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yes. There will be adapters from dual 8pin to 12pin.

Also, custom designs are supposed to ship with dual 8pins on the card instead. 

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Yes, adapters are included. From the other thread:

1 hour ago, Exty said:

to everyone who is wondering what cables you will need , it has been confirmed that it will come with an adapter and it will need 2 8 pin connectors

 

Annotation 2020-09-01 135833.png

 

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3 minutes ago, starsarethebest9 said:

So I am thinking getting the RTX 3080 i have the Corsair AX1000 will that power supply work with the RTX 12 pin that is required? 

The 3080 should ship with an adapter in the box. 

Corsair will probably manufacture a new lead for their PSU's that you might be able to purchase at some point.

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Ah good, strongly thinking of a 3070 here.  Be more than enough performance for me at 1440p 165hz. 

 

Main concern was my EVGA G3 650.

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21 minutes ago, decemvre said:

No NVLink for 3080 founders edition? Is that correct? Could other manufacturers still provide NVLink?

Nope, only 3090. Multi-GPU for gaming is dead.

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3 minutes ago, decemvre said:

Was planning on using it for deep learning workstations. Guess I'll have to go with multi 3090 then.

Ah I see. Well, that use case is what the 3090 is aimed for as a Titan-esque card from my understanding (although I understand the massive price gap makes it less attractive perhaps).

Crystal: CPU: i7 7700K | Motherboard: Asus ROG Strix Z270F | RAM: GSkill 16 GB@3200MHz | GPU: Nvidia GTX 1080 Ti FE | Case: Corsair Crystal 570X (black) | PSU: EVGA Supernova G2 1000W | Monitor: Asus VG248QE 24"

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15 hours ago, decemvre said:

Was planning on using it for deep learning workstations. Guess I'll have to go with multi 3090 then.

You don't need nvlink to do multi gpu deep learning.

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16 minutes ago, decemvre said:

How do you pool memory otherwise?

Depending on what you're doing, data-parallelism is pretty painless and achieves pretty similar results. Otherwise, there's no actual "memory pooling" happening. Trying to fit a batch size bigger than a single card allows would lead to a OOM error. You can read about it here (take a look at the comments too!).

 

You might also want to wait for the RDNA2 releases to see if nvidia releases a Super/Ti variant, maybe those will have one or two nvlink bricks, along with more vram.

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1 minute ago, igormp said:

Depending on what you're doing, data-parallelism is pretty painless and achieves pretty similar results. Otherwise, there's no actual "memory pooling" happening. Trying to fit a batch size bigger than a single card allows would lead to a OOM error. You can read about it here (take a look at the comments too!).

 

You might also want to wait for the RDNA2 releases to see if nvidia releases a Super/Ti variant, maybe those will have one or two nvlink bricks, along with more vram.

I may not have the luxury to wait as the investment has a given timeline. But thank you kindly for the link I am reading it now.

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