With the recent public release of macOS Monterey, Apple has added Metal support for the PluggableDevice architecture, hence, it is now possible to train TensorFlow models with the dedicated GPU (dGPU) on MacBook Pros and iMacs with ease (sort of). AMD ROCm port) and can purely focus on the communication layers between TensorFlow and device-level operations. More importantly, hardware manufacturers no longer have to fork and implement their own version of TensorFlow (e.g. This allows users to enjoy accelerated training on non-CUDA devices with minimal modification in their code. GPUs, TPUs, NPUs) into the TensorFlow ecosystem. TensorFlow introduced PluggableDevice in mid-2021 which enables hardware manufacturers to seamlessly integrate their accelerators (e.g. Photo by Nikolay Tarashchenko on Unsplash
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