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Delivering an incremental speed boost vs nvidia chips seems like a tough way to win. Even if they can be 2x faster, people will still stick to cuda. They eith

Delivering an incremental speed boost vs nvidia chips seems like a tough way to win. Even if they can be 2x faster, people will still stick to cuda. They either have to be 5-10x faster or find a new market. Definitely possible. Would be pretty embarrassing for nvidia if that happened.

ur-whale 8y ago
A large part of accelerating AI loads in H/w lives in the software stack, not in the chip itself. If people can run TensorFlow loads directly on the chip via qroq's s/w stack, who cares about Cuda. That will be the differentiator for this company, not their h/w manufacturing prowess.
- sanxiyn 8y ago
  Apparently they have a person who was involved in TensorFlow TPU port.
sytelus 8y ago
Nope. People aren't addicted to CUDA. In fact its hell to work with CUDA. Just to even download the binaries you have to go through registration process, docs are shit and version dependency is nightmare. The only reason CUDA is in use is because in old days it was the only game in town and Caffee framework integrated it from some very early code researchers wrote. Then people kept using that baseline code all the way to TF and PyTorch. Thanks to TPU, frameworks are already being to forced to be agnostic and new alternatives will be much easier to integrate. If Groq chip delivers what its promising then you can bet that it would be integrated within few months in most frameworks and people will soon forget about CUDA. Most people who work with deep learning neither write code specific to cuda nor do they care that cuda is being used under the hood as long as things are being massively parallelized.
- sanxiyn 8y ago
  > If Groq chip delivers what its promising then you can bet that it would be integrated within few months in most frameworks and people will soon forget about CUDA. Groq seems careful not to promise any price point. Even if Groq delivers every promise, if it's expensive its adoption will be chancy.
sanxiyn 8y ago
Nope, as long as TensorFlow works, a lot of people won't care about CUDA.

ur-whale 8y ago

A large part of accelerating AI loads in H/w lives in the software stack, not in the chip itself. If people can run TensorFlow loads directly on the chip via qroq's s/w stack, who cares about Cuda. That will be the differentiator for this company, not their h/w manufacturing prowess.

sanxiyn 8y ago
Apparently they have a person who was involved in TensorFlow TPU port.

sytelus 8y ago

Nope. People aren't addicted to CUDA. In fact its hell to work with CUDA. Just to even download the binaries you have to go through registration process, docs are shit and version dependency is nightmare. The only reason CUDA is in use is because in old days it was the only game in town and Caffee framework integrated it from some very early code researchers wrote. Then people kept using that baseline code all the way to TF and PyTorch. Thanks to TPU, frameworks are already being to forced to be agnostic and new alternatives will be much easier to integrate. If Groq chip delivers what its promising then you can bet that it would be integrated within few months in most frameworks and people will soon forget about CUDA. Most people who work with deep learning neither write code specific to cuda nor do they care that cuda is being used under the hood as long as things are being massively parallelized.

sanxiyn 8y ago
> If Groq chip delivers what its promising then you can bet that it would be integrated within few months in most frameworks and people will soon forget about CUDA. Groq seems careful not to promise any price point. Even if Groq delivers every promise, if it's expensive its adoption will be chancy.

sanxiyn 8y ago

Nope, as long as TensorFlow works, a lot of people won't care about CUDA.