v0.28.0: Keras 2.11+ optimizers, faster reducescatter, fixes for latest TensorFlow, CUDA, NCCL

[maxhgerlach]

Added

• TensorFlow: Added new get_local_and_global_gradients to PartialDistributedGradientTape to retrieve local and non-local gradients separately. (#3859)

Changed

• Improved reducescatter performance by allocating output tensors before enqueuing the operation. (#3824)
• TensorFlow: Ensured that tf.logical_and within allreduce tf.cond runs on CPU. (#3885)
• TensorFlow: Added support for Keras 2.11+ optimizers. (#3860)
• CUDA_VISIBLE_DEVICES environment variable is no longer passed to remote nodes. (#3865)

Fixed

• Fixed build with ROCm. (#3839, #3848)
• Fixed build of Docker image horovod-nvtabular. (#3851)
• Fixed linking recent NCCL by defaulting CUDA runtime library linkage to static and ensuring that weak symbols are overridden. (#3867, #3846)
• Fixed compatibility with TensorFlow 2.12 and recent nightly versions. (#3864, #3894, #3906, #3907)
• Fixed missing arguments of Keras allreduce function. (#3905)
• Updated with_device functions in MXNet and PyTorch to skip unnecessary cudaSetDevice calls. (#3912)

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This discussion was created from the release v0.28.0: Keras 2.11+ optimizers, faster reducescatter, fixes for latest TensorFlow, CUDA, NCCL.