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Check out the docs on TensorFlow GPU usage If you wanted data parallelism where you run a copy of your model on multiple GPUs and split the data between them, you could use the tf.distribute.MirroredStrategy. The tf.distribute.Strategy docs are also a good source to read. Also, you should also profile your application; adding a second GPU has the potential ...


You can get GPUs by selecting N1 VM instance type:


Search for the Deep Learning VM

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