MRI Acquisition: Multi-Environment Research Computer for Exploration and Discovery (MERCED) Cluster

MRI 采集：用于探索和发现的多环境研究计算机 (MERCED) 集群

• 批准号: 1429783
• 负责人: Hrant Hratchian
• 金额: $ 51.58万
• 依托单位: University of California - Merced
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1429783&HistoricalAwards=false
• 关键词: MRI; Acquisition; Multi; Environment; Research

Scientific computing plays a central role in knowledge discovery and scientific advancement. Over 13% of tenured/tenure-track faculty at the University of California Merced (UCM) specialize in areas focused on computational science. This expertise at UCM cuts through the university's three schools and includes faculty-led labs in the natural sciences, engineering, and social sciences.This proposal seeks support for the acquisition of a shared high-performance computing (HPC) cluster named the Multi-Environment Research Computer for Exploration and Discovery (MERCED). The cluster includes heterogeneous nodes, including nodes with large memory, nodes with large storage space, and GPU nodes. The three specific research areas benefit from this cluster, including modeling and simulation of complex systems, data enabled science, and numerical optimization. In the simulation of complex systems the cluster would advance research in high-performance molecular dynamics, computations of atomistic interactions for friction modeling, first principles simulations of chemical reactions and chemical biology, and fluid dynamics. In data enabled study, the cluster would impact the research in computational system biology, such as handling high-throughput genomics data, cognitive sciences, such as the evolution of language in human populations, history and world culture, such as integration of many datasets representing multiple spatial, temporal and thematic scales and permitting analysis and spatial visualization of this historical data in human affairs, and using GPU computing for speeding up the performance of database systems. In numerical optimization, the cluster would enhance the research in optimizing electric grid, GPU computing for 3D data processing, and signal reconstruction algorithms. The cluster enhances the educational and outreach activities at UCM as well as in the nearby universities.

科学计算在知识发现和科学进步中起着核心作用。加利福尼亚大学默塞德分校（UCM）的终身/终身轨道教师中，超过13％专注于专注于计算科学的领域。 UCM的这种专业知识削减了大学的三所学校，其中包括自然科学，工程和社会科学领域领导的实验室。该提案寻求支持获得共享的高性能计算（HPC）集群，名为多个环境研究计算机的多个环境研究计算机（Merced）。该群集包括异质节点，包括具有较大内存的节点，具有较大存储空间的节点和GPU节点。该集群中的三个特定研究领域受益，包括复杂系统的建模和模拟，支持数据的科学和数值优化。在复杂系统的模拟中，群集将进步研究高性能分子动力学，摩擦建模的原子相互作用的计算，化学反应和化学生物学的第一原理模拟以及流体动力学。 In data enabled study, the cluster would impact the research in computational system biology, such as handling high-throughput genomics data, cognitive sciences, such as the evolution of language in human populations, history and world culture, such as integration of many datasets representing multiple spatial, temporal and thematic scales and permitting analysis and spatial visualization of this historical data in human affairs, and using GPU computing for speeding up the performance of database systems.在数值优化中，群集将增强在优化电网，用于3D数据处理的GPU计算以及信号重建算法的研究。该集群增强了UCM以及附近大学的教育和外展活动。

项目成果

Using projection operators with maximum overlap methods to simplify challenging self‐consistent field optimization

使用具有最大重叠方法的投影算子来简化具有挑战性的自洽场优化

• DOI: 10.1002/jcc.26797
• 发表时间: 2021
• 期刊: Journal of Computational Chemistry
• 影响因子: 3
• 作者: Corzo, Hector H.;Abou Taka, Ali;Pribram‐Jones, Aurora;Hratchian, Hrant P.
• 通讯作者: Hratchian, Hrant P.

A density functional theory investigation of the reaction of water with Ce2O−

水与 Ce2O 反应的密度泛函理论研究

• DOI: 10.1016/j.comptc.2022.113603
• 发表时间: 2022
• 期刊: Computational and Theoretical Chemistry
• 影响因子: 2.8
• 作者: Harb, Hassan;Hratchian, Hrant P.
• 通讯作者: Hratchian, Hrant P.

Enhanced Reactivity for Aromatic Bromination via Halogen Bonding with Lactic Acid Derivatives

• DOI: 10.1021/acs.joc.2c00611
• 发表时间: 2022-06-16
• 期刊: JOURNAL OF ORGANIC CHEMISTRY
• 影响因子: 3.6
• 作者: Baker, Sarah I.;Yaghoubi, Mahshid;Baxter, Ryan D.
• 通讯作者: Baxter, Ryan D.

New Photoelectron–Valence Electron Interactions Evident in the Photoelectron Spectrum of Gd 2 O –

Gd 2 O 光电子能谱中明显的新光电子 — 价电子相互作用 —

• DOI: 10.1021/acs.jpca.1c07818
• 发表时间: 2021
• 期刊: The Journal of Physical Chemistry A
• 作者: Mason, Jarrett L.;Harb, Hassan;Abou Taka, Ali;Huizenga, Caleb D.;Corzo, Hector H.;Hratchian, Hrant P.;Jarrold, Caroline Chick
• 通讯作者: Jarrold, Caroline Chick

Comparison of Linear Response Theory, Projected Initial Maximum Overlap Method, and Molecular Dynamics-Based Vibronic Spectra: The Case of Methylene Blue

线性响应理论、投影初始最大重叠法和基于分子动力学的振动光谱的比较：以亚甲基蓝为例

• DOI: 10.1021/acs.jctc.1c01127
• 发表时间: 2022
• 期刊: Journal of Chemical Theory and Computation
• 影响因子: 5.5
• 作者: Abou Taka, Ali;Lu, Shao-Yu;Gowland, Duncan;Zuehlsdorff, Tim J.;Corzo, Hector H.;Pribram-Jones, Aurora;Shi, Liang;Hratchian, Hrant P.;Isborn, Christine M.
• 通讯作者: Isborn, Christine M.