首页> 外国专利> 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

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

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.
机译:处理器和内存单元之间(或内存层次结构中)的卷积降低组件(CoLor组件)将降低矩阵中的位置映射到非降低矩阵中的等效位置,并在计算繁重的卷积层中提供自动零填充。识别组件识别在深度神经网络(DNN)中执行计算的处理组件,在其中将卷积实现为通用矩阵到矩阵乘法(GEMM)运算,并识别存储深度神经网络(DNN)特征的处理组件的子集。一个非降级形式的组件,它确定一组连续较大的神经网络的输出。地址转换组件将由处理组件的子集生成的地址请求从降低的索引形式转换为非降低的索引形式。

著录项

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号