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CONVOLUTIONAL NEURAL NETWORKS ON HARDWARE ACCELERATORS

机译:硬件加速器上的卷积神经网络

摘要

A hardware acceleration component is provided for implementing a convolutional neural network. The hardware acceleration component includes an array of N rows and M columns of functional units, an array of N input data buffers configured to store input data, and an array of M weights data buffers configured to store weights data. Each of the N input data buffers is coupled to a corresponding one of the N rows of functional units. Each of the M weights data buffers is coupled to a corresponding one of the M columns of functional units. Each functional unit in a row is configured to receive a same set of input data. Each functional unit in a column is configured to receive a same set of weights data from the weights data buffer coupled to the row. Each of the functional units is configured to perform a convolution of the received input data and the received weights data, and the M columns of functional units are configured to provide M planes of output data.
机译:提供了用于实现卷积神经网络的硬件加速组件。硬件加速组件包括:功能单元的N行和M列的阵列;配置为存储输入数据的N个输入数据缓冲器的阵列;以及配置为存储加权数据的M个权重数据缓冲器的阵列。 N个输入数据缓冲器中的每一个耦合到N行功能单元中的相应行。 M个权重数据缓冲器中的每一个耦合到功能单元的M列中的相应列。行中的每个功能单元都配置为接收同一组输入数据。列中的每个功能单元被配置为从耦合至行的权重数据缓冲器接收相同的权重数据集。每个功能单元被配置为执行所接收的输入数据和所接收的权重数据的卷积,并且M列的功能单元被配置为提供M个输出数据平面。

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