TUFLOW Simulation Speed: Difference between revisions
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* Using Quadtree may decrease RAM requirement as with Quadtree mesh only active code polygon is processed instead of the whole model domain rectangle used for HPC and Classic. Also, judicious refinement and using larger cells in non-focus areas will decrease the number of active cells and therefore the RAM requirement.
* The larger cell size, the less RAM is required. <u>[https://www.youtube.com/watch?v=1jWyIXHR_lM Cell size sensitivity testing]</u> can be carried out to find out the largest cell size without compromising model accuracy.
* Using Sub Grid Sampling (SGS)
<ol>
* Increase your 2D cell size. Thanks to SGS the cell size can typically be increased whilst still achieving a good cell size convergence.
* Review your SGS Sample Frequency in the TLF. Typically, a value of 11 or less is all that is necessary to set the SGS parameterisation to a level that achieves excellent accuracy. If the SGS Sample Frequency is excessively large, test reducing the default value by using either the <font color="blue"><tt>SGS Sample Frequency </tt></font> <font color="red"><tt>==</tt></font><tt> or <font color="blue"><tt>SGS Sample Sample Target Distance </tt></font> <font color="red"><tt>==</tt></font><tt> commands.
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* Inputs might be clipped if their extent is much larger than the code, e.g. grids, material layers and so on. For example if a 100GB DEM is being input to TUFLOW with the majority of the DEM being outside the TUFLOW model, TUFLOW allocates memory to read the entire DEM in for processing. Memory for reading inputs is only used temporarily and is released after the processing of the input, e.g. the DEM.
* Large DEM and material grids can use up a lot of memory during model initialisation as the entire grid is read for processing. Re-tiling the grid into smaller sections will use up less memory as each smaller grid will be processed at the time avoiding high memory peaks.
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