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Performance Benchmarks in EMME/2

Performance Benchmarks in EMME/2. Matt Carlson INRO Seminar, Arup, London 2004-09-28. Introduction. A look at some issues regarding performance benchmarks in EMME/2 Show a sample of benchmarks achieved by a range of hardware on the same EMME/2 model Hopefully stimulate some debate!.

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Performance Benchmarks in EMME/2

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  1. Performance Benchmarks in EMME/2 Matt Carlson INRO Seminar, Arup, London 2004-09-28

  2. Introduction • A look at some issues regarding performance benchmarks in EMME/2 • Show a sample of benchmarks achieved by a range of hardware on the same EMME/2 model • Hopefully stimulate some debate!

  3. Purpose (1) Inspired by discussions on the INRO Lists regarding the influence of the following features on performance: • Operating System (Windows, Unix, Linux) • Speed of Processors • Number of Processors • Amount of memory • Disk type (SCSI, RAID Arrays)

  4. Purpose (2) Winnipeg Model: • The Winnipeg model runs ‘too quickly’ to get meaningful benchmarks on current hardware • Some users have recently wondered why there are not more complex elements in the Winnipeg model, such as more complex turn penalties.

  5. Meanwhile, Some Benchmarks

  6. Some Observations (1) • As expected, run times decrease as spec increases • AMD Athlons look promising in terms of performance per clock cycle • Front Side Bus (FSB) appears to be a significant indicator of bottleneck • Athlon 64s should be investigated due to no FSB bottleneck and performance per clock cycle

  7. Some Observations (2) • Generally, ‘more is more’, however: • Hyperthreaded or Multiple Processors do not speed up run times, as expected BUT: • In the real world, the potential to do other things at the same time as a model run IS vastly increased by more physical or virtual processors

  8. Some Observations (3) Rule of Thumb (Assignment) - Zvi Leve, INRO: • Highway assignment is more influenced by processor speed • Transit assignment is more influenced by disk speed

  9. Some Observations (4) Rule of Thumb (Operating Systems) – Mike Florian, INRO: • Linux: faster for disk access for matrix calculations • Windows: faster for assignment

  10. A Larger Demonstration Databank? • A larger model available to all users would provide alarge sample of benchmarks • There would be an opportunity to further showcase the potential of EMME/2 and ENIF, such as: • More complex turn penalties • Crowding on Transit Services • Park & Ride • Combined Assignment-Distribution-Mode Choice techniques such as the Santiago Model (Michael Florian and Shuguang He, 11th EEUG, Madrid, 2002)

  11. An Alternative Idea • A ‘fictitious’ large model could be constructed: • Network Data • Constructed from publicly available GIS data (freely available in the US) • Matrix Data • Purely synthetic data, perhaps constructed using a gravity model

  12. Conclusion • Performance benchmarks could be more easily obtained on a more complex or larger model – Difficult to form conclusions based on a model not publicly available • This could be achieved by: • More complexity for the Winnipeg model • A different, larger model – real or fictitious! • This could have the by-product of showcasing more EMME/2 and ENIF features

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