Scaling Performance Measurement and Analysis Tools for Parallel Programming
May 29, 2008
The number of processor cores available in high-performance computing systems is steadily increasing. In the latest (Nov 2007) list of the TOP500 supercomputers, 86% of the systems listed have more than 1024 processor cores and the average is about 3300. While these machines promise ever more compute power and memory capacity to tackle today's complex simulation problems, they force application developers to greatly enhance the scalability of their codes to be able to exploit it. To better support them in their porting and tuning process, many parallel tools research groups have already started to work on scaling their methods, techniques, and tools to extreme processor counts.
In this talk, I start with surveying existing profiling and tracing tools, report on our experience in using them in extreme scaling environments, review existing working and promising new methods and techniques, and discuss strategies for solving unsolved issues and problems. Secondly, I give an overview of the status and currently on-going work on Scalasca, Juelich's project on "Scalable Performance Analysis of Large-Scale Applications" including first experiences porting and using Scalasca on Jugene, Juelich's 65,536 core BlueGene/P system.
About NERSC and Berkeley Lab
The National Energy Research Scientific Computing Center (NERSC) is the primary high-performance computing facility for scientific research sponsored by the U.S. Department of Energy's Office of Science. Located at Lawrence Berkeley National Laboratory, the NERSC Center serves more than 4,000 scientists at national laboratories and universities researching a wide range of problems in combustion, climate modeling, fusion energy, materials science, physics, chemistry, computational biology, and other disciplines. Berkeley Lab is a U.S. Department of Energy national laboratory located in Berkeley, California. It conducts unclassified scientific research and is managed by the University of California for the U.S. DOE Office of Science. For more information about computing sciences at Berkeley Lab, please visit www.lbl.gov/cs.
