×

Method to Map Convolutional Layers of Deep Neural Network on a Plurality of Processing Elements with SIMD Execution Units, Private Memories, and Connected as a 2D Systolic Processor Array

  • US 20200134105A1
  • Filed: 10/31/2018
  • Published: 04/30/2020
  • Est. Priority Date: 10/31/2018
  • Status: Active Application
First Claim
Patent Images

1. A method for improving performance of a predefined Deep Neural Network (DNN) convolution processing on a computing device, the method comprising:

  • inputting parameters as input data into a processor on a computer that formalizes a design space exploration of a convolution mapping on a predefined computer architecture that will execute the predefined convolution processing, wherein the parameters are predefined as guided by a specification for the predefined convolution processing to be implemented by the convolution mapping and by a microarchitectural specification for the processor that will execute the predefined convolution processing; and

    calculating, by the processor, performance metrics for executing the predefined convolution processing on the computing device, as functions of the predefined parameters, as proxy estimates of performance of different possible design choices to implement the predefined convolution processing.

View all claims
  • 1 Assignment
Timeline View
Assignment View
    ×
    ×