Hybrid non-uniform convolution transform engine for deep learning applications
Abstract:
A system performs convolution operations based on an analysis of the input size. The input includes data elements and filter weights. The system includes multiple processing elements. Each processing element includes multipliers and adders, with more of the adders than the multipliers. According to at least the analysis result which indicates whether the input size matches a predetermined size, the system is operative to select a first mode or a second mode. In the first mode, a greater number of the adders than the multipliers are enabled for each processing element to multiply transformed input and to perform an inverse transformation. In the second mode, an equal number of the adders and the multipliers are enabled for each processing element to multiply-and-accumulate the input. One or more of the multipliers are shared by the first mode and the second mode.
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