Inference system

Patent metadata

Field	Value
Publication number	US-2020160186-A1
Application number	US-201916686732-A
Country	US
Kind code	A1
Filing date	Nov 18, 2019
Priority date	Nov 20, 2018
Publication date	May 21, 2020
Grant date	—

Abstract

There is described an inference system for performing inference in a machine learning or neural net system, preferably an analog computing system. The overall power consumption of the inference system is reduced by providing for a dynamic or adjustable memory refresh rate of the inference system, and/or providing a dynamic or adjustable accuracy level of components of the inference system.

First claim

1 . An inference system comprising:
at least one neuron circuit arranged to receive at least one data input and at least one weighting signal, the neuron circuit arranged to output a signal based on at least the at least one data input and the at least one weighting signal; and at least one weighting refresh circuit arranged to retrieve at least one weighting data value from a memory and to output at least one weighting signal for the at least one neuron circuit, wherein the weighting refresh circuit is configured to repeatedly retrieve the at least one weighting data value from the memory at a refresh rate, wherein the refresh rate is dynamic or adjustable.

2 .- 6 . (canceled)

7 . The inference system of claim 1 , wherein the refresh rate is adjustable based on one or more of:
a voltage or current level of a power supply associated with the inference system; a power supply source of a device incorporating the inference system; a power mode of a device incorporating the inference system; operational parameters of the inference system; and operational temperature of the inference system.

8 . (canceled)

9 . The inference system of claim 1 , wherein the refresh rate is adjusted based on one or more of the following:
a voice activity detection module (VAD) indicating the presence of speech in received audio; a voice keyword detection module (VKD) indicating the presence of a keyword or wake-word in received audio; a speaker identification or verification module indicating the identity or authorisation of a speaker of the received audio; a command recognition module arranged to recognise commands present in speech in the received audio; an audio quality metrics module arranged to determine at least one indication of the signal quality of the received audio, e.g., signal-to-noise level, signal amplitude, bandwidth metrics, etc.; an acoustic environment determination module arranged to determine at least one indication of the user's environment; and a signal indicative of a user interaction with an electronic device incorporating the inference system.

10 . (canceled)

11 . The inference system of claim 1 The inference system of any one of claims 1 - 10 , wherein the refresh rate is adjusted based on the output of a memory reference cell.

12 . The inference system of claim 11 , wherein the inference system comprises at least one memory reference cell, the memory reference cell arranged to receive a weighting signal from a weighting circuit, the weighting signal stored in the memory reference cell,
wherein the memory reference cell is configured to monitor the level of the stored weighting signal, and wherein the memory reference cell is arranged to trigger a refresh of the weighting storage elements for at least a portion of the inference system if the monitored level passes a threshold value.

13 . The inference system of claim 12 , wherein the allowable threshold level of the memory reference cell is adjusted based on a desired accuracy level of the inference system.

14 . The inference system of claim 1 , wherein a refresh operation may be triggered based on a calculation cycle, or as an on-demand refreshing of system memory.

15 . The inference system of claim 1 , wherein the inference system is operable to perform a calibration operation, wherein the data inputs for the at least one neuron circuit are set to known input values and the output of the at least one neuron circuit is compared to an expected output value, and wherein if the output is different to the expected output value a weighting storage element refresh with a modified weighting signal value is performed.

16 . (canceled)

17 . The inference system of claim 1 , wherein the inference system comprises a plurality of weighting storage elements, wherein the different weighting storage elements are refreshed at different refresh rates.

18 . The inference system of claim 1 , wherein the inference system comprises a plurality of neuron circuits having at least one associated weighting refresh element, wherein the plurality of neuron circuits are arranged in sets comprising one or more neuron circuits and each set of each neuron circuits is provided with a separate weighting refresh circuit.

19 .- 20 . (canceled)

21 . The inference system of claim 1 , wherein the inference system is configured to generate an output based on a received input signal, wherein the refresh rate is adjustable based on the characteristics of the received input signal, for example the signal-to-noise ratio of the received input signal; the amplitude level of the received input signal; or any other suitable quality metric of the received input signal.

22 . (canceled)

23 . The inference system of claim 1 , wherein the refresh rate is adjustable based on the magnitude of the weighting factor corresponding to the weighting storage element to be refreshed.

24 . (canceled)

25 . The inference system of claim 1 , wherein the weighting refresh circuit comprises a digital-to-analog converter (DAC) which is configured to receive a weighting data value from a digital memory storage, and to convert the digital weighting data value to an analog weighting current output of the weighting refresh circuit.

26 . The inference system of claim 25 , wherein the DAC is selectively coupled with a plurality of weighting storage elements, wherein the DAC is configured to output respective analog weighting currents which may be used to provide respective weighting signals to refresh each of the plurality of weighting storage elements, wherein the refresh of the respective weighting storage elements of the plurality by respective weighting signals is be performed at different times by the same DAC.

27 . (canceled)

28 . The inference system of claim 1 , wherein the at least one neuron circuit comprises compensation circuitry for compensating for any variation in the at least one weighting signal between refresh operations.

29 . (canceled)

30 . A neuron circuit for inference, the circuit comprising:
an input to receive a data signal representative of a data input for the neuron circuit; a controlled current source arranged to output onto an accumulation node a weighting current dependent on the voltage on a control node, via a first switch controlled by the data signal a weighting storage element connected to the control node a second switch periodically closed to connect the weighting storage element to a weighting signal source and opened to isolate the weighting storage element.

31 .- 34 . (canceled)

35 . The neuron circuit of claim 30 comprising compensation circuitry for compensating for any change in the value of the weighting current.

36 . The neuron circuit of claim 35 wherein the compensation circuitry is configured to receive a reference current and, based on the reference current, to control at least one of:
a conversion gain of a controller for controlling the first switch based on the data signal;
a value of capacitance coupled to the accumulation node;
a conversion gain of a converter for generating an output signal based on current supplied to the accumulation node; and
a digital gain applied to a digital output signal from a converter for generating an output signal based on current supplied to the accumulation node.

37 . The neuron circuit of claim 36 wherein

Assignees

• Cirrus Logic Int Semiconductor Ltd

Inventors

• Lesso John Paul
• Pennock John Laurence
• Bates Gordon James

Classifications

• G06N5/04

  Inference or reasoning models · CPC title

• G06N5/046

  Forward inferencing; Production systems · CPC title

• G06N3/082 Primary

  modifying the architecture, e.g. adding, deleting or silencing nodes or connections · CPC title

• G06N3/048

  Activation functions · CPC title

• G06N3/065 Primary

  Analogue means · CPC title