摘要:
A model calculation unit for calculating a data-based function model in a control unit is provided, the model calculation unit having a processor core which includes: a multiplication unit for carrying out a multiplication on the hardware side; an addition unit for carrying out an addition on the hardware side; an exponential function unit for calculating an exponential function on the hardware side; a memory in the form of a configuration register for storing hyperparameters and node data of the data-based function model to be calculated; and a logic circuit for controlling, on the hardware side, the calculation sequence in the multiplication unit, the addition unit, the exponential function unit and the memory in order to ascertain the data-based function model.
摘要:
A method for operating a control unit, the control unit including a software-controlled main processing unit, a strictly hardware-based model calculation unit for calculating an algorithm, for carrying out a Bayesian regression method, based on configuration data, and a memory unit, a model memory area being defined in the memory unit to which a configuration register block for providing the configuration data in the model calculation unit is assigned, a calculation start-configuration register being assigned the highest address in the configuration register block into which configuration data are written, the writing into of which starts the calculation in the model calculation unit, the configuration data being written in a memory area of the memory unit from the model memory area into the configuration register block with an incremental copying process, the addresses being copied in the incremental copying process in ascending order.
摘要:
An FMA unit, for carrying out an arithmetic operation in a model computation unit of a control unit, is configured to process input of two factors and one summand in the form of floating point values, and provide a computation result of such processing as an output variable in the form of a floating point value. The FMA unit is designed to carry out a multiplication and a subsequent addition, the bit resolutions of the inputs for the factors being lower than the bit resolution of the input for the summand and the bit resolution of the output variable.
摘要:
A method for generating a data-based function model includes: providing a first data-based partial model ascertained from a first training data record; providing at least one additional training data record; and performing the following steps for the at least one additional training data record: ascertaining a difference training data record having training data which correspond to the differences between the output values of the relevant additional training data record and the function value of the sum of the partial function values (ffirst—partial—model(x) fsecond—partial—model(x)) of the first data-based partial model and previously ascertained data-based partial model(s) at each of the measuring points of the relevant training data record; ascertaining an additional data-based partial model from the difference training data record; and forming a sum (f(x)) from the first and the additional data-based partial models.
摘要:
A method for carrying out a calculation of a data-based function model in a control unit having a computing unit and a separate model calculation unit having a computing core, including: loading a first part of the configuration data, which contain hyperparameters of the data-based function model and a first part of supporting point data having multiple supporting points, into the model calculation unit; starting a calculation in the computing core of the model calculation unit, to obtain a model value at a predefined test point; and transferring a second part of the configuration data, which contain a second part of the supporting point data having multiple supporting points, into the model calculation unit, prior to the completion of the calculation in the computing core of the model calculation unit.
摘要:
A method for carrying out a calculation of a data-based function model, in particular a Gaussian process model, the data-based function model being defined by predefined hyperparameters and node data, multiple input variables being assigned to one output variable and having a sum of terms, each of which depend on one of the input variables, including the following: determining at least one input variable to be varied, for which multiple output values of a corresponding output variable are to be determined; calculating the sum of the terms, which depend on the input variables not to be varied; providing multiple input values for each of the determined at least one input variable to be varied; and ascertaining multiple output values of the output variable for the provided multiple input values, each based on the calculated sum of the terms, which depend on the input variables not to be varied.