CyberTraining: Implementation: Small: COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure (COMPLECS)

网络培训：实施：小型：最终用户全面学习以有效利用网络基础设施 (COMPLECS)

• 批准号: 2320934
• 负责人: Robert Sinkovits
• 金额: $ 50万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2320934&HistoricalAwards=false
• 关键词: CyberTraining; Implementation; Small; COMPrehensive; Learning

Advanced cyberinfrastructure (CI), comprising resources with capabilities beyond those of desktop computing, plays an important role in nearly every scientific and engineering discipline. Most CI users no longer need to write their own software, relying instead on existing robust 3rd party applications. Unfortunately, much of the available training still emphasizes software development topics rather than the skills other than programming that are needed to effectively use advanced CI. COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure (COMPLECS) addresses this gap by creating a coherent training program spanning foundational knowledge to the practical skills that enable these CI users to make best use of these specialized resources. The training consists of three tiers (multi-day workshops, webinars and self-paced study), which gives participants a variety of options that best fit into their schedules. Since workshop participation is limited, preference is given to students and educators at minority serving and primarily undergraduate institutions (MSIs and PUIs), and researchers from domains that have not traditionally used advanced CI. Webinars and self-paced learning are available to all. COMPLECS helps to build a better trained workforce with skills that make them more effective researchers, while also leading to improved utilization of NSF-funded CI resources.COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure (COMPLECS) helps CI Users acquire the skills and knowledge they need to efficiently accomplish their compute and data intensive research. Training topics include parallel computing concepts, intermediate Linux and shell scripting, hardware essentials, batch computing, data management, best practices in securing data and research, interactive computing, getting help and how to work effectively with user support, code migration and installation, high throughput computing and Linux tools for file processing. Except for several foundational topics, the program is designed so that webinar and self-paced study participants can take the training in any order. Materials are available through GitHub repositories, Google drives and captioned recordings of webinars. The evaluation plan consists of both formative components that allows the program to be continuously improved and summative components to ensure that the program is meeting its goals. COMPLECS makes a concerted effort to recruit participants from underrepresented groups though coordination with ACCESS, Campus Champions and other organizations.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.