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NSF/CISE Computer Systems Research 2017 PI Meeting

NSF/CISE Computer Systems Research 2017 PI Meeting
NSF/CISE 计算机系统研究 2017 PI 会议
批准号:
1740398
负责人:
Erik Saule
金额:
$21.29万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-04-15 至 2018-03-31

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中文摘要
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英文摘要
The Computing Systems Research (CSR) program of the NSF funds a widerange of systems research including (but not limited to) systems forInternet-of-Things (which makes our homes and city smarter), systems tomake more affordable and energy-efficient our Supercomputers (whichfurthers medical research, our understanding of the universe, andwarns the population of tornadoes and hurricanes, to name a few),systems to improve the usefulness, security, and reliability of oursmartphones, and systems to secure and scale the cloud (which hasexpanded the capabilities of IT systems while dramatically decreasingthe associated costs). The project organizes and funds a communityevent for all the PIs of awards from the CSR program. At this event,the researchers funded by the CSR program will have the opportunity tomeet at-large and share and discuss their research and ideas for thefuture.The project organizes a PI meeting that includes mostly three types ofactivities. Plenary presentations will give a forum for the mostremarkable research in the field to be presented and diffused to alarge audience. These presentations are also useful to set the toneand quality of expected research for the PIs of more recentawards. Poster presentations of ongoing award enable casual scientificconversation and person-to-person research diffusion; they areexpected to strengthen the social interaction between CSR researchersand to lead to new collaborations and synergy in the field. Breakoutsessions will focus on subfield of systems research to summarizerecent successful methodology and identify problems and opportunitiesfor future work. The project provides a forum for systems researchers to meet and toform new collaborations, to discuss and to disseminate successfulefforts, to identify the problems and opportunities of the future, andto maximize the impact of subsequent systems research efforts.
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CAREER: Machine and Structure Oblivious Graph Analytics
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