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ML Compute is GPU-accelerated on both Intel and M1, as well as natively supporting each CPU's respective vector instructions via the BNNS API in Accelerate.fram
by Reason077 6y ago
ML Compute is GPU-accelerated on both Intel and M1, as well as natively supporting each CPU's respective vector instructions via the BNNS API in Accelerate.framework:
https://developer.apple.com/documentation/mlcompute https://developer.apple.com/documentation/mlcompute
I don't think Apple have stated whether MLCompute also utilises the M1's "Neural Engine", but geohot did manage to target it in tinygrad:
https://github.com/geohot/tinygrad/tree/master/ane https://github.com/geohot/tinygrad/tree/master/ane
- 0x008 6y agoBut that’s a CoreML model so that might not be possible with regular tensor flow models?
- georgehotz 6y agoThe MLCompute API supports three options "CPU", "GPU" or "any", which is GPU sometimes and CPU sometimes. Not the neural engine. There's some MLComputeANE code in the framework, but afaik there's no way to use it yet. Also, from looking at it, I believe the neural engine only supports float16.
- zahlex 6y agoAs far as my understanding goes, ML Compute is for training models via CPU or GPU and not ever supposed to use the ANE: https://developer.apple.com/documentation/mlcompute https://developer.apple.com/documentation/mlcompute Core ML on the other hand is designed to use trained models and runs automatically on CPU, GPU or ANE depending on what fits the currently executed model layer best: https://developer.apple.com/documentation/coreml https://developer.apple.com/documentation/coreml
- iopuy 6y agoHave you tried using Zimmer?