3 ms·

I agree that the lack of (official) Navi support is just bad strategy on AMD's part, but I disagree with your numbers. Their goal needs to be performance parit

I agree that the lack of (official) Navi support is just bad strategy on AMD's part, but I disagree with your numbers. Their goal needs to be performance parity or dominance, and then perhaps offer a slight discount. That's how they're succeeding with Zen on CPUs. Offering the kind of steep discount you write about is just bad business.

jamesblonde 7y ago
At the high-end (V100), Nvidia are price gouging, so there is room for a profitable strategy here where AMD significantly undercut Nvidia. My reasoning comes from my belief that AMD will not reach performance parity in the next generation - for deep learning, at least. If the new Arcturus GPU is competitive with Nvidia's new Ampere chip, that would be great. But they won't sell if they are not significantly cheaper. But they won't be significantly cheaper (Arcturus will be the "Enterprise" GPU). However, Big Navi will be much cheaper and can be used in a data center for deep learning without the legal problems that using a 3080Ti would have. I see this as the same "war" between Enterprise hard-disks from 10-15 years ago. Google came out and built their infrastructure on cheap commodity disks. But Dell, HPE and other vendors would not let you use them - they said they were inferior, etc. Commodity GPUs could "democratize" deep learning - ordinary servers could just include a couple of GPUs as a cheap add-on.
- deleted 7y ago
  [deleted]
jchw 7y ago
From a consumer perspective Ryzen certainly feels like a steep discount. Was there a comparable price/perf to 3900X/3950X in the Intel world? Last I looked it seemed like you had to hop ship to Xeon with more expensive boards and really expensive CPUs to get something similar on paper. It looks like the 10980XE is the best answer. But in fairness, I believe it and its pricing was exactly an answer to Ryzen 9.
Dylan16807 7y ago
Per core performance matters on a desktop. Per GPU performance doesn't really matter for doing giant machine learning jobs.
CountSessine 7y ago
x86 CPUs arrive in a software marketplace with tons of compatible software available for them. AMD GPUs are at an enormous disadvantage without support for Cuda or some equivalent, or even some hint to developers about what they should be programming to (is it still OpenCL?) They necessarily have to sell at a huge discount or datacenter providers won’t even pick up the phone when they call.

jamesblonde 7y ago

At the high-end (V100), Nvidia are price gouging, so there is room for a profitable strategy here where AMD significantly undercut Nvidia. My reasoning comes from my belief that AMD will not reach performance parity in the next generation - for deep learning, at least. If the new Arcturus GPU is competitive with Nvidia's new Ampere chip, that would be great. But they won't sell if they are not significantly cheaper. But they won't be significantly cheaper (Arcturus will be the "Enterprise" GPU). However, Big Navi will be much cheaper and can be used in a data center for deep learning without the legal problems that using a 3080Ti would have. I see this as the same "war" between Enterprise hard-disks from 10-15 years ago. Google came out and built their infrastructure on cheap commodity disks. But Dell, HPE and other vendors would not let you use them - they said they were inferior, etc. Commodity GPUs could "democratize" deep learning - ordinary servers could just include a couple of GPUs as a cheap add-on.

deleted 7y ago
[deleted]

jchw 7y ago

From a consumer perspective Ryzen certainly feels like a steep discount. Was there a comparable price/perf to 3900X/3950X in the Intel world? Last I looked it seemed like you had to hop ship to Xeon with more expensive boards and really expensive CPUs to get something similar on paper. It looks like the 10980XE is the best answer. But in fairness, I believe it and its pricing was exactly an answer to Ryzen 9.

Dylan16807 7y ago

Per core performance matters on a desktop. Per GPU performance doesn't really matter for doing giant machine learning jobs.

CountSessine 7y ago

x86 CPUs arrive in a software marketplace with tons of compatible software available for them. AMD GPUs are at an enormous disadvantage without support for Cuda or some equivalent, or even some hint to developers about what they should be programming to (is it still OpenCL?) They necessarily have to sell at a huge discount or datacenter providers won’t even pick up the phone when they call.