Automated performance analysis using ASL performance properties

Authors:
Karl Fürlinger;Michael Gerndt
Affiliations:
Institut für Informatik, Lehrstuhl für Rechnertechnik und Rechnerorganisation, Technische Universität München, Garching, Germany;Institut für Informatik, Lehrstuhl für Rechnertechnik und Rechnerorganisation, Technische Universität München, Garching, Germany
Venue:
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
Year:
2006

Citing 4
Cited 0

The Paradyn Parallel Performance Measurement Tool

Computer
An API for Runtime Code Patching

International Journal of High Performance Computing Applications
On-line automated performance diagnosis on thousands of processes

Proceedings of the eleventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Performance analysis of shared-memory parallel applications using performance properties

HPCC'05 Proceedings of the First international conference on High Performance Computing and Communications

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present our approach for automating the performance analysis of parallel applications based on the idea of ASL performance properties. Our tool Periscope automatically searches for inefficiencies specified as ASL properties, leveraging a set of agents distributed over the target machine and arranged in a tree-like hierarchy. Decomposing the analysis using a set of agents allows the analysis process to be performed in a scalable way. If the machine or target application scales in number of nodes or processors used, Periscope similarly scales in number of agents employed.