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Radeon Instinct – Optimized Machine and Deep Learning

radeon.com

61–70 of 88 posts

Re: Radeon Instinct – Optimized Machine and Deep Learning

#61

I can't even look at the press picture without remembering that is the exact same metal card slot tab that I had on my IBM PC 35 years ago. They should take a picture of the other end or something.

I wish modern chassis, and indeed, consumer cards, would come with these support brackets.

Re: Radeon Instinct – Optimized Machine and Deep Learning

#62
post #35

What's a good GPU / setup for someone doing deep learning at home? Does anyone have recommendations?

This is the setup I recently made and has been working great so far. However, most of it was purchased on black friday - you can probably replace any of these components with comparable parts that are currently on sale.

https://docs.google.com/spreadsheets/d/1GgTpPbLdRDvw3Mf_d1W0...

Re: Radeon Instinct – Optimized Machine and Deep Learning

#63
post #49
post #21

Earlier quoted context omitted.

I disagree; most people use caffe / keras / theano / tensorflow / etc hiding the cuDNN details so end users won't care much. Offering more performance / shorter training loops is a big deal. Your typical ML learning loop with an expensive human regularly waiting for experiment results shows clear benefits.

The point is that there is no optimized cuDNN equivalent for AMD hardware at this point.

[deleted]

Re: Radeon Instinct – Optimized Machine and Deep Learning

#64
post #49
post #21

Earlier quoted context omitted.

I disagree; most people use caffe / keras / theano / tensorflow / etc hiding the cuDNN details so end users won't care much. Offering more performance / shorter training loops is a big deal. Your typical ML learning loop with an expensive human regularly waiting for experiment results shows clear benefits.

The point is that there is no optimized cuDNN equivalent for AMD hardware at this point.

AMD has built this middleware for all of those applications (keras, tensorflow, caffe, etc) and they show the performance results in their slides.

Re: Radeon Instinct – Optimized Machine and Deep Learning

#65
post #49
post #21

Earlier quoted context omitted.

I disagree; most people use caffe / keras / theano / tensorflow / etc hiding the cuDNN details so end users won't care much. Offering more performance / shorter training loops is a big deal. Your typical ML learning loop with an expensive human regularly waiting for experiment results shows clear benefits.

The point is that there is no optimized cuDNN equivalent for AMD hardware at this point.

[deleted]

Re: Radeon Instinct – Optimized Machine and Deep Learning

#66
post #35

What's a good GPU / setup for someone doing deep learning at home? Does anyone have recommendations?

If you're getting a single video card, or one for calculation and one just to do video, make sure motherboard has 16 PCI-e rel3 lanes into the primary card, people are using z170 and z97. For 4 video cards, you want x99 mobo, newegg does a good job of standardizing different mfrs' specs e.g. http://www.newegg.com/Product/Product.aspx?Item=N82E16813132...

Other concerns: you want a full size cage, with the SSD drives all the way at the top, out of the way of the video cards (the largest Nvidia OEM 3 fan cards are almost 13" long, so there's going to be some Tetris if you want a lot of drives and video cards in there). Cooling critical, stuff the box with RAM and Xeon's or i7s.

This is a good tip: older Xeon servers, dual socket, can support good PCI bandwidth with 2 CPUs: https://news.ycombinator.com/item?id=12606481

Re: Radeon Instinct – Optimized Machine and Deep Learning

#68

Ahh, what exciting times we live in. Just look at the example applications: - autonomous vehicles - autopilot drone - personal assistant - personal robots - ... i know it's optimistic, but it's not science-fiction.

- running out of natural resources

- child slavery to build new iPhones in Africa and China

- killing and burning wildlife to build new farms in Latin America

- still not having any solution for problem of drinkable water in 2/3 of World

What a time to be alive!

Re: Radeon Instinct – Optimized Machine and Deep Learning

#69
post #68

Ahh, what exciting times we live in. Just look at the example applications: - autonomous vehicles - autopilot drone - personal assistant - personal robots - ... i know it's optimistic, but it's not science-fiction.

- running out of natural resources - child slavery to build new iPhones in Africa and China - killing and burning wildlife to build new farms in Latin America - still not having any solution for problem of drinkable water in 2/3 of World What a time to be alive!

Yes, the world is not perfect by any stretch of the imagination. Lots of things to be improved. If you could choose another time to live in, when would it be?

Re: Radeon Instinct – Optimized Machine and Deep Learning

#70
post #69
post #68

Earlier quoted context omitted.

- running out of natural resources - child slavery to build new iPhones in Africa and China - killing and burning wildlife to build new farms in Latin America - still not having any solution for problem of drinkable water in 2/3 of World What a time to be alive!

Yes, the world is not perfect by any stretch of the imagination. Lots of things to be improved. If you could choose another time to live in, when would it be?

Wow, that's a great question. I can't decide if it would be in 20 years or 40 years ago. Just to be part or witness of creating Internet as we know it or as we will see it! When some of the above problems don't exist any more because of technological advancement and some worsen because of the very same reason, but we no longer see them, because no one is looking at the wild parts of the world.
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