Abstract

The Trapper software-engineering environment for parallel and distributed systems comprises tools for software design, hardware configuration, mapping, monitoring, visualization, and performance tuning of parallel applications and systems. This article's authors used Trapper as the main software-development tool to realize a complex industrial research application within the Prometheus collision-avoidance project at Daimler-Benz. In this project, they outfitted a Mercedes 500 SEL research vehicle with 18 cameras and approximately 60 computing nodes for various image-processing and control algorithms such as lane following, obstacle detection, and traffic-sign recognition. This article seeks to analyze the behavior and improve the performance of the most time-consuming task of the whole software: traffic-sign recognition. The authors show how Trapper effectively detected and eliminated performance bottlenecks of this parallel application.

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