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SPX: Collaborative Research: NSF Scalable Parallelism in the Extreme (SPX) Workshop on Future Directions for Parallel and Distributed Computing

SPX: Collaborative Research: NSF Scalable Parallelism in the Extreme (SPX) Workshop on Future Directions for Parallel and Distributed Computing
SPX:协作研究:NSF 可扩展并行性极限 (SPX) 并行和分布式计算未来方向研讨会
批准号:
1931313
负责人:
Michael Carbin
金额:
$1.32万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-05-01 至 2020-01-31

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中文摘要
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英文摘要
This NSF Scalable Parallelism in the Extreme (SPX) workshop provides an opportunity for SPX principal investigators as well as other researchers in the areas of parallel and distributed computing to discuss the latest advances, demonstrate technical accomplishments, and inform NSF of important and groundbreaking future research directions in these areas. The technical program, while taking stock of recent results, will include breakout sessions to discuss research directions that address critical concerns in the design and implementation of extremely scalable parallel and distributed systems. The broader impacts include broadening participants' perspectives and providing a venue to form new collaborations. Furthermore, a post-workshop report describing the most important and promising research directions will be made available to the broader research community, to inspire research in those directions.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.
期刊论文(1)
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会议论文
Future Directions for Parallel and Distributed Computing: SPX 2019 Workshop Report
并行和分布式计算的未来方向:SPX 2019 研讨会报告
DOI: --
发表时间: 2019
期刊: NSF Workshop Reports
影响因子: --
作者: [Stoller, Scott D., Carbin, Michael, Adve, Sarita, Agrawal, Kunal, Blelloch, Guy, Stanzione, Dan, Yelick, Katherine, Zaharia, Matei]
通讯作者: Zaharia, Matei
Programming Languages Mentoring Workshop at ACM SIGPLAN Conference on Programming Language Design and Implementation, 2018
CAREER: A Programming Language for Developing Software to Execute Reliably on Unreliable Hardware
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