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Mismatched graphics cards and TUFLOW GPU

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We have hit out memory limit with a very large TUFLOW GPU model and were interested in adding another graphics card to our machine.  Does SLI increase the memory available for TUFLOW GPU -  if we add a 6GB card (GTX Titan) to our existing 3GB card (GTX 780) will this mean we have 9GB available or do the cards need to match?



SLI is a method for enabling rendering on multiple cards.  The TUFLOW GPU extension is written with NVIDIA CUDA which does not support the use of the SLI. However, you can run a large model on up to four cards on the same motherboard (data is transferred between cards via the motherboard using the PCI bus).  Essentially the model is split between the cards, so the memory requirement will be shared amongst the cards.  This means that running on multiple GPUs increases the size of the model that can be simulated. 


It is noted that you will need a GPU licence for each GPU card you wish to access.  For example, if you have more than one GPU card and you wish to run the model across both cards, you will need two (free) GPU licences. 


In terms of the cards matching you should be able to use mis-matched cards, however, the model is currently split evenly between the cards.  This means that:

* The slowest card will limit the speed as they have to synchronise every timestep

* The card with the smallest RAM will limit the model size to N x Smallest RAM, where N is the number of cards being used.


If interested, we can looking at allowing the user to define the split between the cards, however, an uneven split may not be ideal.  For example, if you were to run a very large (i.e. a 9GB model) split unevenly across the two cards (3GB 780 and 6GB Titan) for memory reasons the Titan would need to process twice as much of the model as the 780.  Given the Titan and the 780 have similar CUDA core counts (identical, depending on if you are using Ti or black variants), this would mean that the 780 would be waiting for the Titan.



TUFLOW Support Team

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