INI Seminar: Julio Lopez

Time: April 3, 2009 - 2:30 PM - 3:50 PM

Location: DEC@CIC


Julio López, Systems Scientist, presents "Data-Intensive Scalable Computing for Science."

The INI Seminar takes place every Friday, 2:30 - 3:50 p.m., at the Distributed Education Classroom at the Collaborative Innovation Center (DEC@CIC).

Talk Abstract: Data analytics at scale become extremely difficult as data set sizes increase. These tasks are data intensive in nature, constrained by I/O bandwidth and obtain little benefit from abundant computational resources. Internet services companies have developed systems and abstractions to support their search business. Scalable systems, such as GFS/HDFS, Map-Reduce and BigTable, are used to build distributed applications that process, index, and analyze web-scale datasets. Open-source implementations of these systems, such as Hadoop/HDFS/HBase, are available and widely used for analyzing unstructured data. 
Speaker Bio: Julio Lopez is a Systems Scientist faculty in the Parallel Data Laboratory at Carnegie Mellon University. His research interests are in systems and application support for data intensive computing at large scale. His current research focuses on creating scalable approaches for data analytics in high-performance computing. His work includes methods for compression of large seismic wavefields, scalable I/O for ground motion simulations and indexing techniques for multi-dimensional meshes. He obtained his M.S. and Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University, and his B.Eng. in Computer Systems from Universidad EAFIT in Medellín, Colombia.