ML Compute on M1 Macs
Until now, TensorFlow has only utilized the CPU for training on Mac. The new tensorflow_macos fork of TensorFlow 2.4 leverages ML Compute to enable machine learning libraries to take full advantage of not only the CPU, but also the GPU in both M1- and Intel-powered Macs for dramatically faster training performance.
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Performance benchmarks for Mac-optimized TensorFlow training show significant speedups for common models across M1- and Intel-powered Macs when leveraging the GPU for training. For example, TensorFlow users can now get up to 7x faster training on the new 13-inch MacBook Pro with M1[…]
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No one doing deep learning for anything more than a hobby is using the Intel CPU in their laptop.
I know this is too much to expect from something that has been cleared by Apple's marketing department, but I would love to see the M1 benchmarked against the kind of commodity discrete GPUs in a p2large EC2. These are the mainstream of what is actually used to train non-trivial neural networks.
I bet the M1 actually does OK up against a p2large! But it probably doesn't win, so we have to have our intelligence insulted with a set of useless results.
