Flood Modeller-TUFLOW Benchmarking: Difference between revisions
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The results of the benchmarking of model 1 are shown in Table 1. The implicit TUFLOW Classic scheme is comparable to the TUFLOW HPC when it is run on a couple of cores. This is due to the smaller timestep used in the explicit finite volume scheme which uses an adaptive timestep. As the number of cores used increases, the linked Flood Modeller Pro-TUFLOW HPC simulation is quicker, with run times reduced by 42%.
'''Table 1: Runtimes for
{| align="center" class="wikitable"
! style="background-color:#005581; font-weight:bold; color:white;" width=23% | Processor Name
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! style="background-color:#005581; font-weight:bold; color:white;" width=10% | TUFLOW HPC Runtime (s) on 8 Cores
! style="background-color:#005581; font-weight:bold; color:white;" width=10% | TUFLOW HPC Runtime (s) on GPU Card
! style="background-color:#005581; font-weight:bold; color:white;" width=10% | % Speed up between TUFLOW Classic and TUFLOW HPC on a GPU
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|Intel(R) Core(TM) i7-7820x CPU @ 3.60GHz ||NVIDIA GeForce GTX 1080||8||6041||8071||4718||3502||1022||83%
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|Intel(R) Core(TM) i7-7820x CPU @ 3.6 Ghz ||Nvidia GeForce RTX 2080 ti||11||5944||8611||5666||4567||726||88%
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|Intel(R) Core(TM) i7-7700 HQ CPU @ 2.8 Ghz ||Nvidia GeForce GTX 1050||4||6622||10867||7857||N/A||3171||52%
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A GPU card has a significant number of cores within it which can be utilized to undertake the 2D calculations. Running the same model on a GPU card leads to up to an 83% reduction in run times. This means that nearly 8 simulations can be run on a GPU card in the time that a single simulation could be run using TUFLOW classic, highlighting the efficiencies of investing in hardware and also GPU modules.
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