[BrailleHunting]

The P100 has much better double-precision performance, but it's single-precision perf doesn't justify the cost in most instances.

The DGX1 (w 8 P100's) is another example of an overpriced, turnkey money extraction "solution."

Also worth noting it's hard to get a Ti non-founder edition, which has a hefty premium on it for the privilege of being first. The regular 1080 non-FE cards are probably the best bang/buck right now.

Folking doing ML/AI/DL, or any HPC really, gotta profile their apps to find bottlenecks and root out resource waste: single prec math? ram? algorithm complexity? storage iops? network latency? etc. because throwing money at a problem is no substitute for having a clue how to use money, time and electricity wisely.

[llukas]

Compared to what it can replace DGX-1 is not overpriced in any way.

Feel free to invest your time and money into building and debugging issues on your own system. Companies which pay big $$$ to their data scientists have different incentives than regular users - you do not want to waste time of your expensive staff on chasing hardware/software issues.

[Roritharr]

129000$ for the DGX-1, for anyone interested.

Saves you debugging your way to a workable 8*1080ti, when you look at it from this angle. Not sure if being able to swap out the cards is what makes building them yourself worth it in addition to the cost saving.

[modeless]

P100 has double rate FP16 which makes it twice as fast, so make that 16x 1080Ti. Also those won't fit into one machine, so now you're building a cluster, and what are you going to use for the interconnect? You won't get linear scaling, so make that more like 24x 1080Tis plus extra development effort for scaling on a cluster, if your problem even scales that way. Now account for the power usage...

[llukas]

What interconnect do you have between those 8*1080ti? If your problem doesn't require communication then it may make sense.

If you require non-trivial communication no PCIe setup would beat NVLink communication bandwidth on DGX-1.

[jacquesm]

> 129000$ for the DGX-1, for anyone interested.

If you are allowed to buy one. Nvidia doesn't have nearly enough chips to meet demand, the bulk of their production has been earmarked for quite a while ahead, what little is left over and makes it into the DGX-1 is sold to very few hand picked customers.

[ansible]

There is also the unified memory on the DGX-1, which is supposed to make streaming data to/from the GPUs a lot more efficient, as well as enable much larger data sets.

[cameldrv]

The P100 also has 2x the performance on FP16 and NVLink, which is about 10x faster than PCIe.