4 ms·
This is interesting as it seems to compete with their Cloud TPU offering. If benchmarks hold up against this as they looked here: https://www.forbes.com/sites/m
by reilly3000 9y ago
This is interesting as it seems to compete with their Cloud TPU offering. If benchmarks hold up against this as they looked here: https://www.forbes.com/sites/moorinsights/2018/02/13/google-announces-expensive-cloud-tpu-availability/#75ed5416359f https://www.forbes.com/sites/moorinsights/2018/02/13/google-...
... then V100 would win every time. It offers:
- Proven/Familiar platform in CUDA.
- No specific cloud provider lockin
- Similar/Better $/performance on FP16 while maintaining FP24/32 as an option.
What am I missing?
- dgacmu 9y agoThe more recent RiseML benchmkark: (https://blog.riseml.com/comparing-google-tpuv2-against-nvidia-v100-on-resnet-50-c2bbb6a51e5e https://blog.riseml.com/comparing-google-tpuv2-against-nvidi... And the HN discussion of that benchmark, for context: https://news.ycombinator.com/item?id=16931394 https://news.ycombinator.com/item?id=16931394
- dimitry12 9y agoBoth require model tuning before you can get a speed-up from mixed-precision training.