G06J1/00

Chopper Stabilized Bias Unit Element with Binary Weighted Charge Transfer Capacitors
20220383002 · 2022-12-01 · ·

A Bias Unit Element (UE) has a digital input, a sign input, and a chop clock. The sign input is exclusive ORed with the chop clock to generate a signed chop clock. Each Bias UE comprises a positive Bias UE and a negative Bias UE, each comprising groups of NAND gates generating an output and a complementary output, each of which are coupled to differential charge transfer lines through binary weighted charge transfer capacitors to a differential charge transfer bus comprising a positive charge transfer line and a negative charge transfer line. The chopped sign input enables the positive Bias UE when the sign bit is positive and enables the negative Bias UE when the sign bit is negative.

Architecture for Analog Multiplier-Accumulator with Binary Weighted Charge Transfer Capacitors
20220385301 · 2022-12-01 · ·

An architecture for a multiplier-accumulator (MAC) uses a common Unit Element (UE) for each aspect of operation, the MAC formed as a plurality of MAC UEs, a plurality of Bias UEs, and a plurality of Analog to Digital Conversion (ADC) UEs which collectively perform a scalable MAC operation and generate a binary result. Each MAC UE, BIAS UE and ADC UE comprises groups of NAND gates with complementary outputs arranged in NAND-groups, each NAND gate coupled to a differential charge transfer bus through a binary weighted charge transfer capacitor to form an analog multiplication product as a charge applied to the differential charge transfer bus. The analog charge transfer bus is coupled to groups of ADC UEs with an ADC controller which enables and disables the ADC UEs using successive approximation to determine the accumulated multiplication result.

Architecture for Analog Multiplier-Accumulator with Binary Weighted Charge Transfer Capacitors
20220385301 · 2022-12-01 · ·

An architecture for a multiplier-accumulator (MAC) uses a common Unit Element (UE) for each aspect of operation, the MAC formed as a plurality of MAC UEs, a plurality of Bias UEs, and a plurality of Analog to Digital Conversion (ADC) UEs which collectively perform a scalable MAC operation and generate a binary result. Each MAC UE, BIAS UE and ADC UE comprises groups of NAND gates with complementary outputs arranged in NAND-groups, each NAND gate coupled to a differential charge transfer bus through a binary weighted charge transfer capacitor to form an analog multiplication product as a charge applied to the differential charge transfer bus. The analog charge transfer bus is coupled to groups of ADC UEs with an ADC controller which enables and disables the ADC UEs using successive approximation to determine the accumulated multiplication result.

Hybrid accumulation method in multiply-accumulate for machine learning
11615256 · 2023-03-28 ·

Methods for performing mixed-mode Multiply-Accumulate (MAC) functions in an integrated circuit (IC) are disclosed. By performing part of the MAC operation spatially and in parallel, and part of it temporally and serially, the number of MAC operations can be programmed in the serial/temporal MAC segment as a multiple of the parallel/spatial MAC segment. Such a trait provides a degree of flexibility in programming the mixed-mode MAC function. A Programmable-Hybrid-Accumulation (PHA) method, performs the accumulation function of the MAC IC, by transforming the accumulation signal to a hybrid accumulation signal. The hybrid accumulation signal is comprised of a Most-Significant-Portion (MSP) and a Least-Significant-Portion (LSP), wherein the portions of the hybrid accumulation signal can be programmed in accordance with cost-performance objectives of an end application. Transforming the accumulated signal to a hybrid signal, and utilizing the PHA method, enables keeping the signal magnitudes bounded which prevent signal over-flow constraints while accumulation cycles proceed. Arranging a mixed-signal MAC in accordance with the PHA method can, among other benefits, help to limit the peak-to-peak analog signal swings which enhances performance attributes such as lower current consumption, faster speed, lower power supply voltage, and a wider signal accumulation range before power supply operating head-room conditions are breached.

