Xeon support about tfjs

[gaikwadrahul8]

Hi, @lukemovement

As far I know TensorFlow.js itself currently does not have built-in support for directly utilizing multiple processors or sockets on your machine even when using Xeon processors.

Tensorflow.js can be used in Node.js environments through the @tensorflow/tfjs-node package. However, it doesn't have built-in support for distributed training across multiple processors or sockets within the Node.js runtime itself.
While tfjs-node can leverage multiple CPU cores through Node.js's worker threads for certain operations, it's not designed for full-fledged distributed training like the Python library.

TensorFlow Python Library is recommended approach for complex models or large datasets using the TensorFlow Python library with its distribution strategies is the most effective way to train on multiple processors or GPUs.

It offers robust support for distributed training across various hardware configurations including multi-socket machines.
This approach involves writing your training code in Python and utilizing TensorFlow's distribution APIs like tf.distribute.MirroredStrategy, tf.distribute.MultiWorkerMirroredStrategy or tf.distribute.TPUStrategy. These APIs handle data parallelism and model replication across available devices enabling efficient training on multiple cores.

I hope this information is helpful. Please let me know if you have any further questions.

If I have missed something here please let me know. Thank you for your cooperation and patience.

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[gaikwadrahul8]

Hi, @lukemovement

We haven't got confirmation from your end, May I know your issue got resolved ? if so please feel free to close this issue ? if you've any further questions please feel free to ask us

Thank you for your understanding and patience.

[google-ml-butler]

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