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AMD Radeon Instinct accelerators for deep learning

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Posted · Original PosterOP
21 minutes ago, Notional said:

You don't need permission :)

never mind, thought it was the original from AMD.


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1 hour ago, AresKrieger said:

Well unless their pricing is good the only one with potential is the mi25 as the others fall below pascals Tflop ratings and Nvidia has given them the same deep learning compatibility as the titan xp.

Not everyone needs multiple compute accelerators, and not everyone needs the fastest. One of the biggest barriers to researchers is the entry cost to use these types of platforms, either by buying the assets or buying time on a compute cluster.

 

The MI6 should be a very cheap card, based on Polaris GPU prices and also based on what the market price is now for these specialized accelerators, that will get used in workstations to fine tune code before sending it off to the bigger compute clusters or for smaller tasks/smaller outfits.

 

There are more smaller use cases for compute tasks than there are big ones, not everyone gets multi-million dollar funding grants from governments or fortune 500 companies.

 

Edit:

FYI speaking from working in a university IT department so I hear these complaints first hand 

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11 minutes ago, leadeater said:

Not everyone needs multiple compute accelerators, and not everyone needs the fastest. One of the biggest barriers to researchers is the entry cost to use these types of platforms, either by buying the assets or buying time on a compute cluster.

Thats why I said "unless the price is good", I doubt a server component can beat a consumer one when budget is a factor, though AMD's practices often confuse me so I allow that as a possibility.


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5 minutes ago, AresKrieger said:

Thats why I said "unless the price is good", I doubt a server component can beat a consumer one when budget is a factor, though AMD's practices often confuse me so I allow that as a possibility.

Yea AMD have really struggled to get in to the data center market, hopefully this will be a small step in to it.

 

They need to get their name out there better and get partnerships in things like RoboRace, really looking forward to watching that :). Nvidia powered of course.

https://en.wikipedia.org/wiki/Roborace

http://roborace.com/

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1 hour ago, zMeul said:

P100 you mean?

Sure


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Just keeping this here as a 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Apparently AMD gpus are nearly always more powerful than the Nvidia cards, my gpu computing lecturer tells me. But Nvidia has the market share cuz Cuda and code is easy to write for that and a lot of code already exists 


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4 minutes ago, Sidiox said:

Apparently AMD gpus are nearly always more powerful than the Nvidia cards, my gpu computing lecturer tells me. But Nvidia has the market share cuz Cuda and code is easy to write for that and a lot of code already exists 

Yep pretty much correct, although AMD GPUs having more raw power is a thing it's quite difficult to utilize it for the reasons you mentioned (Cuda vs OpenCL). It's also not so much that Cuda is better but it was first and Nvidia backed it very strongly with good support so is very well embedded in the industry.

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4 hours ago, NumLock21 said:

permission to post this in OP?

shure put it in 

 

edit: nah it not og amd  lol , but you also dont have to ask lol 


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6 hours ago, TheRandomness said:

The highest end Vega 10/11 chip has most likely been used here, and a TDP of <300W indicates maybe a dual GPU solution.. Two 150W Vega 10/11 chips with 'High Bandwidth cache' (probably HBM2) and '2x packed maths' leads to that assumption. So basically a potential Vega 11 chip (unless Vega 10 is really that efficient) with HBM2, and Vega 11 is the codename for the weaker of the two GPUs... I'm probably completely wrong on this :P

Naaa, 2x math means 2 16bit floating point operations at once, this is why they have 25TF. And what 2 GPU solution should run below 300W? This is big Vega.


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17 hours ago, Paytend01 said:

Just curious, what are these cards for? I dont need a long answer just something to know what they are.

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21 hours ago, leadeater said:

Not everyone needs multiple compute accelerators, and not everyone needs the fastest. One of the biggest barriers to researchers is the entry cost to use these types of platforms, either by buying the assets or buying time on a compute cluster.

 

The MI6 should be a very cheap card, based on Polaris GPU prices and also based on what the market price is now for these specialized accelerators, that will get used in workstations to fine tune code before sending it off to the bigger compute clusters or for smaller tasks/smaller outfits.

 

There are more smaller use cases for compute tasks than there are big ones, not everyone gets multi-million dollar funding grants from governments or fortune 500 companies.

 

Edit:

FYI speaking from working in a university IT department so I hear these complaints first hand 

You are absolutely right. but it's cost and bureaucracy. I used my 980 ti at ESA for computing tasks for a couple of days because a new computer takes forever to be cleared. Back in Portugal, my 980 ti had more power than my uni's "supercomputer" that thing was built in the 90s and they couldn'the replace it easily due to the high costs. I am sure this will be a huge boon for them.


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