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Colloquium Details

Performance Analysis for the Exascale Era: Going Beyond Just Measuring Flop/s and Cache Misses

Author:Martin Schulz Lawrence Livermore National Laboratory
Date:March 06, 2015
Time:15:30
Location:220 Deschutes

Abstract

With rising system and application complexity, performance analysis is more important, but also more difficult than ever. In such environments, traditional tools, which measure simple performance metrics such as Flop/s and cache misses and relate them to source code, are no longer sufficient. Instead we require novel approaches that allow a deeper correlation of performance data with application and communication structure, that provide multiple views on measured data, and that offer intuitive visualizations to enable actionable insight.

In this talk I will discuss a general methodology that enables such kind of tools and I will present two novel performance visualization tools as case studies: MemAxis, a memory analysis tool to gather and display data movement within NUMA systems, and Ravel, a trace visualizer based on logical time. Both tools provide the developer with an application centric view of performance data, which aids in capturing the performance behavior of the application and thereby enables optimization.

Biography

Martin Schulz is a Computer Scientist at the Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory (LLNL). He earned his Doctorate in Computer Science in 2001 from the Technische Universitaet Muenchen (Munich, Germany) and also holds a Master of Science in Computer Science from the University of Illinois at Urbana Champaign. He has published over 175 peer-reviewed papers. He currently serves as the chair of the MPI forum, the standardization body for the Message Passing Interface. He is the PI for the Office of Science X-Stack project "Performance Insights for Programmers and Exascale Runtimes" (PIPER) as well as for the ASC/CCE project on Open$\mid$SpeedShop, and is involved in the DOE/Office of Science exascale projects CESAR, ExMatEx, and ARGO.

Martin's research interests include parallel and distributed architectures and applications; performance monitoring, modeling and analysis; memory system optimization; parallel programming paradigms; tool support for parallel programming; power-aware parallel computing; and fault tolerance at the application and system level. Martin was a recipient of the IEEE/ACM Gordon Bell Award in 2006 and an R&D100 award in 2011.