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Processor and memory transparent convolutional lowering and auto zero padding for deep neural network implementations
Processor and memory transparent convolutional lowering and auto zero padding for deep neural network implementations
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机译:用于深度神经网络实现的处理器和内存透明卷积降低和自动零填充
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摘要
A convolutional lowering component (CoLor component) between processor and memory units (or within a memory hierarchy) maps location in a lowered matrix to an equivalent location in a non-lowered matrix and provides auto zero padding in computational heavy convolutional layers. An identification component identifies processing components that execute computations in deep neural networks (DNNs) in which convolutions are realized as general matrix to matrix multiplications (GEMM) operations, and identifies a subset of the processing components that store deep neural network (DNN) features in a non-lowered form component that determines output for successively larger neural networks of a set. An address translation component translates address requests, generated by the subset of processing components to a memory subsystem, from a lowered index form to a non-lowered index form.
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