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Comment by NegatioN | Hacker News Reader

I agree with your sentiment completely, it would be a win/win to be able to use TF and other similar frameworks on AMD hardware. But I would also like to point out that using online compute power for this should be possible even at a student budget (assuming you're in the west).

Amazon and Google have good options for those who can't afford dishing out $650x4 for a decent ML setup.

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Online computing power is not the same as your own - it's like taxi vs your own car. You can't do what you want when you want. Turned on your Amazon machine? No sleep till you fix the bugs and load all GPUs :) Every "downtime" costs. I, personally, find it very disturbing and despite the fact my employer pays for my Amazon time I often prefer my laptop with GeForce 840M :)

Agreed, as well as the evolving nontrivial hunt for cost reductions e.g. "Just use spot instances in US west 1 on weekends", stuff like that.

A pascal GPU and older CPU that takes at least 32GB RAM is a decent combination. I'm looking to upgrade to an older Xeon and a 1080 (price should be dropping any week now...) or 1080 Ti. Even the Sandy/ivy bridge i7's have not too bad results on most benchmarks: http://www.anandtech.com/show/9483/intel-skylake-review-6700...

> it would be a win/win to be able to use TF and other similar frameworks on AMD hardware.

Agree. Competition is good for the consumer. A cuDNN port that runs on AMD hardware should be available this year:

http://www.anandtech.com/show/10905/amd-announces-radeon-ins...

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