I'm looking for hardware configuration pieces of advice. I'm having 2 computers, one hyperconvergent server, and one workstation for which I'm planning the hardware. The workstation will be for dev and research. For this one, in a nutshell I'm having 2 hardware possibilities, A and B. I'm having 2 important factors: 1) ethernet speed 2) cuda compute. Other factors: system stability at factory frequencies and overclocked ones, extensibility.
A. Maximus XI Formula Z390, two 2080ti with NVlink, and a connexion to a hyperconvergent server through a 10Gbit (switch and server) ethernet connexion. The Formula had only 5Gbit connexion. The two 2080ti will have 8x and 8x connexion with the motherboard.
B. Maximus XI Hero Z390, two 2080ti with NVlink, one 10Gbit PCIE 4x for the connexion to the 10Gbit server. I think I'll have 8x and 4x connexion with the 2080ti, and 4x for the NIC 10 Gbit.
In a nutshell I have 5Gbit and 32 lines vs 10Gbit and 28 lines.
Questions:
- can you confirm the PCI speeds in the B case, as well as the deep learning hardware requirements ?
- which configuration would you recommend, and why ?
Many thanks.
[0] http://timdettmers.com/2018/12/16/deep-learning-hardware-guide/