EAGER: CDS&E: Field Programmable Gate Arrays (FPGAs) for Enhancing the Speed and Energy Efficiency of Quantum Chemistry Simulations

渴望:CDS

基本信息

  • 批准号:
    2028365
  • 负责人:
  • 金额:
    $ 23.07万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-09-01 至 2025-08-31
  • 项目状态:
    未结题

项目摘要

Professor Bryan M. Wong of the University of California-Riverside is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to utilize new computational hardware, known as Field Programmable Gate Arrays (FPGAs). The goal of this research project is to enhance the speed and energy efficiency of quantum chemistry calculations. Modern quantum chemistry calculations depend critically on massively parallelized computational hardware to enable their predictions. Massively parallel is the term for using a large number of separate computers (or computer processors) to perform a set of coordinated computations simultaneously. Quantitatively accurate predictions from such calculations impact several chemical technologies including combustion, catalysis, process modeling, and chemical production industries. However, the supercomputing centers used to run these predictive calculations consume enormous amounts of energy and resources. Also many such calculations do not scale well as the studied chemical systems grow larger. To address these important issues, FPGAs are being harnessed to enhance the computational speed, as well as to maintain the delicate balance between performance and energy efficiency for large-scale quantum calculations. In addition to addressing these scientific and technological needs, this project is carried out at the University of California-Riverside, which is an accredited Hispanic Serving Institution (HSI). As such, Professor Wong's institution is an ideal place to attract researchers who might otherwise not be aware of the employment opportunities in science and engineering. An FPGA consists of an array of thousands of connection and logic blocks seamlessly connected with each other to create extremely re-configurable programming units. Like Graphics Processing Units (GPUs), FPGAs are ideal for parallelization, but with the added advantage of having reprogrammable circuitry at the hardware level to enable even further parallelization and significant energy gains. This EAGER project is sub-divided into two main (but highly connected) thrusts. Thrust 1 will extend the use of FPGAs to accelerate Fock-matrix builds and Hamiltonian diagonalization for ab initio molecular dynamics (AIMD) and linear-response time-dependent density functional theory calculations, respectively. Thrust 2 will subsequently assess and demonstrate the immense energy efficiency (compared to CPUs/GPUs) of FPGAs for these quantum calculations. The field of quantum chemistry has yet to utilize FPGAs for production-level calculations of any kind, creating an exciting opportunity for transformative leadership in this area. Together these thrusts address basic (yet practical) parallelization issues in quantum chemistry with non-conventional computing approaches, and introduce a new computational capability to perform these quantum chemistry calculations in an energy-efficient manner.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.
加州大学河滨分校的Bryan M. Wong教授利用新的计算硬件,即现场可编程门阵列(fpga),获得了化学学部化学理论、模型和计算方法项目的奖励。这个研究项目的目标是提高量子化学计算的速度和能量效率。现代量子化学计算严重依赖于大规模并行计算硬件来实现他们的预测。大规模并行是使用大量独立的计算机(或计算机处理器)同时执行一组协调计算的术语。从这些计算中得出的定量准确预测影响了几种化学技术,包括燃烧、催化、过程建模和化学生产行业。然而,用于运行这些预测计算的超级计算中心消耗了大量的能源和资源。而且,随着所研究的化学系统变大,许多这样的计算不能很好地扩展。为了解决这些重要问题,fpga正在被用来提高计算速度,以及在大规模量子计算中保持性能和能源效率之间的微妙平衡。除了满足这些科学和技术需求外,该项目还在加州大学河滨分校进行,这是一个经过认证的西班牙裔服务机构(HSI)。因此,黄教授的研究机构是吸引研究人员的理想场所,否则他们可能不知道科学和工程方面的就业机会。FPGA由数千个连接和逻辑块组成,这些连接和逻辑块彼此无缝连接,以创建极其可重新配置的编程单元。与图形处理单元(gpu)一样,fpga是并行化的理想选择,但在硬件级别具有可重新编程电路的额外优势,可以实现进一步的并行化和显著的能量增益。这个EAGER项目被细分为两个主要的(但高度相连的)重点。Thrust 1将扩展fpga的使用,分别加速从头算分子动力学(AIMD)的fock矩阵构建和哈密顿对角化,以及线性响应时变密度泛函理论计算。Thrust 2随后将评估并演示fpga用于这些量子计算的巨大能源效率(与cpu / gpu相比)。量子化学领域尚未利用fpga进行任何类型的生产级计算,这为该领域的变革领导创造了令人兴奋的机会。这些突破共同解决了量子化学中使用非常规计算方法的基本(但实际)并行化问题,并引入了一种新的计算能力,以节能的方式执行这些量子化学计算。该奖项反映了美国国家科学基金会的法定使命,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

期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
HADOKEN: An open-source software package for predicting electron confinement effects in various nanowire geometries and configurations
HADOKEN:一种开源软件包,用于预测各种纳米线几何形状和配置中的电子限制效应
  • DOI:
    10.1016/j.cpc.2022.108299
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    6.3
  • 作者:
    Chevalier, Cameron;Wong, Bryan M.
  • 通讯作者:
    Wong, Bryan M.
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Bryan Wong其他文献

Low-cost model reconstruction from image sequences
从图像序列进行低成本模型重建
Amplification Effects on the Acoustic Change Complex in Older Adults With Sensorineural Hearing Loss
对感音神经性听力损失老年人声学变化复合体的放大效应
Model Reconstruction for a Virtual Interactive MERLIN
虚拟交互式 MERLIN 的模型重建
  • DOI:
  • 发表时间:
    1999
  • 期刊:
  • 影响因子:
    0
  • 作者:
    C. Lyness;Otto;Bryan Wong;P. Marais
  • 通讯作者:
    P. Marais

Bryan Wong的其他文献

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{{ truncateString('Bryan Wong', 18)}}的其他基金

Collaborative Research: DMREF: Organic Materials Architectured for Researching Vibronic Excitations with Light in the Infrared (MARVEL-IR)
合作研究:DMREF:用于研究红外光振动激发的有机材料 (MARVEL-IR)
  • 批准号:
    2323669
  • 财政年份:
    2023
  • 资助金额:
    $ 23.07万
  • 项目类别:
    Continuing Grant
D3SC: Data-Driven Modeling and Experimental Investigation for Discovery of Aquatic Chemistry Reaction Kinetics: New Tools for Water Reuse Applications
D3SC:用于发现水生化学反应动力学的数据驱动建模和实验研究:水回用应用的新工具
  • 批准号:
    1808242
  • 财政年份:
    2019
  • 资助金额:
    $ 23.07万
  • 项目类别:
    Standard Grant
EAGER: CDS&E: An Open-Source Software Package for Assessing and Controlling Photocatalytic Reactions
渴望:CDS
  • 批准号:
    1833218
  • 财政年份:
    2018
  • 资助金额:
    $ 23.07万
  • 项目类别:
    Continuing Grant
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