MRI: Acquisition of a High-Performance Computing Cluster for Research and Teaching at UC Irvine

MRI:购买高性能计算集群用于加州大学欧文分校的研究和教学

基本信息

项目摘要

This acquisition provides a modern, energy-efficient, campus-wide, High-Performance Computing Community Cluster (HPC3) enabling research and research training in areas ranging from elementary particle physics and quantum chemistry through earth-system modeling and engineering to social ecology. HPC3 is expected to deliver a combination of high flexibility and user friendliness with high efficiency for both massively parallel and shared memory applications that is not always achievable by centralized supercomputing or cloud computing facilities.The acquisition is a mixed CPU/GPU cluster that provides substantial computing power to a diverse, high-performance computing (HPC) community of 13 major user research groups as well as other researchers and students at the institution and three local partnering campuses of California State University. The acquisition will also be used by researchers across the Nation by virtue of HPC3's integration with the Open Science Grid (OSG) and eXtreme Science and Engineering Discovery Environment (XSEDE). Examples of research projects that will use HPC3 include: new elementary particle discovery, first-principles simulations of high-temperature superconductors and quantum spin liquids, simulations of warm dense matter, electronic structure of small-gap compounds, nonadiabatic molecular dynamics simulations of photocatalysts and light-driven materials, Monte Carlosimulations of crowded protein solutions, thermodynamic properties of pharmaceuticals, RNA sequencing, alignment of biological networks, ice-sheet modeling, global climate modeling including cloud effects, geophysical climate data analysis, multiscale materials modeling, and simulations of turbulent flow. All partnering universities are Hispanic-serving institutions, and minorities underrepresented in the Science, Technology, Engineering, and Mathematics (STEM) fields will be actively recruited through mentoring and outreach on campus and to local high schools in underserved areas. HPC3 will also support the development of highly optimized HPC software used by scientists worldwide for simulations in condensed matter physics, quantum chemistry, computational fluid dynamics, and earth system science.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.
此次收购提供了一个现代化的,节能的,校园范围内的,高性能计算社区集群(HPC 3),使研究和研究培训领域,从基本粒子物理学和量子化学,通过地球系统建模和工程社会生态学。HPC 3有望为大规模并行和共享内存应用提供高灵活性和用户友好性以及高效率的组合,而集中式超级计算或云计算设施并不总是能实现这一点。此次收购是一个混合CPU/GPU集群,为多样化、高性能计算(HPC)社区的13个主要用户研究小组以及其他研究人员和学生在该机构和三个当地的合作校园加州州立大学。此次收购还将通过HPC 3与开放科学网格(OSG)和极限科学与工程发现环境(XSEDE)的集成被全国各地的研究人员使用。 将使用HPC 3的研究项目示例包括:新的基本粒子发现,高温超导体和量子自旋液体的第一性原理模拟,热致密物质的模拟,小间隙化合物的电子结构,光催化剂和光驱动材料的非绝热分子动力学模拟,拥挤蛋白质溶液的蒙特卡罗模拟,药物的热力学性质,RNA测序,生物网络的排列、冰盖建模、包括云效应在内的全球气候建模、地球物理气候数据分析、多尺度材料建模和湍流模拟。 所有合作大学都是为西班牙裔服务的机构,在科学,技术,工程和数学(STEM)领域代表性不足的少数民族将通过校园内的辅导和外联活动以及服务不足地区的当地高中积极招募。HPC 3还将支持开发高度优化的HPC软件,供全球科学家用于凝聚态物理、量子化学、计算流体动力学和地球系统科学的模拟。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

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Aparna Chandramowlishwaran其他文献

Optimizing the hypre solver for manycore and GPU architectures
针对众核和 GPU 架构优化 hypre 求解器
  • DOI:
    10.1016/j.jocs.2020.101279
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    D. Sahasrabudhe;Rohit Zambre;Aparna Chandramowlishwaran;M. Berzins
  • 通讯作者:
    M. Berzins
Diagnosis, Tuning, and Redesign for Multicore Performance: A Case Study of the Fast Multipole Method
多核性能的诊断、调整和重新设计:快速多极方法的案例研究
SRC Poster ) PEAK : Parallel EM Algorithm using Kd-tree
SRC 海报 ) PEAK:使用 Kd 树的并行 EM 算法
  • DOI:
  • 发表时间:
    2015
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Laleh Aghababaie Beni;Aparna Chandramowlishwaran
  • 通讯作者:
    Aparna Chandramowlishwaran
Performance evaluation of concurrent collections on high-performance multicore computing systems
高性能多核计算系统上并发集合的性能评估
PASCAL: A Parallel Algorithmic SCALable Framework for N-body Problems
PASCAL:用于 N 体问题的并行算法可扩展框架
  • DOI:
    10.1007/978-3-319-64203-1_35
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Laleh Aghababaie Beni;Aparna Chandramowlishwaran
  • 通讯作者:
    Aparna Chandramowlishwaran

Aparna Chandramowlishwaran的其他文献

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{{ truncateString('Aparna Chandramowlishwaran', 18)}}的其他基金

CAREER: HiPer: A CFD solver for High-Performance Turbulent Flow Simulations on Massively Parallel Machines
职业:HiPer:用于大规模并行机器上高性能湍流模拟的 CFD 求解器
  • 批准号:
    1750549
  • 财政年份:
    2018
  • 资助金额:
    $ 40万
  • 项目类别:
    Continuing Grant
XPS: EXPL: DSD: Portal: A Language and Compiler for Parallel N-body Computations
XPS:EXPL:DSD:Portal:并行 N 体计算的语言和编译器
  • 批准号:
    1533917
  • 财政年份:
    2015
  • 资助金额:
    $ 40万
  • 项目类别:
    Standard Grant

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