OpenMP: An Industry-Standard API for Shared-Memory Programming
IEEE Computational Science & Engineering
Euro-Par '98 Proceedings of the 4th International Euro-Par Conference on 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
A Rule-based Approach for Automatic Bottleneck Detection in Programs on Shared
HIPS '97 Proceedings of the 1997 Workshop on High-Level Programming Models and Supportive Environments (HIPS '97)
Autopilot: Adaptive Control of Distributed Applications
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
FINESSE: a prototype feedback-guided performance enhancement system
EURO-PDP'00 Proceedings of the 8th Euromicro conference on Parallel and distributed processing
Performance analysis of large-scale OpenMP and hybrid MPI/OpenMP applications with VampirNG
IWOMP'05/IWOMP'06 Proceedings of the 2005 and 2006 international conference on OpenMP shared memory parallel programming
Performance analysis for teraflop computers: a distributed automatic approach
EUROMICRO-PDP'02 Proceedings of the 10th Euromicro conference on Parallel, distributed and network-based processing
Performance analysis of shared-memory parallel applications using performance properties
HPCC'05 Proceedings of the First international conference on High Performance Computing and Communications
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Performance analysis is an important step in tuning performance critical applications. It is a cyclic process of measuring and analyzing performance data which is driven by the programmer's hypotheses on potential performance problems. 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 ASL we apply it to OpenMP by successfully formalizing several OpenMP performance properties.