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Working on a build that's part workstation, part gaming rig, and part deep-learning research platform.  I'm trying to eliminate bottlenecks wherever possible to get the most out of my hardware.

I'm planning to put two GTX 1070s, a 10Gb/s networking card, and a NVMe SSD into the PCIe slots on a MSI X99A Gaming Pro Carbon with an Intel i7-6850K (40 PCIe lanes).  

The manual tells me I can get x8/x16/x8/x8 bandwidth out of those slots.  With those limitations, am I better off sticking with 1Gb/s networking and a SATAIII?  

I know I probably won't see much bottleneck while gaming, but what about running optimized deep learning libraries like TensorFlow?  

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For the GPU's you are realy not limited by PCIe bandwith on 8x vs 16x. So it will be fine.

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@Dabasepc

7 minutes ago, gioGats said:

I know I probably won't see much bottleneck while gaming, but what about running optimized deep learning libraries like TensorFlow?

He's not asking about bottlenecks during gaming, he's asking about bottlenecks during deep learning computing.

Unfortunately, I doubt there is anyone on this forum with the experience to help him with deep learning.

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get a single 1080 (Or wait for the 1080ti), i know its less fps per dollar, but i currently run two 980ti's in sli, and trust me the amount of issues i'v had with it just isn't worth it. Like Linus says "Get a single, more powerful gpu over 2 weaker ones". 

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x8/x16/x8/x8 bandwidth

= x8 for 1070

x16 for 1070

x8 for SSD

x8 for 10G NIC

You should be fine, the second 1070 will be ok on a x8 slot and the SSD i think only requires x4. Im pretty sure 10G requires x8

 

^this will be much faster compared to SATA SSD and gigabit networking

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