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> product comparable to NVIDIA 4090 no, they need a product good at training and gpu compute at a reasonable price that product doesn't need to be good at ren

> product comparable to NVIDIA 4090 no, they need a product good at training and gpu compute at a reasonable price that product doesn't need to be good at rendering, ray tracing and similar sure students and some independent contractors probably love getting both a good graphic card and a CUDA card in one and it makes it easier for people to experiment with it but company PCs normally ban playing games on company PCs and the overlap of "needing max GPU compute" and "needing complicated 3D rendering tasks" is limited. through having 1 product instead of two does make supply chain and pricing easier but then 4090 is by now in a price range where students are unlikely to afford it and people will think twice about buying it just to play around with GPU compute. So e.g. the 7900XTX having somewhat comparable GPU compute usability then a 4080 would have been good enough for the non company use case, where a dedicated compute-per-money cheaper GPU compute only card would be preferable for the company use case I think.

nl 4y ago
Long time ML worker here. People work in one of 3 ways: 1) Consumer Nvidia GPU cards on custom PCs 2) Self hosted shared server 3) Cloud infrastructure. There is no "GPU compute only card" that is widely used outside servers. > company PCs normally ban playing games on company PCs and the overlap of "needing max GPU compute" and "needing complicated 3D rendering tasks" is limited. The "don't play games thing" isn't a factor. Most companies just buy a 4090 or whatever, and if they have to tell staff not to play games, they say "don't play games". Fortnight runs just fine on pretty much anything anyway.
- dathinab 4y ago
  my point is a card bought for doing GPU computer not being able to work as a normal graphic card is not a problem I'm aware that currently GPU compute only cards are not widly used outside of the server space. But that's not because people need the consumer GPU features (bedsides video decode) but because the economics of availability and cost lead to consumer GPUs being the best option (and this economic effects don't just apply to customers but also Nvidia itself).

nl 4y ago

Long time ML worker here. People work in one of 3 ways: 1) Consumer Nvidia GPU cards on custom PCs 2) Self hosted shared server 3) Cloud infrastructure. There is no "GPU compute only card" that is widely used outside servers. > company PCs normally ban playing games on company PCs and the overlap of "needing max GPU compute" and "needing complicated 3D rendering tasks" is limited. The "don't play games thing" isn't a factor. Most companies just buy a 4090 or whatever, and if they have to tell staff not to play games, they say "don't play games". Fortnight runs just fine on pretty much anything anyway.

dathinab 4y ago
my point is a card bought for doing GPU computer not being able to work as a normal graphic card is not a problem I'm aware that currently GPU compute only cards are not widly used outside of the server space. But that's not because people need the consumer GPU features (bedsides video decode) but because the economics of availability and cost lead to consumer GPUs being the best option (and this economic effects don't just apply to customers but also Nvidia itself).