Hybrid accumulation method in multiply-accumulate for machine learning
11615256 · 2023-03-28 ·

Methods for performing mixed-mode Multiply-Accumulate (MAC) functions in an integrated circuit (IC) are disclosed. By performing part of the MAC operation spatially and in parallel, and part of it temporally and serially, the number of MAC operations can be programmed in the serial/temporal MAC segment as a multiple of the parallel/spatial MAC segment. Such a trait provides a degree of flexibility in programming the mixed-mode MAC function. A Programmable-Hybrid-Accumulation (PHA) method, performs the accumulation function of the MAC IC, by transforming the accumulation signal to a hybrid accumulation signal. The hybrid accumulation signal is comprised of a Most-Significant-Portion (MSP) and a Least-Significant-Portion (LSP), wherein the portions of the hybrid accumulation signal can be programmed in accordance with cost-performance objectives of an end application. Transforming the accumulated signal to a hybrid signal, and utilizing the PHA method, enables keeping the signal magnitudes bounded which prevent signal over-flow constraints while accumulation cycles proceed. Arranging a mixed-signal MAC in accordance with the PHA method can, among other benefits, help to limit the peak-to-peak analog signal swings which enhances performance attributes such as lower current consumption, faster speed, lower power supply voltage, and a wider signal accumulation range before power supply operating head-room conditions are breached.

MIXED-SIGNAL ACCELERATION OF DEEP NEURAL NETWORKS
20220350662 · 2022-11-03 ·

Disclosed are devices, systems and methods for accelerating vector-based computation. In one example aspect, an accelerator apparatus includes a plurality of mixed-signal units, each of which includes a first digital-to-analog convertor configured to convert a subset of digital-domain bits to a first analog-domain signal and a second digital-to-analog convertor configured to convert a subset of digital-domain bits to a second analog-domain signal. Each mixed-signal unit also includes a capacitor coupled to the digital-to-analog convertors to accumulate a result of a multiplication operation as an analog signal. The apparatus includes a circuitry coupled to the mixed-signal units to shift part of the analog signals of the plurality of mixed-signal units. The circuitry comprises an additional capacitor to store an analog-domain result for a multiply-accumulate operation. The apparatus also includes an analog-to-digital converter coupled to the circuitry to convert the analog-domain result into a digital-domain result.

CONSTRAINED OPTIMIZATION USING AN ANALOG PROCESSOR
20230110047 · 2023-04-13 · ·

Described herein are techniques of using a hybrid analog-digital processor to optimize parameters of a system for an objective under one or more constraints. The techniques involve using the hybrid analog-digital processor to optimizing parameter values of the system. The optimizing comprises: determining, using an analog processor of the hybrid analog-digital processor, a parameter gradient for parameter values of the system based on the objective function and the at least one constraint; and updating the parameter values of the system using the parameter gradient.

CONSTRAINED OPTIMIZATION USING AN ANALOG PROCESSOR
20230110047 · 2023-04-13 · ·

Described herein are techniques of using a hybrid analog-digital processor to optimize parameters of a system for an objective under one or more constraints. The techniques involve using the hybrid analog-digital processor to optimizing parameter values of the system. The optimizing comprises: determining, using an analog processor of the hybrid analog-digital processor, a parameter gradient for parameter values of the system based on the objective function and the at least one constraint; and updating the parameter values of the system using the parameter gradient.

System and methods for mixed-signal computing

A mixed-signal integrated circuit that includes: a global reference signal source; a first summation node and a second summation node; a plurality of distinct pairs of current generating circuits arranged along the first summation node and the second summation node; a first current generating circuit of each of the plurality of distinct pairs that is arranged on the first summation node and a second current generating circuit of each of the plurality of distinct pairs is arranged on the second summation node; a common-mode current circuit that is arranged in electrical communication with each of the first and second summation nodes; where a local DAC adjusts a differential current between the first second summation nodes based on reference signals from the global reference source; and a comparator or a finite state machine that generates a binary output value current values obtained from the first and second summation nodes.

Chopper stabilized bias unit element with binary weighted charge transfer capacitors
11687738 · 2023-06-27 · ·

A Bias Unit Element (UE) has a digital input, a sign input, and a chop clock. The sign input is exclusive ORed with the chop clock to generate a signed chop clock. Each Bias UE comprises a positive Bias UE and a negative Bias UE, each comprising groups of NAND gates generating an output and a complementary output, each of which are coupled to differential charge transfer lines through binary weighted charge transfer capacitors to a differential charge transfer bus comprising a positive charge transfer line and a negative charge transfer line. The chopped sign input enables the positive Bias UE when the sign bit is positive and enables the negative Bias UE when the sign bit is negative.