Training neural network accelerators using mixed precision data formats

BD Rouhani,NA Taesik,ES Chung,D Lo, DC Burger,Rouhani Bita Darvish,Chung Eric S,Lo Daniel, Burger Douglas C

user-5f8cf9244c775ec6fa691c99(2020)

引用 7|浏览57
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摘要
Technology related to training a neural network accelerator using mixed precision data formats is disclosed. In one example of the disclosed technology, a neural network accelerator is configured to accelerate a given layer of a multi-layer neural network. An input tensor for the given layer can be converted from a normal-precision floating-point format to a quantized-precision floating-point format. A tensor operation can be performed using the converted input tensor. A result of the tensor operation can be converted from the block floating-point format to the normal-precision floating-point format. The converted result can be used to generate an output tensor of the layer of the neural network, where the output tensor is in normal-precision floating-point format.
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关键词
Tensor (intrinsic definition),Block (telecommunications),Artificial neural network,Layer (object-oriented design),Computational science,Computer science,Training (meteorology),Mixed precision
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