Algorithms for Scheduling and Large Data Analysis
When: Monday, March 5, 2012 - 9:45am - 11:00am
Where: KEC 1007
Speaker Information
Speaker Name: Ben Moseley
Speaker Title/Description:
Ph.D. Candidate
University of Illinois Urbana Champaign
Speaker Biography:
Ben Moseley is currently a PhD candidate in the University of Illinois Urbana Champaign (UIUC) and is planning on graduating this May. Ben obtained his M.S. (2008) and B.S. (2006) in computer science at UIUC. While at UIUC, Ben interned at Yahoo! Research during the summers of 2010 and 2011. Ben received the Best Student Paper award at SODA 2010.
Abstract:
In this talk we will be concerned with designing algorithms for schedulers and
MapReduce. The first part of the talk will be on scheduling algorithms. We
will discuss recent developments on scheduling models and performance metrics.
Our focus will be on the recent direction of scheduling research and how it
compares to past work.
The second portion of the talk will focus on designing algorithms for large
data analysis using MapReduce. Recently, the MapReduce parallel computing
framework has become the de facto standard for processing large data. In this
talk we discuss the theoretical model of the MapReduce framework. The
constraints of the MapReduce model pose several algorithmic challenges. We
will introduce recent developments and key research questions related to the
theoretical foundations of MapReduce. We will then introduce some algorithmic
ideas that can be used to design algorithms for MapReduce.
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