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Available in orders of up to 10,000 GPUs today - no shortage More than 10x cheaper than allocating machines on a tier 1 cloud - AWS, Azure, GCP, Oracle, etc M

Available in orders of up to 10,000 GPUs today - no shortage More than 10x cheaper than allocating machines on a tier 1 cloud - AWS, Azure, GCP, Oracle, etc More memory - 128GB HBM per GPU - means bigger models fit for training/inference without the nightmare of model parallelism over MPI/infiniband/etc Longer term - finetuning optimizations

mardifoufs 3y ago
Ah! The memory sounds interesting. How would that compare to similar Nvidia hardware w.r.t cost assuming the hardware was available? Does AMD provide something similar to nvlink, and even libraries like cudnn? Also, last I checked none of the public clouds offered any of the latest gens MI GPUs, so I wasn't aware that it had good availability! Azure had a preview but I'll look more into it now. Thank you for your answer btw!
- gdiamos 3y ago
  Yeah getting around the no public cloud thing was really annoying. We had to build our own datacenter. On the plus side, it was drastically cheaper and now we can just slot in machines. I would prefer that a tier 1 cloud made MI GPUs available though. It would make it so much more accessible.
  - bitcoinmoney 3y ago
    Are you releasing your software stack to the public?
    - gdiamos 3y ago
      It's available now with an enterprise license, because we validate that it is running correctly on a system we help configure. We will open source pieces of it over time. Our strategy is open source functional core. Eventually we will have an open source dev environment that runs on a personal scale computer. We already have this for some configurations, but we don't do enough testing to ensure perf/functionality on many different systems. We are mainly bottlenecked by resources as a 12-person startup. We have released some open source SDKs here: https://github.com/orgs/lamini-ai https://github.com/orgs/lamini-ai This class has some training recipe code: https://www.deeplearning.ai/short-courses/finetuning-large-language-models/ https://www.deeplearning.ai/short-courses/finetuning-large-l... One thing I'd like to push back to open source is the scale out AMD SLURM support.
- gdiamos 3y ago
  See the memory size comparison (GB) in this table: https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_processing_units#Tesla https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_proces...
  - QuarterReptile 3y ago
    It blows my mind that A100 and H100 are each safely below 1000W power draw.

mardifoufs 3y ago

Ah! The memory sounds interesting. How would that compare to similar Nvidia hardware w.r.t cost assuming the hardware was available? Does AMD provide something similar to nvlink, and even libraries like cudnn? Also, last I checked none of the public clouds offered any of the latest gens MI GPUs, so I wasn't aware that it had good availability! Azure had a preview but I'll look more into it now. Thank you for your answer btw!

gdiamos 3y ago
Yeah getting around the no public cloud thing was really annoying. We had to build our own datacenter. On the plus side, it was drastically cheaper and now we can just slot in machines. I would prefer that a tier 1 cloud made MI GPUs available though. It would make it so much more accessible.
- bitcoinmoney 3y ago
  Are you releasing your software stack to the public?
  - gdiamos 3y ago
    It's available now with an enterprise license, because we validate that it is running correctly on a system we help configure. We will open source pieces of it over time. Our strategy is open source functional core. Eventually we will have an open source dev environment that runs on a personal scale computer. We already have this for some configurations, but we don't do enough testing to ensure perf/functionality on many different systems. We are mainly bottlenecked by resources as a 12-person startup. We have released some open source SDKs here: https://github.com/orgs/lamini-ai https://github.com/orgs/lamini-ai This class has some training recipe code: https://www.deeplearning.ai/short-courses/finetuning-large-language-models/ https://www.deeplearning.ai/short-courses/finetuning-large-l... One thing I'd like to push back to open source is the scale out AMD SLURM support.
gdiamos 3y ago
See the memory size comparison (GB) in this table: https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_processing_units#Tesla https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_proces...
- QuarterReptile 3y ago
  It blows my mind that A100 and H100 are each safely below 1000W power draw.