Cyberinfrastructure for Accelerating Physics & Astronomy Applications With Many-core and Accelerator-Based Systems

加速物理发展的网络基础设施

基本信息

  • 批准号:
    0961044
  • 负责人:
  • 金额:
    $ 157.9万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2010
  • 资助国家:
    美国
  • 起止时间:
    2010-04-01 至 2014-03-31
  • 项目状态:
    已结题

项目摘要

The rapid increase of data rates and volumes (peta-operations/second, 15 petabytes/year) from physics and astronomy simulations, observations, experiments and analyses are reaching critical computational impasse. To meet the demands of petascale to exascale computing challenges, fundamentally new energy efficient supercomputing architectures and solutions will have to be researched and developed. The uniqueness of this work is in adopting science/application-driven approach where the key application-drivers are identified up-front to assess the efficacy of this new approach. With wide appeal, the new period of energy efficient science with new performance metrics such as operations-per-watt presents a great opportunity to lead the progress of scientific research.We will build a cyberinfrastructure of comprehensive software libraries, tools, frameworks, easy-assembly common hardware modules and complete turnkey solutions by leveraging emerging many-core architectures with emphasis on Graphics Processing Units (GPUs). The three-year research plan will develop algorithms, and hardware infrastructures for efficient scalable solutions directly applicable to a broad range of compute-intensive scientific problems. The set of applications are categorized into three separate domains - simulation, instrumentation and data processing - covering specific real-case challenges in cosmology, astronomy, optics, and image/data processing with potential of interdisciplinary relevance. The developed cyberinfrastructure will be released to the broader scientific community with methodologies for easy implementation. Successfully harnessing the power of the parallel architectures such as GPUs for compute-intensive scientific problems via the planned cyberinfrastructure will open doors for new discovery and revolutionize the growth of science. The infrastructure will actively identify interdisciplinary acceleration overlaps and will alleviate adoption. Extremely high-speed massive simulations will cut the overall execution times by several orders of magnitudes, thereby reducing monthly time cycles, prone to malfunctions and delays, to hours and minutes. Remote on-site handling of high data rates will make real-time imaging in radio astronomy possible for the first time. Partnerships have been established with international groups in National Astronomical Observatories of China, and University of Heidelberg, Germany. The proposed research will engage and enable students. The combination of low cost devices and cyberinfrastructure will supply affordable high performance computing for young researchers and students. The infrastructure will be released to the broader community in yearly cycles with open source license punctuated with workshops to widen the scope of the research.
来自物理学和天文学模拟、观测、实验和分析的数据速率和数据量(千万亿次操作/秒,15千万亿字节/年)的快速增长正在达到关键的计算僵局。为了满足千万亿次到亿次计算挑战的需求,必须研究和开发全新的节能超级计算架构和解决方案。 这项工作的独特之处在于采用了科学/应用驱动的方法,其中预先确定了关键的应用驱动因素,以评估这种新方法的功效。新一代的高能效科学具有广泛的吸引力,新的性能指标(如每瓦操作数)为引领科学研究的进步提供了一个很好的机会。我们将利用新兴的众核架构(重点是图形处理单元(GPU)),建立一个由综合软件库、工具、框架、易于组装的通用硬件模块和完整的交钥匙解决方案组成的网络基础设施。这项为期三年的研究计划将开发算法和硬件基础设施,以实现直接适用于广泛的计算密集型科学问题的高效可扩展解决方案。这套应用程序被分为三个独立的领域-模拟,仪器和数据处理-涵盖宇宙学,天文学,光学和图像/数据处理的具体实际情况的挑战与潜在的跨学科的相关性。开发的网络基础设施将向更广泛的科学界发布,并附有易于实施的方法。通过计划中的网络基础设施,成功地利用GPU等并行架构的力量来解决计算密集型科学问题,将为新发现打开大门,并彻底改变科学的发展。该基础设施将积极识别跨学科加速重叠,并将减轻采用。极高速的大规模模拟将使整体执行时间减少几个数量级,从而将容易出现故障和延迟的每月时间周期减少到几小时和几分钟。高数据率的远程现场处理将首次使射电天文学中的实时成像成为可能。与中国国家天文台和德国海德堡大学的国际团体建立了伙伴关系。拟议的研究将吸引和使学生。低成本设备和网络基础设施的结合将为年轻的研究人员和学生提供负担得起的高性能计算。该基础设施将以每年一次的周期向更广泛的社区发布,其中包括开源许可证,并不时举办研讨会,以扩大研究范围。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Dan Werthimer其他文献

