题目：Enabling Big-data Computing Workflows in High-performance Networks
报告人：吴奇石 教授
地点：学院101会议室
时间：2016年12月15日（星期四） 晚上7：30
学术报告简介:
Many applications in various science, business, and industry domains are producing colossal amounts of data, now frequently termed as “big data”, on the order of terabyte at present and petabyte or even exabyte in the predictable future. No matter which type of data is considered, an end-to-end computing solution that facilitates data transfer, processing, visualization, and analytics would be essential for scientific research, knowledge discovery, or business intelligence. Such computing solutions are typically built upon data- and network-intensive workflows comprised of computing modules with complex dependencies. The goal of our research is to develop an integrated and automated workflow solution to support big-data applications in high-performance networks. Together with science collaborators at national laboratories within U.S. Department of Energy, we design a three-layer workflow architecture where the workflow performance is optimized through the co-scheduling of computing and networking resources based on resource abstraction, bandwidth reservation, and workflow mapping. This talk provides a brief tutorial on big-data scientific applications and shares our research results on various enabling technologies based on rigorous algorithm design, theoretical dynamics analysis, and real network implementation, deployment, and evaluation.
报告人简介:
吴奇石，现任美国新泽西理工学院（NJIT）终身教授，大数据中心主任，博士生导师，美国橡树岭国家实验室合作研究员，中国西北大学国家级特聘教授，郑州大学讲座教授及特聘学科骨干，西安电子科技大学华山学者讲座教授，天津大学客座教授，浙江大学及中国电子科技大学海外特聘专家。1991年考入浙江大学，连读本科、硕士和博士，竺可桢奖学金获得者，全校优秀毕业生代表（告别演讲者）。2000年获美国普渡大学硕士，2003年在美国橡树岭国家实验室完成博士论文，获美国路易斯安那州立大学计算机科学博士学位及最佳博士论文入围奖，并在美国橡树岭国家实验室工作至2006年。同年受聘为美国孟菲斯大学助理教授，2011年获终身教授。2015年受聘为美国新泽西理工学院终身教授及大数据中心主任。在顶级会议（如INFOCOM、IPDPS）和顶级期刊（如ACM/IEEE TON、TC、TPDS、TKDE等）发表了近200篇论文，获得多个国际会议最佳论文奖。是多个专业期刊的编辑部成员，组织了多次有影响力的国际会议（如IEEE CLOUD等），多次入选美国能源部、美国国家自然科学基金、美国科学进步促进会等组织的科研项目申请评审委员会。