Granted Patent B2

US 12,253,918 · App. 17/798,978 · Granted Mar 18, 2025

Inventors: Andre Guntoro (Weil der Stadt, DE); Christoph Schorn (Benningen Am Neckar, DE); Jo Pletinckx (Sersheim, DE); Leonardo Luiz Ecco (Stuttgart, DE); Sebastian Vogel (Schaidt, DE)

Assignee: ROBERT BOSCH GMBH

G06F11/1476G06F11/141

Abstract

Claims (6)

1. A method for operating a hardware platform for an inference calculation of a layered neural network, the hardware platform including a computing unit with an internal working memory and an external working memory arranged outside the computing unit and connected to the computing unit, the method comprising the following steps:

reading in a first portion of input data which are required for the inference calculation of a first layer of the neural network and redundancy information relating to said input data from the external working memory into the internal working memory of the computing unit;

checking integrity of the input data based on the redundancy information;

in response to the input data being identified as error-free, carrying out, by the computing unit at least part of the first-layer inference calculation for the input data to obtain a work result;

determining redundancy information for the work result, based on which an integrity of the work result can be verified; and

writing the work result and the redundancy information to the external working memory, wherein the work result includes outputs from neurons of the first layer which each contain a weighted sum of inputs of the neurons of the first layer, wherein the inference calculation includes convolution of data with a plurality of convolutional kernels, and wherein the redundancy information is determined by convolving the data with a control kernel which is a sum of the convolutional kernels.

Assignments (1)

Priority Claims (1)

Continuity (1)

References Cited (25)