A versatile ground data display system for spacelab experiments
  • DOI:
    10.1007/bf00661153
  • 发表时间:
    1983-01-01
  • 期刊:
  • 影响因子:
    1.500
  • 作者:
    Dan Werthimer;Beth Keer;Michael Lampton
  • 通讯作者:
    Michael Lampton

Dan Werthimer的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Dan Werthimer', 18)}}的其他基金

Digital Instrumentation for the Research Community: The Next Generation of CASPER
研究界数字仪器:下一代 CASPER
  • 批准号:
    2009537
  • 财政年份:
    2020
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Standard Grant
Digital Instrumentation for the Radio Astronomy Community: The Next Generation of CASPER
射电天文学界的数字仪器:下一代 CASPER
  • 批准号:
    1711254
  • 财政年份:
    2017
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Standard Grant
Digital Instrumentation for the Radio Astronomy Community
射电天文学界的数字仪器
  • 批准号:
    1407804
  • 财政年份:
    2014
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Continuing Grant
Collaborative Research: Large-Aperture Experiment to Detect the Dark Age (LEDA)
合作研究:探测黑暗时代的大孔径实验(LEDA)
  • 批准号:
    1106045
  • 财政年份:
    2011
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Continuing Grant
Advanced Multibeam Spectrometer for the GBT
GBT 先进多光束光谱仪
  • 批准号:
    1006509
  • 财政年份:
    2010
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Standard Grant
Collaborative Digital Instrumentation for the Radio Astronomy Community
射电天文学界的协作数字仪器
  • 批准号:
    0906040
  • 财政年份:
    2009
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Standard Grant
Radio Transient and SETI Sky Surveys Using the Arecibo L-Band Feed Array
使用阿雷西博 L 波段馈电阵列进行无线电瞬变和 SETI 巡天
  • 批准号:
    0808175
  • 财政年份:
    2008
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Continuing Grant
Low Cost, Rapid Development Instrumentation for Radio Telescopes
低成本、快速开发的射电望远镜仪器
  • 批准号:
    0619596
  • 财政年份:
    2006
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Continuing Grant

相似海外基金

CAREER: Accelerating Scientific Discovery via Deep Learning with Strong Physics Inductive Biases
职业:通过具有强物理归纳偏差的深度学习加速科学发现
  • 批准号:
    2338909
  • 财政年份:
    2024
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Continuing Grant
CAREER: Combining Machine Learning and Physics-based Modeling Approaches for Accelerating Scientific Discovery
职业:结合机器学习和基于物理的建模方法来加速科学发现
  • 批准号:
    2239175
  • 财政年份:
    2023
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Continuing Grant
Accelerating the development of novel technologies for nuclear physics
加速核物理新技术发展
  • 批准号:
    ST/W005646/1
  • 财政年份:
    2022
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Research Grant
Accelerating Searches for Beyond the Standard Model Physics and the ATLAS Pixel Detector
加速超越标准模型物理和 ATLAS 像素探测器的搜索
  • 批准号:
    2110963
  • 财政年份:
    2021
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Continuing Grant
EAGER: Collaborative Research:III: Exploring Physics Guided Machine Learning for Accelerating Sensing and Physical Sciences
EAGER:协作研究:III:探索物理引导机器学习以加速传感和物理科学
  • 批准号:
    2026710
  • 财政年份:
    2020
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Standard Grant
EAGER: Collaborative Research: III: Exploring Physics Guided Machine Learning for Accelerating Sensing and Physical Sciences
EAGER:协作研究:III:探索物理引导机器学习以加速传感和物理科学
  • 批准号:
    2026703
  • 财政年份:
    2020
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Standard Grant
EAGER: Collaborative Research: III: Exploring Physics Guided Machine Learning for Accelerating Sensing and Physical Sciences
EAGER:协作研究:III:探索物理引导机器学习以加速传感和物理科学
  • 批准号:
    2026704
  • 财政年份:
    2020
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Standard Grant
EAGER: Collaborative Research: III: Exploring Physics Guided Machine Learning for Accelerating Sensing and Physical Sciences
EAGER:协作研究:III:探索物理引导机器学习以加速传感和物理科学
  • 批准号:
    2026702
  • 财政年份:
    2020
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Standard Grant
RUI: Machine Learning Approaches for Accelerating Scientific Discovery in Nuclear Physics
RUI:加速核物理科学发现的机器学习方法
  • 批准号:
    2012865
  • 财政年份:
    2020
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Continuing Grant
Collaborative Research: Science-Aware Computational Methods for Accelerating Data-Intensive Discovery: Astroparticle Physics as a Test Case
协作研究:加速数据密集型发现的科学感知计算方法:天体粒子物理学作为测试用例
  • 批准号:
    1940074
  • 财政年份:
    2019
  • 资助金额:
    $ 157.9万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了