报告题目：Cumulon: Simplifying Matrix-Based Data Analytics in the Cloud
报告日期及时间: 4月29日上午9点-10点
报告地点：会议室B403
报告人：Prof. Jun Yang
报告人单位：Duke University, USA
报告摘要:
Cumulon is a system aimed at simplifying the development and deployment of statistical analysis of big data in public clouds. Cumulon allows users to program in their familiar language of matrices and linear algebra, without worrying about how to map data and computation to specific hardware and cloud software platforms. Given requirements in terms of time, monetary cost, and risk tolerance, Cumulon automatically makes intelligent provisioning, configuration, and execution decisions---from the type and number of machines to acquire, to the choice of blocking factors for matrix multiply. For clouds with auction-based markets, where the market conditions, Cumulon helps users decide how to bid for such resources and how to cope with market volatility. In this talk, I will share our experience in building Cumulon, including the alternatives explored and the lessons learned.
报告人简介:
Jun Yang is a Professor of Computer Science at Duke University, where he has been teaching since receiving his Ph.D. from Stanford University in 2001. He is broadly interested in databases and data-intensive systems. He is a recipient of the NSF CAREER Award, IBM Faculty Award, HP Labs Innovation Research Award, and Google Faculty Research Award. He also received the David and Janet Vaughan Brooks Teaching Award at Duke. His current research interests lie in making data analysis easier and more scalable for scientists, statisticians, and journalists.
邀请人：彭智勇教授
