[migmolper]

Good afternoon,


We are a research group and we are assembling a workstation for SPH calculations.

Our idea is to put two graphic cards NVIDIA RTX 2080 ti in order to do ours GPU calculus. Our CPU is a i7 8700-k. It is possible that this configuration generate a bottle neck when both GPU are working simultaneisly? If the answer it is yes, wich CPU would we buy?



Cheers

[Simbelmynë]

It should probably depend on the SPH implementation. There are many algorithms that need almost no CPU interaction. Mining is one such example, where you can use as many GPUs as you have PCIe slots on your motherboard, while at the same time have the cheapest possible CPU.


This may or may not be the case for your SPH implementation. My gut feeling though is that if you have to worry about the 8700k being a bottle neck, then the implementation is not very well suited for a dual GPU setup. What other CPU except perhaps 9900k could possibly be better? (I am assuming that you will not do any actual calculations on the CPU, only use it for non-GPU bound activities)

[flotus1]

Depending on the implementation of your code, there are 2 potential bottlenecks caused by the choice of CPU.
1) as Simbelmynë said: not enough CPU performance. This includes both the CPU itself being too slow in parallel workloads due to its 6 cores and lacking memory bandwidth with only 2 memory channels.
2) PCIe transfer bottleneck: The CPU only has 16 PCIe lanes for GPUs. So with 2 of them, each GPU is connected by 8 lanes instead of the full 16 lanes. Again, it highly depends on the implementation of your code if this will cause an actual bottleneck.