The Unified Modeling Language reference manual
The Unified Modeling Language reference manual
TAU: A Portable Parallel Program Analysis Environment for pC++
CONPAR 94 - VAPP VI Proceedings of the Third Joint International Conference on Vector and Parallel Processing: Parallel Processing
EARL - A Programmable and Extensible Toolkit for Analyzing Event Traces of Message Passing Programs
HPCN Europe '99 Proceedings of the 7th International Conference on High-Performance Computing and Networking
Autopilot: Adaptive Control of Distributed Applications
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
$P$^$3$$T+$: A performance estimator for distributed and parallel programs
Scientific Programming
FINESSE: a prototype feedback-guided performance enhancement system
EURO-PDP'00 Proceedings of the 8th Euromicro conference on Parallel and distributed processing
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Multiprocessor systems are increasingly being used to handle large-scale scientific applications that demand high-performance. However, performance analysis is not as mature for multiprocessor systems as for uniprocessor systems, and improved ways of automatic performance analysis are needed to reduce the cost and complexity of developing distributed/ parallel applications. Performance analysis is commonly a cyclic process of measuring and analyzing performance data, identifying and possibly eliminating performance bottlenecks in slow progression. Currently this process is controlled manually by the programmer. We believe that the implicit knowledge applied in this cyclic process should be formalized in order to provide automatic performance analysis for a wider class of programming paradigms and target architectures. This article describes the performance property specification language (ASL) developed in the APART Esprit IV working group which allows specifying performance-related data by an object-oriented model and performance properties by functions and constraints defined over performance-related data. Performance problems and bottlenecks can then be identified based on user- or tool-defined thresholds. In order to demonstrate the usefulness of ASLw e apply it to HPF (High Performance Fortran) by successfully formalizing several HPF performance properties.