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Microwave-shielded polar molecules
Non-Hermitian topology and braiding with photonic crystals
物理系colloquium: 超快激光精密制造
Remarks on fluctuations in large N dynamics
报告题目:
Managing and Exploiting Big Data for a Smarter Planet
 报告人:
Dr. Tilak Agerwala
Vice President, Systems IBM TJ Watson Research Center
报告时间:
2012-04-25 10:00
报告地点:
1-315, FIT Building
主办单位:
信研院(RIIT)
  简介:

2012清华大学信息技术研究院校庆学术活动之一

2012年清华大学信研院系列学术报告3

Biography:

Tilak Agerwala is vice president, Systems at IBM Research. He is responsible for developing the next-generation systems hardware and software technologies for IBM's Blue Gene Supercomputers, mainframe and Unix computers, storage systems, and data center networking. Dr. Agerwala joined IBM at the T.J. Watson Research Center and has held executive positions at IBM in research, advanced development, development, marketing and business development. His research interests are in the area of high performance computer architectures and systems. Dr. Agerwala received the W. Wallace McDowell Award from the IEEE in 1998 for “outstanding contributions to the development of high performance computers.” He is a founding member of the IBM Academy of Technology. He is a Fellow of the Institute of Electrical and Electronics Engineers. He received his B.Tech in electrical engineering from the Indian Institute of Technology, Kanpur, India and his Ph.D in electrical engineering from the Johns HopkinsUniversity, Baltimore, Maryland.

Abstract:

The explosion of real world events and information has created the need for building a new kind of intelligence to manage and benefit from Big Data in a timely and cost effective fashion. My presentation will give an overview of this massive opportunity and the emerging big analytics solutions for exploiting this new resource. It will lay out our vision of a consistent, extensible, and consumable analytics platform that will reduce cost-to-value for enterprises and will increase analytics solution coverage. I will also highlight the emergence of a data centric computing paradigm to support emerging internet scale analytics workloads.

 

 

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