Where: Spine Auditorium
Description
This lecture will discuss recent programming models for High Performance Computing and Big Data Analytics across two sessions: The first session focuses on the Message Passing Interface MPI, the most widely used programming model on High Performance Computing Systems, and the most recent features added by the MPI-2.2 and MPI-3.0 specification. This talk will also discuss implementation aspects based on experience of the speaker with the Open MPI library. The second session focuses on the Hadoop ecosystem widely utilized in Big Data Analytics, and the programming models propagated by Hadoop such as Map-Reduce. This talk will touch on the entire eco-system of Hadoop, including Hbase - a non-SQL database often deployed with Hadoop-, PIG a querying and scripting language popular with Hadoop users- ,and Spark, an emerging programming model for Big Data Analytics developed at the University of Califorina at Berkely.
Edgar Gabriel
Edgar Gabriel is an Associate Professor in the department of Computer Science at the University of Houston, USA. Prior to that,he was a post-doctoral researcher in the Innovative Computing Laboratory at the University of Tennessee, USA and at the High Performance Computing Center (HLRS) in Stuttgart, Germany. He got his doctoral degree from the University of Stuttgart, Germany. His research interests are in High Performance Computing, Parallel I/O and Message Passing Systems. He is an early contributor to the popular Open MPI library, and the lead architect of numerous other message passing systems, including Volpex MPI, ADCL and PACX-MPI. http://www.cs.uh.edu/~gabriel
Malek Smaoui
Malek Smaoui received her M.S. in 2009 and Ph.D. in 2011 in computer science from the University of Houston. Her research interests are primarily in parallel computing, volunteer computing with BOINC and optimizations with evolutionary algorithms for scientific applications. She is currently a lecturer at King Abdullah University of Science and Technology with focus on teaching parallel programming models and high performance computing and architecture.
Saber Feki
Saber Feki received his PhD in computer science at the University of Houston in 2010. His research interests are in high performance computing, automatic performance tuning and parallel programming models. In 2011, he joined the oil and gas giant TOTAL as an HPC Research Scientist and he currently holds the position of computational scientist at the KAUST Supercomputing Laboratory. His latest activities are focused on accelerating seismic imaging and electromagnetics applications using OpenACC.
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