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Where specified "fp16", the V100 benchmarks use the code from https://github.com/tensorflow/benchmarks/tree/master/scripts/tf_cnn_benchmarks https://github.com/
by elmarhaussmann 9y ago
Where specified "fp16", the V100 benchmarks use the code from https://github.com/tensorflow/benchmarks/tree/master/scripts/tf_cnn_benchmarks https://github.com/tensorflow/benchmarks/tree/master/scripts... with the flag --use_fp16=true which enables fp16 for some but not all Tensors.
- dkobran 9y agoIt's my understanding that fp16 (available on the previous generation P100) and mixed-precision (major innovation of V100) are different things and the speedup of TensorCores is entirely missing from this benchmark. Unlike the general purpose P100, the TPU is a heavily optimized chip built for Deep Learning, hence it's performance increase. However, the V100 is also heavily optimized for Deep Learning (arguably the first non-GPU chip) from NVIDIA. I'm in no position to defend NVIDIA here haha but it seems like the benchmark misses the point if this is indeed the case.
- elmarhaussmann 9y agoIt was my understanding that the TensorFlow benchmarks do make use of TensorCores on the V100. We'll verify and update accordingly.