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Collaborative Research: CyberTraining: CIC: Framework for Integrated Research Software Training in High Energy Physics (FIRST-HEP)

Collaborative Research: CyberTraining: CIC: Framework for Integrated Research Software Training in High Energy Physics (FIRST-HEP)
协作研究:网络培训:CIC:高能物理综合研究软件培训框架 (FIRST-HEP)
批准号:
1829729
负责人:
G J Peter Elmer
金额:
$37.5万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-08-01 至 2024-07-31

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中文摘要
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英文摘要
High-energy physics (HEP) aims to understand the fundamental building blocks of nature and their interactions by using large facilities such as the Large Hadron Collider (LHC) at the European Laboratory for Particle Physics (CERN) in Switzerland and the Long-Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE) planned for the 2020s at Fermilab, in Illinois, as well as many smaller experiments. These experiments generate ever increasing amounts of data and rely on a sophisticated software ecosystem consisting of tens of millions of lines of code that is critical to mine this data and produce physics results. People are the key to developing, maintaining, and evolving this software ecosystem for HEP experiments over many decades. Building the necessary software requires a workforce with a mix of HEP domain knowledge and advanced software skills. The Framework for Integrated Research Software Training in High Energy Physics (FIRST-HEP) project provides a training path from a researcher's first steps through active contribution to software training and workforce development. The project serves the national interest as stated by NSF's mission to promote the progress of science by preparing a workforce trained in cyberinfrastructure and impacts STEM disciplines in terms of much needed and sought after software training.The FIRST-HEP project directly organizes training activities and works with partners to leverage and bring synergy to disparate existing efforts in order to maximize their collective impact. It brings together an extended set of partners from the community to build not only missing basic training elements like introductory programming skills in Python, git and Unix but also use of HEP data formats like ROOT and advanced topics including parallel programming, performance tuning, machine learning and data science for Ph.D. students. It works to build a community of instructors and experiments around the software training material and transforms the approach for research software training in HEP. It builds the workforce required for the cyberinfrastructure challenges of running and planned HEP facilities and experiments in the coming years.The FIRST-HEP education and training activities include specific goals to educate minorities in HEP, K- 12 educators and the broader STEM workforce. The K-12 teachers learn very basic skills of Unix including file management, programming languages, such as C+ and shell scripting. FIRST-HEP harnesses the potential of the underrepresented groups and works to ensure that the pool meets or exceeds the diversity in the larger HEP graduate student population when selecting both training participants and instructors for the HEP fundamental training sessions and the advanced computing schools. FIRST-HEP includes a dedicated outreach activity on cybertraining to the local Puerto Rico public. FIRST-HEP leverages engagement with the Software Carpentries to host training of K-12 teachers at UPRM in basic Software Carpentry skills and who in turn train their students. This encourages the teachers and school authorities to consider incorporating the basic carpentries into the high school curriculum. The training and cyber skills gained during the FIRST-HEP fundamental training courses directly contribute to the broader STEM workforce and trains students to pursue data science careers and other research areas besides HEP, such as Astronomy, where similar software skills are required.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.
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Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP)
  • 批准号:
    2323298
  • 项目类别:
    Cooperative Agreement
  • 资助金额:
    $2500.0万
  • 财政年份:
    2023
  • 负责人:
    G J Peter Elmer
  • 依托单位:
Collaborative Research: Disciplinary Improvements: FAIROS-HEP, a Research Coordination Network for Particle Physics
  • 批准号:
    2226379
  • 项目类别:
    Standard Grant
  • 资助金额:
    $44.07万
  • 财政年份:
    2022
  • 负责人:
    G J Peter Elmer
  • 依托单位:
RAPID: Open Research Infrastructure for COVID-19 Ventilator Data
  • 批准号:
    2031509
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.0万
  • 财政年份:
    2020
  • 负责人:
    G J Peter Elmer
  • 依托单位:
S2I2: Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP)
  • 批准号:
    1836650
  • 项目类别:
    Cooperative Agreement
  • 资助金额:
    $2500.0万
  • 财政年份:
    2018
  • 负责人:
    G J Peter Elmer
  • 依托单位:
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)