SynapseAI_Core
tensorflow_macos
| SynapseAI_Core | tensorflow_macos | |
|---|---|---|
| 1 | 33 | |
| 25 | 2,887 | |
| - | - | |
| 0.0 | 3.4 | |
| over 1 year ago | almost 3 years ago | |
| C | Shell | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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SynapseAI_Core
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The hunt for the M1’s neural engine
Habana has their own SynapseAI layer that their TF/PyTorch port runs on. Custom ops are supported too, via a compiler targeting the TPCs, using a C language variant.
Oh, and they have an open-source UM software stack for those but it's really not usable. Doesn't allow access to the systolic arrays (MME), only using the TPCs is just _starting_ to enumerate what it doesn't have. (but, it made the Linux kernel maintainers happy so...):
https://github.com/HabanaAI/SynapseAI_Core#limitations (not to be confused with the closed-source SynapseAI)
tensorflow_macos
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Updated Apple Silicon Guide for M2 Pro and M2 Max Chips
https://github.com/apple/tensorflow_macos is no longer needed
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The hunt for the M1’s neural engine
Tensorflow has a CoreML enabled version which run on ANE.
https://github.com/apple/tensorflow_macos
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M1 Mac users
Apple released a guide on how to use the M1's integrated Neural Chip in TensorFlow. Have a look at this Apple documentation page (and maybe also this GitHub that talks about TensorFlow together with Apple's own ML Compute platform).
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MacBook Air or Wait for new potential MacBook Air with M2
Tensorflow does work on Apple Silicon
- Kernels dying when using tensorflow in Jupyter Notebooks.
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Main PyTorch maintainer confirms that work is being done to support Apple Silicon GPU acceleration for the popular machine learning framework.
Apple did some work to optimize tensorflow for M1, can be found here https://github.com/apple/tensorflow_macos It's alpha, but works fine, I tried it
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The M1 Max is the fastest GPU we have ever measured in Affinity Photo benchmark
https://github.com/apple/tensorflow_macos/issues/25
https://forums.macrumors.com/threads/apple-silicon-deep-lear...
It is expected that the M1 Max should have similar performance to a RTX-2080 or Titan X.
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MacBook Pro M1 Pro benchmark
In case anyone is interested, in ran a fairly simple MNIST benchmark (proposed here : https://github.com/apple/tensorflow_macos/issues/25) on my recently acquired M1 Pro MBP (16-core GPU, 16GB RAM).
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Error while installing tensorflow on Mac M1
The only method I know of to download tensorflow on M1 macs is the one documented here: https://github.com/apple/tensorflow_macos
- How exactly does the Neural Engine benefit the consumer?
What are some alternatives?
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
miniforge - A conda-forge distribution.
GibsonEnv - Gibson Environments: Real-World Perception for Embodied Agents
Pointnet_Pointnet2_pytorch - PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
willow - Open source, local, and self-hosted Amazon Echo/Google Home competitive Voice Assistant alternative
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
flamegraph - Easy flamegraphs for Rust projects and everything else, without Perl or pipes <3
Python-docker - Docker Official Image packaging for Python
coremltools - Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.
RAFT
Enzyme - High-performance automatic differentiation of LLVM and MLIR.