AMD Radeon Instinct MI60 and MI50 accelerators announced

[HEXUS]

The world’s first 7nm data centre GPUs deliver “supercharged compute performance”.

Read more.

[darcotech]

How this compares with Vega 64 (in TFLOPS)?
Well Vega 64 has 25.3 TFLOPS (FP16) and this one has 29.5 TFLOPS FP16, so 16% improvement?
or 12.7 TFLOPS (FP32) vs 14.7 for the new one so 16% better

These are not great numbers or I am doing something wrong?

[Tabbykatze]

*cleans self up*

Ahem, that's pretty impressive. Liking the Hive system with the Infinity Fabric ring, would like to know more.

[CAT-THE-FIFTH]

How this compares with Vega 64 (in TFLOPS)?
Well Vega 64 has 25.3 TFLOPS (FP16) and this one has 29.5 TFLOPS FP16, so 16% improvement?
or 12.7 TFLOPS (FP32) vs 14.7 for the new one so 16% better

These are not great numbers or I am doing something wrong?

Think of this card as 14NM Vega but with expanded INT4,INT8 and FP64 throughput and 4 stacks of HBM2 instead of 2:

https://www.anandtech.com/show/13562...ed-by-7nm-vega

With respect to accelerator features, 7nm Vega and the resulting MI60 & MI50 cards differentiates itself from the previous Vega 10-powered MI25 in a few key areas. 7nm Vega brings support for half-rate double precision – up from 1/16th rate – and AMD is supporting new low precision data types as well. These INT8 and INT4 instructions are especially useful for machine learning inferencing, where high precision isn’t necessary, with AMD able to get up to 4x the perf of an FP16/INT16 data type when using the smallest INT4 data type. However it’s not clear from AMD’s presentation how flexible these new data types are – and with what instructions they can be used – which will be important for understanding the full capabilities of the new GPU. All told, AMD is claiming a peak throughput of 7.4 TFLOPS FP64, 14.7 TFLOPS FP32, and 118 TOPS for INT4.

It probably still has 4096 compute cores as before,so most of the FP32 TFLOPs increase is probably through better IPC,higher clockspeeds,etc.

[Ozaron]

IF links on GPU. Come on AMD, roll through the business products, earn some money, and give us a viable IF m-GPU consumer solution on 7nm which smokes RTX for less outlay.

[philehidiot]

I think that the previous gen stuff was already well optimised for FP16 and FP32 throughput so the selling point here is the power consumption and the new feature set as well as the reduced cost of ownership.

There is a big issue about CUDA being like herpes in this arena and so the overall cost of switching is a lot more than just the cost of the hardware. Nvidia also have some other software advantage from what I can tell which is likely a function of market share.

Nvidia have however shot themselves in the foot. Anyone checked out the latest Nvidia drivers T&Cs for consumer GPUs? The Licence Agreement stops them being used in datacentres - something which is open to defintion and could really just say "not for commercial number crunching". This may put off a lot of small players and turn them to AMD. At which case the software development rate will increase massively as it's the smaller companies that actually innovate whereas Nvidia... well... let's just say their development methods are a little old school.

[afiretruck]

IF links on GPU. Come on AMD, roll through the business products, earn some money, and give us a viable IF m-GPU consumer solution on 7nm which smokes RTX for less outlay.

This would be a logical step forward, but it remains to be seen how well gaming performance scales with multiple GPUs on IF.

It would be awesome if they could make a viable MCM gaming GPU, but I just don't think it'll work as well as Zen has for them.