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r2.9 cherry-pick: Update RELEASE.md #56039

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merged 3 commits into from May 9, 2022
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r2.9 cherry-pick: Update RELEASE.md #56039

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* `tf.experimental.dtensor`: Added DTensor, an extension to TensorFlow for large-scale modeling with minimal changes to user code. You are welcome to try it out, though be aware that the DTensor API is experimental and up-to backward-incompatible changes. DTensor and Keras integration is published under `tf.keras.dtensor` in this release (refer to the `tf.keras` entry). The tutoral and guide for DTensor will be published on https://www.tensorflow.org/. Please stay tuned.

* [oneDNN optimizations](https://medium.com/intel-analytics-software/leverage-intel-deep-learning-optimizations-in-tensorflow-129faa80ee07):
* oneDNN optimizations are enabled by default in Linux x86 packages on CPUs with neural-network-focused hardware features such as AVX512_VNNI, AVX512_BF16, AMX, etc, which are found on [Intel Cascade Lake](https://www.intel.com/content/www/us/en/products/platforms/details/cascade-lake.html) and newer CPUs.
* For Linux x86 packages that are run on older CPUs and Windows x86 packages, oneDNN optimizations are disabled by default. They can be turned on by setting the environment variable `TF_ENABLE_ONEDNN_OPTS=1` before running TensorFlow.
* These optimizations can yield slightly different numerical results from when they are off due to floating-point round-off errors from different computation approaches and orders. To turn oneDNN optimizations off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0` before running TensorFlow.
* To verify that the optimizations are on, look for a message beginning with “oneDNN custom operations are on” in the log. If the message is not there, it means oneDNN optimizations are off.
* For more details on how oneDNN optimizations work, please refer to TensorFlow [RFC #400](https://github.com/tensorflow/community/blob/master/rfcs/20210930-enable-onednn-ops.md).
* [oneDNN CPU custom operations and performance optimizations](https://github.com/tensorflow/community/blob/master/rfcs/20210930-enable-onednn-ops.md) are available in Linux x86, Windows x86, and Linux aarch64 packages.
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* **Linux and Windows x86 packages:**
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* **Linux x86:** oneDNN custom ops are *enabled by default* on CPUs with neural-network-focused hardware features such as AVX512_VNNI, AVX512_BF16, AMX, etc., which are found on [Intel Cascade Lake](https://www.intel.com/content/www/us/en/products/platforms/details/cascade-lake.html) and newer CPUs.
* [Example performance speedups.](https://medium.com/intel-analytics-software/leverage-intel-deep-learning-optimizations-in-tensorflow-129faa80ee07)
* For older CPUs, oneDNN custom ops are disabled by default.
* **Windows x86:** oneDNN custom ops are disabled by default.
* These custom ops can yield slightly different numerical results from when they are off due to floating-point round-off errors from different computation approaches and orders.
* **Linux aach64 (`--config=mkl_aarch64`) package:**
* Experimental oneDNN custom ops are disabled by default.
* If you experience issues with oneDNN custom ops on, we recommend turning them off.
* To explicitly enable or disable oneDNN custom ops and optimizations, set the environment variable `TF_ENABLE_ONEDNN_OPTS` to `1` (enable) or `0` (disable) before running TensorFlow. (The variable is checked during `import tensorflow`.) To fall back to default settings, unset the environment variable.
* To verify that the custom ops are on, look for a message with *"oneDNN custom operations are on"* in the log. If the message is not there, it means they are off.
* This is not to be confused with the log message beginning with *"This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)..."*. The message can be printed regardless of whether oneDNN custom ops are enabled, because TensorFlow Linux x86's default matrix multiplication and convolution ops also call oneDNN matrix multiplication routines as a basic building block. (See Figure 2 of [TensorFlow RFC #400](https://github.com/tensorflow/community/blob/master/rfcs/20210930-enable-onednn-ops.md).)
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# Bug Fixes and Other Changes

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