New GPU for Deep Learning on old machine

ricopan

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Aug 10, 2017
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I want to experiment with DL (specifically TensorFlow) to see if I can gain any traction on some computational biology problems. At first I'm hoping to use one of my current machines -- but they have PCI 2.0, and so I assume critically limited long term. No point in getting a card that will be limited by my PCI bottleneck, but I really have no idea how or with what card that will occur. If I see promise I would get a newer machine, but that would probably be 6 months or so from now.

My datasets, once prepped into features, aren't huge by today's standards -- eg 50K samples, maybe 1000 features. Might do useful experiments with smaller sets. I'm guessing the size of the datasets are the critical issue for slow PCI, but I don't know that.

Card could go in either of these machines, if compatible:

1) Supermicro X8DAH+ mobo, dual Xeon 5690, 192 GB RAM. My primary workstation that I do feature prep on, fair bit of parallel code, and currently run SVM machine learning.

2) Dell Precision T7500, dual Xeon 5650, 96 GB RAM. Mostly a database server, probably best here.

I've been looking at the GTX 1000 line (upper limit would be 1070 at this point) if PCI bus wasn't a deal breaker, but there may be something else I don't know about that would suggest an older card. At least a CUDA compatibility of 3.5 needed.

Thanks in advance for any recommendations or thoughts.

UPDATE: FWI, Currently Supermicro has a GeForce GT 220 and the Dell an AMD Bonaire XTX Radeon R7 260X or 360(?)
 

salerhino

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"I've been looking at the GTX 1000 line (upper limit would be 1070 at this point) if PCI bus wasn't a deal breaker, but there may be something else I don't know about that would suggest an older card. At least a CUDA compatibility of 3.5 needed."
Possible problem could be not having UEFI BIOS on older machines.
That is why I wouldn't suggest you using the 1000 series GPUs.
 

ricopan

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Aug 10, 2017
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Thanks, I'll into UEFI requirements with different GPUS. From a quick google, looks like it is debatable whether the 1000 series GPUs require UEFI and in general, one doesn't know whether old mobo + new GPU will work until tried. New info for me. Will keep looking for a bit.

If I decide against the 1000 series, any thoughts about the best older Nividia cards?
 

ricopan

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Aug 10, 2017
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Quiet doesn't matter, as the Supermicro board is loud enough to annoy anyone in the room anyway. Right, don't use the current GPU for anything but running Ubuntu desktop and an occasional graph, no gaming, but CUDA is a different story. Would like powerful within the limits of the PCI 2.0.

I would just stick with the Geforce GT 220 but the newer CUDA interfaces (eg TensorFlow) require a compatibility of > 3.5, and I think that old card is 1.2, so can't use the libraries at all except in CPU only mode. Thinking GTX 750 Ti, but again, I see conflicting advice regarding whether UEFI needed for this GPU as well.
 

ricopan

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Aug 10, 2017
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Ok, thanks for the advice.
I'll leave this thread open for a little while in case someone who's done just this stumbles by. Otherwise I'll get the 750Ti.
Yeah, NVIDIA seems to have cornered the CUDA market. The speed boost on some domains is apparently remarkable -- even that older card likely 100x over what I can do even with optimized linear algebra libraries and dual CPUs that were great, well, 5 years ago(!). Of course that means we expect to work on bigger problems...
 

ricopan

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Aug 10, 2017
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If all else fails, look at the manufacturer -- according to Dell, the Geforce 1000 series is compatible with the T7500, though whether it is worth it with PCI 2.0 for Deep Learning is still an open question.