Difference between revisions of "Flood Modeller-TUFLOW Benchmarking"
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==Flood Modeller-TUFLOW Benchmarking== | ==Flood Modeller-TUFLOW Benchmarking== | ||
− | + | A common query is what is the speed up of running simulations utilising TUFLOW HPC and GPU technology when TUFLOW models are linked to external 1D schemes such as Flood Modeller Pro. Therefore, some benchmarking of linked Flood Modeller Pro-TUFLOW models have been undertaken to demonstrate the show the impact of running the linked models with the TUFLOW HPC solver on a single processor, multiple cores as well as utilizing Nvidia GPU cards. The outputs from these tests have been compared against the TUFLOW Classic engine which due the various inter-dependencies in the matrix solver cannot distribute calculations across multiple processors. | |
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The benchmark simulations have been undertaken internally and unfortunately due to model licencing issues cannot be supplied externally. The models are real world example models typical of the kind that Flood Modeller Pro and TUFLOW are used on. | The benchmark simulations have been undertaken internally and unfortunately due to model licencing issues cannot be supplied externally. The models are real world example models typical of the kind that Flood Modeller Pro and TUFLOW are used on. | ||
Revision as of 20:52, 5 April 2019
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Flood Modeller-TUFLOW Benchmarking
Introduction
The fixed grid TUFLOW software is available in 2 solvers, an implicit finite-difference solver which is now branded as TUFLOW Classic, and an explicit finite volume engine called TUFLOW HPC which stands for Heavily Parallelised Compute. The solution scheme for TUFLOW HPC has highly independent calculations which can be parallelised and when run over multiple processors or on a GPU provides a significant reduction in run times. The following wiki post highlights the potential speed up that could be achieved with utilisation of the TUFLOW HPC engine using GPU card technology:-
The benchmark models in these tests are 2D only models or 1D-2D models which utilise TUFLOW 1D ESTRY engine. The speed up is due to 2D calculations being distributed across multiple processors and undertaken in parallel. The impact of the parallel processing is also seen in integrated 1D-2D models. As well as its own 1D engine which allows the modelling and integration of pipe network models and river models together with a 2D domain, TUFLOW can also be integrated with a range of other 1-Dimensional software including Flood Modeller Pro amongst others.
Flood Modeller-TUFLOW Benchmarking
A common query is what is the speed up of running simulations utilising TUFLOW HPC and GPU technology when TUFLOW models are linked to external 1D schemes such as Flood Modeller Pro. Therefore, some benchmarking of linked Flood Modeller Pro-TUFLOW models have been undertaken to demonstrate the show the impact of running the linked models with the TUFLOW HPC solver on a single processor, multiple cores as well as utilizing Nvidia GPU cards. The outputs from these tests have been compared against the TUFLOW Classic engine which due the various inter-dependencies in the matrix solver cannot distribute calculations across multiple processors.
The benchmark simulations have been undertaken internally and unfortunately due to model licencing issues cannot be supplied externally. The models are real world example models typical of the kind that Flood Modeller Pro and TUFLOW are used on.
Model 1
The first simulated model was a 287 node Flood Modeller network coupled with a TUFLOW model comprising of 297,746 cells with a 2m resolution. The input boundaries corresponded to a 100 year return period. The model was run for 10 hours. The models were run on a number of different setups and run for 4 scenarios. The 4 scenarios are as follows:
- TUFLOW Classic with a fixed timestep of 0.5 seconds
- TUFLOW HPC run on 2 Cores
- TUFLOW HPC run on 4 cores
- TUFLOW HPC run on 8 cores
- TUFLOW HPC run on a Nvidia GPU card. The Nvidia GPU card varies depending on the machine being used.
The TUFLOW version used for the simulations was the 2018-03-AC release and Flood Modeller 4.4.
The results of the benchmarking of model 1 are shown in Table x. 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%. A GPU card is essentially made up of a number of cores 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.
Model 2
Model 2 contains 228 Flood Modeller Pro nodes, a 5m resolution TUFLOW grid with a total of 570,214 cells. The model was run for 26 hours of model time with a 100 year boundary condition. The TUFLOW Classic model was run with a 1.25 second timestep.
The impact of the TUFLOW HPC engine on a GPU card can be seen across a number of models as shown above.
The above simulation times were when running the models using Flood Modeller 4.4. Flood Modeller 4.4 although supporting TUFLOW HPC and GPU cards does not support the concurrent simulation of Flood Modeller Pro, TUFLOW HPC and TUFLOW’s 1D scheme, ESTRY. The ability to run all three simultaneously is available in Flood Modeller 4.5 which has been provided in a beta testing phase for this analysis. The ability to run Flood modeller Pro, TUFLOW 2D and TUFLOW 1D components allows the running of a fully integrated drainage models comprising open channels, 2D floodplains as well as 1-Dimensional pipe networks and their interaction with the surface as represented by the 2D domain. The above same models were run with Flood Modeller 4.5. The model results are presented in table x.
A further model was run which comprised of a Flood Modeller network together with a 2D domain and a X node ESTRY model.
Clearly demonstrates how TUFLOW HPC can leverage the technological improvements that are being made in terms of GPU cards and technology changes.