Alois Ferscha, University of Vienna, Austria
ferscha@ani.univie.ac.at
Prof. Allen D. Malony,University of Oregon, Eugene, OR, USA
malony@cs.uoregon.edu
Monday, July 7, 9:00 - 16:30
The development of performance measurement and analysis techniques and tools for parallel and distributed supercomputers has made it possible to capture a wealth of data about application and system performance behavior. This data embodies the effects of interacting, performance factors found in the program, its algorithms, the architecture and hardware, and the system software, whose interdependent performance relationships grow ever more complex as the supercomputing environment increases in sophistication. Nevertheless, the user is still, for the most part, placed in the central decision-making role in the use of the techniques/tools, the interpretation of the resulting performance information, and the guidance for program or system modification.
Recent work has sought to move human decision-making out of the performance measurement-diagnosis-optimization loop by employing "intelligent" methods based on automated performance measurement, knowledge-based diagnosis frameworks, online, adaptive performance control, and predictive performance models built from detailed empirical analysis. The term "performance data mining" is used to characterize this work.
| 9:00 - 9:15 | Welcome Alois Ferscha, University of Vienna, Austria |
| 9:15 - 9:45 | Introduction Allen D. Malony, Univ. of Oregon, USA Slides, 77 K, (gzipped, uuencoded 27 K) |
| 9:45 - 10:30 | Performance Optimization of Distributed Applications in an Extensible,
Adaptive Environment Diane Rover, Michigan State University, USA Paper, 459 K, (gzipped, uuencoded 124 K) |
| 10:30 - 11:00 | Coffee Break |
| 11:00 - 11:45 | Performance Analysis of HPF+ Kernels Maria Calzarossa, University of Pavia, Italy Abstract, 40 K |
| 11:45 - 12:30 | Optimistic Network Computing and its Performance Control Steve Turner, University of Exeter, UK Paper, 134 K, (gzipped, uuencoded 77 K) |
| 12:30 - 14:00 | Lunch Break |
| 14:00 - 14:45 | Performance Diagnosis is Dynamic Data Mining Allen D. Malony, University of Oregon, USA Slides, 168 K, (gzipped, uuencoded 64 K) |
| 14:45 - 15:30 | The Autopilot Performance-Directed Adaptive Control System Daniel Reed, University of Illinois, Urbana-Champaign, USA Paper, 194 K, (gzipped, uuencoded 88 K) |
| 15:30 - 16:00 | Coffee Break |
| 16:00 - 16:30 | wrap-up, Closing |