6 ms·

Google AI Cloud TPUs

23 points by kundiis 9y ago

aub3bhat 9y ago
180 teraflops per TPU seems great. For reference latest Titan X offers 12 TFLOPs [1] and upcoming AMD card for Deep Learning [2] offers 13 . Though its not clear if TPU performance is calculated at fp16 or fp32[2]. The best GPUs currentLY available on AWS offer mere 2 TFLOPs per GPU [3]. [1] https://blogs.nvidia.com/blog/2017/04/06/titan-xp/ https://blogs.nvidia.com/blog/2017/04/06/titan-xp/ [2] http://pro.radeon.com/en-us/vega-frontier-edition/ http://pro.radeon.com/en-us/vega-frontier-edition/ [3] http://images.nvidia.com/content/pdf/tesla/NVIDIA-Kepler-GK110-GK210-Architecture-Whitepaper.pdf http://images.nvidia.com/content/pdf/tesla/NVIDIA-Kepler-GK1...
- xiphias 9y ago
  https://www.nvidia.com/en-us/data-center/tesla-v100/ https://www.nvidia.com/en-us/data-center/tesla-v100/ Tesla V100 is the thing to be compared with, as it's the first chip optimized for training with the Tensor Core operation (4x4 matrix multiplication and accumulation with mixed fp16/fp32 precision: the inputs to be multiplied are fp16, the accumulation is fp32). V100 performance 100 TFlops this way.
  - aub3bhat 9y ago
    TESLA V100 is apparently ridiculously expensive at 65,0000$. In fact to an extent even NVidia has realized that there is more money in creating a GPU cloud from scratch rather than selling GPUs. I think the net losers are Apple, Amazon/AWS (I believe NVidia is responsible for their lackluster GPU offerings.) & Intel (Who are still hoping for Multi-core to work. And are on track to be disappointed just like they lost mobile market to ARM hoping for Atom to be eventually adopted.)
    - andravin 9y ago
      Hmm, not quite _that_ expensive... you can buy the "DGX Station" with four NVIDIA Tesla V100 GPUs for $69,000. http://wccftech.com/nvidia-volta-tesla-v100-dgx-1-hgx-1-supercomputers/ http://wccftech.com/nvidia-volta-tesla-v100-dgx-1-hgx-1-supe...
- asdf_ 9y ago
  A single chip is only 45 TFLOPS. It is 180 TFLOPs per module (4x TPU chips): https://arstechnica.com/information-technology/2017/05/google-brings-45-teraflops-tensor-flow-processors-to-its-compute-cloud/ https://arstechnica.com/information-technology/2017/05/googl...
infogulch 9y ago
> To solve this problem, we’ve has designed an all-new ML accelerator from scratch I feel like that should be "we have designed" or "we've designed". It seems like someone was in the middle of rewriting it and only got halfway there.

23 points by kundiis 9y ago

180 teraflops per TPU seems great. For reference latest Titan X offers 12 TFLOPs [1] and upcoming AMD card for Deep Learning [2] offers 13 . Though its not clear if TPU performance is calculated at fp16 or fp32[2]. The best GPUs currentLY available on AWS offer mere 2 TFLOPs per GPU [3]. [1] https://blogs.nvidia.com/blog/2017/04/06/titan-xp/ https://blogs.nvidia.com/blog/2017/04/06/titan-xp/ [2] http://pro.radeon.com/en-us/vega-frontier-edition/ http://pro.radeon.com/en-us/vega-frontier-edition/ [3] http://images.nvidia.com/content/pdf/tesla/NVIDIA-Kepler-GK110-GK210-Architecture-Whitepaper.pdf http://images.nvidia.com/content/pdf/tesla/NVIDIA-Kepler-GK1...

xiphias 9y ago
https://www.nvidia.com/en-us/data-center/tesla-v100/ https://www.nvidia.com/en-us/data-center/tesla-v100/ Tesla V100 is the thing to be compared with, as it's the first chip optimized for training with the Tensor Core operation (4x4 matrix multiplication and accumulation with mixed fp16/fp32 precision: the inputs to be multiplied are fp16, the accumulation is fp32). V100 performance 100 TFlops this way.
- aub3bhat 9y ago
  TESLA V100 is apparently ridiculously expensive at 65,0000$. In fact to an extent even NVidia has realized that there is more money in creating a GPU cloud from scratch rather than selling GPUs. I think the net losers are Apple, Amazon/AWS (I believe NVidia is responsible for their lackluster GPU offerings.) & Intel (Who are still hoping for Multi-core to work. And are on track to be disappointed just like they lost mobile market to ARM hoping for Atom to be eventually adopted.)
  - andravin 9y ago
    Hmm, not quite _that_ expensive... you can buy the "DGX Station" with four NVIDIA Tesla V100 GPUs for $69,000. http://wccftech.com/nvidia-volta-tesla-v100-dgx-1-hgx-1-supercomputers/ http://wccftech.com/nvidia-volta-tesla-v100-dgx-1-hgx-1-supe...
asdf_ 9y ago
A single chip is only 45 TFLOPS. It is 180 TFLOPs per module (4x TPU chips): https://arstechnica.com/information-technology/2017/05/google-brings-45-teraflops-tensor-flow-processors-to-its-compute-cloud/ https://arstechnica.com/information-technology/2017/05/googl...

infogulch 9y ago

> To solve this problem, we’ve has designed an all-new ML accelerator from scratch I feel like that should be "we have designed" or "we've designed". It seems like someone was in the middle of rewriting it and only got halfway there.