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Total airport and airspace model (TAAM) parallelization combining sequential and parallel algorithms for performance enhancement
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693)
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This paper describes how to achieve a desired speedup by careful selection of appropriate algorithms for parallelization. Our target simulation is the Total Airport and Airspace Model (TAAM), a worldwide standard for aviation analysis. TAAM is designed as a sequential program, and we have increased its speed by incorporating multithreaded algorithms with minimal changes to the underlying simulation architecture. Our method was to identify algorithms that are bottlenecks in the computation and
doi:10.1109/wsc.2003.1261615
dblp:conf/wsc/SoodW03
fatcat:52xxkjvy45g2zol7smgzdw2cwi