美国亚利桑那州立大学Zhao Ming副教授学术讲座

作者:编辑:发布:2016-06-08点击量:

应BETVTOR伟德app智能与分布计算实验室邀请,美国亚利桑那州立大学Zhao Ming副教授将于2016年6月15日(周三)上午来BETVTOR伟德app举行学术报告,欢迎广大师生参加。

讲座题目IBIS: Interposed Big-data I/O Scheduler

讲座时间:2016年6月15日(周三)上午10:00开始

讲座地点:BETVTOR伟德app会议室(南1楼433室)

主讲人:

Ming Zhao

Associate professor of the ArizonaState University (ASU) School of Computing, Informatics,and Decision Systems Engineering (CIDSE)

讲座摘要:

Big-data systemsare increasingly shared by diverse, data-intensive applications from differentdomains. However, existing systems lack the support for I/O management, and theperformance of big-data applications degrades in unpredictable ways when theycontend for I/Os. This talk will introduce IBIS, an Interposed Big-data I/OScheduler, to address this challenge and provide I/O performancedifferentiation for competing applications in a shared big-data system.

IBIS transparentlyintercepts, isolates, and schedules an application’s different phases of I/Osvia an interposition layer on every datanode of the big-data system. Itprovides a new proportional-share I/O scheduler, SFQ(D2), to allow applicationsto share the I/O service of each datanode with good fairness and resourceutilization. Moreover, it enables the distributed I/O schedulers to coordinatewith one another and achieve proportional sharing of the big-data system’stotal I/O service in a scalable manner. The talk will also share theexperimental results of IBIS implemented for Hadoop/YARN, a widely usedbig-data system. The results show that IBIS delivers much stronger performanceisolation than native Hadoop/YARN (99% better for WordCount and 15% better forTPC-H queries) with good resource utilization.

主讲人简介:

Ming Zhao is anassociate professor of the Arizona State University (ASU) School of Computing, Informatics, andDecision Systems Engineering (CIDSE), where he directs the researchlaboratory for Virtualized Infrastructures, Systems, and Applications(VISA, http://visa.lab.asu.edu). His research is in the areas ofexperimental computer systems, including distributed/cloud, big-data, and high-performancesystems as well as operating systems and storage in general. He is alsointerested in the interdisciplinary studies that bridge computer systemsresearch with other domains. His work has been funded by the NationalScience Foundation (NSF), Department of Homeland Security, Departmentof Defense, Department of Energy, and industry companies, and his researchoutcomes have been adopted by several production systems in industry. Dr.Zhao has received the NSF Faculty Early Career Development (CAREER) award,the Air Force Summer Faculty Fellowship, the VMware Faculty Award, andthe Best Paper Award of the IEEE International Conference onAutonomic Computing. He received his bachelor’s and master’s degreesfrom Tsinghua University, and his PhD from University of Florida.

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