Parallel implementation of the TRANSIMS micro-simulation
Kai Nagel,M. Rickert +1 more
- Vol. 27, Iss: 12, pp 1611-1639
TLDR
This paper describes the parallel implementation of the TRansportation ANalysis and SIMulation System (TRANSIMS) traffic micro-simulation, and describes how information between domains is exchanged, and how the transportation network graph is partitioned.Abstract:
This paper describes the parallel implementation of the TRansportation ANalysis and SIMulation System (TRANSIMS) traffic micro-simulation. The parallelization method is domain decomposition, which means that each CPU of the parallel computer is responsible for a different geographical area of the simulated region. We describe how information between domains is exchanged, and how the transportation network graph is partitioned. An adaptive scheme is used to optimize load balancing. We then demonstrate how computing speeds of our parallel micro-simulations can be systematically predicted once the scenario and the computer architecture are known. This makes it possible, e.g., to decide if a certain study is feasible with a certain computing budget, and how to invest that budget. The main ingredients of the prediction are knowledge about the parallel implementation of the micro-simulation, knowledge about the characteristics of the partitioning of the transportation network graph, and knowledge about the interaction of these quantities with the computer system. In particular, we investigate the differences between switched and non-switched topologies, and the effects of 10 Mbit, 100 Mbit, and Gbit Ethernet. As an example, we show that with a common technology – 100 Mbit switched Ethernet – one can run the 20 000-link EMME/2-network for Portland (Oregon) more than 20 times faster than real time on 16 coupled Pentium CPUs.read more
Citations
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References
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TL;DR: This book presents a unified treatment of recently developed techniques and current understanding about solving systems of linear equations and large scale eigenvalue problems on high-performance computers and provides a rapid introduction to the world of vector and parallel processing for these linear algebra applications.