution. The library software infrastructure will also be extended to maximize productivity via source-to-source automatic differentiation, as well as to enable execution of sparse kernels on emerging GPU-based supercomputing architectures. This award is jointly supported by the NSF Office of Advanced Cyberinfrastructure, and the Division of Materials Research and the Division of Chemistry within the NSF Directorate of Mathematical and Physical Sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
Quantification of electron correlation for approximate quantum calculations
用于近似量子计算的电子相关性的量化
DOI: 10.1063/5.0119260
发表时间: 2022
期刊: The Journal of Chemical Physics
影响因子: --
作者: [Yuan, Shunyue, Chang, Yueqing, Wagner, Lucas K.]
通讯作者: Wagner, Lucas K.
Comparison of Accuracy and Scalability of Gauss--Newton and Alternating Least Squares for CANDECOMC/PARAFAC Decomposition
CANDECOMC/PARAFAC分解的高斯-牛顿法和交替最小二乘法的精度和可扩展性比较
DOI: 10.1137/20m1344561
发表时间: 2021
期刊: SIAM Journal on Scientific Computing
影响因子: 3.1
作者: [Singh, Navjot, Ma, Linjian, Yang, Hongru, Solomonik, Edgar]
通讯作者: Solomonik, Edgar
DOI: 10.1145/3410463.3414647
发表时间: 2020-05
期刊: Proceedings of the ACM International Conference on Parallel Architectures and Compilation Techniques
影响因子: --
作者: [Linjian Ma;Jiayu Ye;Edgar Solomonik]
通讯作者: Linjian Ma;Jiayu Ye;Edgar Solomonik
DOI: 10.1002/nla.2431
发表时间: 2018-11
期刊: Numerical Linear Algebra with Applications
影响因子: 4.3
作者: [Linjian Ma;Edgar Solomonik]
通讯作者: Linjian Ma;Edgar Solomonik
8
    Conference: Workshop on Sparse Tensor Computations
    CAREER: Next-Generation Infrastructure for Tensor Computations
    国内基金
    海外基金
    Research on Quantum Field Theory without a Lagrangian Description
    • 批准号:
      24ZR1403900
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
      SATOSHI NAWATA
    • 依托单位:
    Cell Research
    Cell Research
    Cell Research (细胞研究)