This TechTalk will provide an introduction to parallel execution models, focusing on how programmers think about writing programs.
Does the way that programmers or algorithm developers think about the way a parallel computer works influence the approaches that they take? Can the choice of programming approach lead to inefficient solutions? Do we need new ways to program parallel systems? This session will explore common approaches for developing parallel programs and how they can limit scalability and reliability--whether the programs are for single chip parallelism or the world's largest parallel computers. The importance of an execution model and its relationship to programming models and programming systems will be covered, and why we need to consider new execution models for the parallel systems of the future.
What Attendees Can Expect to Learn About:
• What an execution model is • The difference between an execution model, programming model, and programming system • How an execution model influences how a programmer thinks about implementing parallelism • Common parallel programming approaches and how they can lead to poor scalability
Bonus: Extended, post-event Q&A with Bill Gropp (questions answered offline).
William Gropp is the Thomas M. Siebel Chair in the Department of Computer Science, Deputy Director for Research for the Institute of Advanced Computing Applications and Technologies, and Director of the Parallel Computing Institute at the University of Illinois in Urbana-Champaign. He received his Ph.D. in Computer Science from Stanford University in 1982. He was on the faculty of the Computer Science Department of Yale University from 1982-1990 and a member of the Mathematics and Computer Science Division at Argonne National Laboratory from 1990-2007. His research interests are in parallel computing, software for scientific computing, and numerical methods for partial differential equations. He is a Fellow of ACM, IEEE, and SIAM and a member of the National Academy of Engineering.
