Analysis of information sources in references of the Wikipedia article "شتابدهنده هوش مصنوعی" in Persian language version.
This page lists the TensorFlow Python APIs and graph operators available on Cloud TPU.
{{cite journal}}: Cite journal requires |journal= (help)For the Cloud TPU, Google recommended we use the bfloat16 implementation from the official TPU repository with TensorFlow 1.7.0. Both the TPU and GPU implementations make use of mixed-precision computation on the respective architecture and store most tensors with half-precision.
Intel said that the NNP-L1000 would also support bfloat16, a numerical format that’s being adopted by all the ML industry players for neural networks. The company will also support bfloat16 in its FPGAs, Xeons, and other ML products. The Nervana NNP-L1000 is scheduled for release in 2019.
Intel plans to support this format across all their AI products, including the Xeon and FPGA lines
...Intel will be extending bfloat16 support across our AI product lines, including Intel Xeon processors and Intel FPGAs.
For the Cloud TPU, Google recommended we use the bfloat16 implementation from the official TPU repository with TensorFlow 1.7.0. Both the TPU and GPU implementations make use of mixed-precision computation on the respective architecture and store most tensors with half-precision.
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