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北卡罗莱纳州立大学Xipeng Shen教授学术报告

时间:2018年7月5日,下午2:30-4:30

地点:软件园校区行政楼310会议室

主持人:刘卫国


Title:

Modern Computing and Intelligent Programing Systems

现代计算与智能编程系统的发展


AbstractIn this talk, Dr. Shen will discuss some recent progress in the development of intelligent programming systems, especially in raising program analysis and optimizations to a new level, unleashing the hidden power of compilers, and making applications better harness

the power of modern heterogeneous systems (e.g., GPU). He will demonstrate how the progress helps meet some major challenges in modern computing, including the rapid increase of the volume and variety of data, the rise of deep learning, the shift of computing towards cloud and IoT, and the fast development of heterogeneity in processors and memory.


摘要:在这次讲座中,慎教授将要介绍他的小组近年来在智能编程系统上取得的一些进展。这些技术把程序分析和优化提升到了一个新的高度,更好地发掘编译器的作用,并且让程序能够有效地克服硬件的局限性,充分地发挥现代异构体系(例如图形处理器)的潜能。慎教授还将阐述这些技术如何帮助迎接现代计算展现出的一系列新的挑战:数据量和数据多样性迅速地增加,深度学习的崛起,云和物联网计算的出现和普及,以及处理器和内存朝向异构性的发展。


Bio (报告人简介):


Xipeng Shen is an Associate Professor in the Computer Science Department at North Carolina State University in USA. He has received a number of recognitions, including Early Career Research Award from the US Department of Energy, CAREER Award from US NSF, Google Faculty Research Award, IBM Center for Advanced Studies Faculty Fellow Award, ACM Distinguished Speaker, and so on. His primary research work lies in the field of programming systems and high performance machine learning, featuring an emphasis on inter-disciplinary problems and approaches. His research has produced influential results in multicore and GPU code optimizations, as well as progresses in machine learning, exemplified with a series of new machine learning algorithms (e.g., Yinyang K-Means, Multi-label Scene Classification) published at major ML/AI venues and adopted by Microsoft and other industry companies.


Prior to joining NC State in 2014 as a Chancellor's Faculty Excellence Program cluster hire in Data-Driven Science, Shen was the Adina Allen Term Distinguished Associate Professor in the Computer Science Department at The College of William and Mary. He spent his sabbatical at MIT, Microsoft Research, and Intel Labs between 2012 and 2013. He was an assistant professor at The College of William and Mary from 2006 to 2012. He received his Ph.D. in Computer Science from University of Rochester in 2006.



慎熙鹏是美国北卡州立大学计算机系的副教授。他获得美国能源部Early Career 研究奖,美国自然基金CAREER奖,谷歌教师研究奖,IBM CAS 教师研究奖, 北卡州立大学学者奖。他是ACM杰出演讲者。他的研究主要在编程系统和高性能机器学习领域,特别关注于交叉领域的问题和方法。他的研究在多核和GPU程序优化方面产生了很多影响。同时,他的研究产生了一系列新的高性能机器学习的算法(例如Yinyang K-Means, Multi-label Scene Classification),得到工业界的采纳和应用。


2014年加入北卡州立大学之前,慎教授是美国威廉玛丽学院的一名Adina Allen冠名副教授。他曾是麻省理工和微软研究院的访问科学家,并担任英特尔 实验室和思科的顾问。他于2006年在美国罗切斯特大学获取计算机博士学位,于 2001年在中科院自动化所获取硕士学位,于1998年在北方工业大学获取学士学位。