Sunday, Full Day
Title: Practical Automatic Performance Analysis
Presenters: Michael Gerndt, University of Technology Munich; Barton P. Miller, University of Wisconsin; Tomàs Margalef, Autonomous University of Barcelona; Bernd Mohr, Research Centre Juelich
Level: 10% Introductory | 50% Intermediate | 40% Advanced
Efficient usage of today's hierarchical clustered machines promises scalable high performance at low cost but often demands the usage of more than one parallel programming models in the same application. As a consequence, performance analysis and tuning become more difficult and creates a need for advanced tools.
In the last years progress was made towards the design and implementation of automatic performance analysis tools. First research tools are already available that either allow to automatically analyze program traces, e.g., Kappa-Pi and KOJAK, or even further implement a fully automatic on-line search, e.g., Paradyn. These tools will be presented in this tutorial. In addition, the tutorial will give an overview of standard and new performance analysis techniques, a concise presentation of performance properties for MPI and OpenMP and an overview of other automatic performance analysis tools not presented in this tutorial.
The tutorial will be a combination of presentation and online demonstrations. It will cover information which application people as well as tool developers will find most useful.
The tutorial is given by members of the APART working group (Automatic Performance Analysis: Resources and Tools) which is funded by the European Commission. APART is a collaborative effort of more than twenty partners from United States and Europe. Over the next years, APART will coordinate several development projects for automatic performance analysis tools in Europe and the United States.
Related Tutorials: M8 - Performance Tuning Using Hardware Counter Data; M11 - Performance Technology for Complex Parallel Systems