Patent classifications
G06G7/163
Power Control by Direct Drive
A power control circuit comprising a power supply and a load, the load being synthesized from an impedance synthesizer comprising two-terminal impedance elements connected in series and grouped in impedance modules. The impedance elements in each impedance module are of equal value, while those between the modules bear ratios uniquely defined according to the numbers of impedance elements in the impedance modules. A number of switches associated with said impedance elements short out a selected number of the impedance elements under the control of a first analog signal which may be preprocessed by an analytic function. The analog signal is converted to digital signals by an analog-to-digital converter, then level shifted to control the switches associated with the impedance elements, whereby the amount of power delivered to the load is controllable by the first analog signal. Pulse-width-modulation is deployed to further control the power by a second analog signal, with additional benefit of overload protection.
Nonvolatile memory device and method of processing in memory (PIM) using the same
A nonvolatile memory device includes a memory cell array, an input current generator, an operation cell array and an analog-to-digital converter. The memory cell array includes NAND strings storing multiplicand data, wherein first ends of the NAND strings are connected to bitlines and second ends of the NAND strings output multiplication bits corresponding to bitwise multiplication of the multiplicand data stored in the NAND strings and multiplier data loaded on the bitlines. The input current generator generates input currents. The operation cell array includes switching transistors. Gate electrodes of the switching transistors are connected to the second ends of the NAND strings. The switching transistors selectively sum the input currents based on the multiplication bits to output the output currents. The analog-to-digital converter converts the output currents to digital values.
CHARGE DOMAIN MATHEMATICAL ENGINE AND METHOD
A multiplier has a pair of charge reservoirs. The pair of charge reservoirs are connected in series. A first charge movement device induces charge movement to or from the pair of charge reservoirs at a same rate. A second charge movement device induces charge movement to or from one of the pair of reservoirs, the rate of charge movement programmed to one of add or remove charges at a rate proportional to the first charge movement device. The first charge movement device loads a first charge into a first of the pair of charge reservoirs during a first cycle. The first charge movement device and the second charge movement device remove charges at a proportional rate from the pair of charge reservoirs during a second cycle until the first of the pair of charge reservoirs is depleted of the first charge. The second charge reservoir thereafter holding the multiplied result.
Power control by direct drive
A power control circuit comprising a power supply and a load, the load being synthesized from an impedance synthesizer comprising two-terminal impedance elements connected in series and grouped in impedance modules. The impedance elements in each impedance module are of equal value, while those between the modules bear ratios uniquely defined according to the numbers of impedance elements in the impedance modules. A number of switches associated with said impedance elements short out a selected number of the impedance elements under the control of a first analog signal which may be preprocessed by an analytic function. The analog signal is converted to digital signals by an analog-to-digital converter, then level shifted to control the switches associated with the impedance elements, whereby the amount of power delivered to the load is controllable by the first analog signal. Pulse-width-modulation is deployed to further control the power by a second analog signal, with additional benefit of overload protection.
Current-mode analog multipliers for artificial intelligence
Analog multipliers can perform signal processing with approximate precision asynchronously (clock free) and with low power consumptions, which can be advantageous including in emerging mobile and portable artificial intelligence (AI) and machine learning (ML) applications near or at the edge and or near sensors. Based on low cost, mainstream, and purely digital Complementary-Metal-Oxide-Semiconductor (CMOS) manufacturing process, the present invention discloses embodiments of current-mode analog multipliers that can be utilized in multiply-accumulate (MAC) signal processing in end-application that require low cost, low power consumption, (clock free) and asynchronous operations.
Current-mode analog multiply-accumulate circuits for artificial intelligence
Analog multipliers can perform signal processing with approximate precision asynchronously (clock free) and with low power consumptions, which can be advantageous including in emerging mobile and portable artificial intelligence (AI) and machine learning (ML) applications near or at the edge and or near sensors. Based on low cost, mainstream, and purely digital Complementary-Metal-Oxide-Semiconductor (CMOS) manufacturing process, the present invention discloses embodiments of current-mode analog multipliers that can be utilized in multiply-accumulate (MAC) signal processing in end-application that require low cost, low power consumption, (clock free) and asynchronous operations.
Current-mode analog multiply-accumulate circuits for artificial intelligence
Analog multipliers can perform signal processing with approximate precision asynchronously (clock free) and with low power consumptions, which can be advantageous including in emerging mobile and portable artificial intelligence (AI) and machine learning (ML) applications near or at the edge and or near sensors. Based on low cost, mainstream, and purely digital Complementary-Metal-Oxide-Semiconductor (CMOS) manufacturing process, the present invention discloses embodiments of current-mode analog multipliers that can be utilized in multiply-accumulate (MAC) signal processing in end-application that require low cost, low power consumption, (clock free) and asynchronous operations.
Crossbar allocation for matrix-vector multiplications
Repeating patterns are identified in a matrix. Based on the identification of the repeating patterns, instructions are generated, which are executable by processing cores of a dot product engine to allocate analog multiplication crossbars of the dot product engine to perform multiplication of the matrix with a vector.
Hardware Accelerated Discretized Neural Network
An innovative low-bit-width device may include a first digital-to-analog converter (DAC), a second DAC, a plurality of non-volatile memory (NVM) weight arrays, one or more analog-to-digital converters (ADCs), and a neural circuit. The first DAC is configured to convert a digital input signal into an analog input signal. The second DAC is configured to convert a digital previous hidden state (PHS) signal into an analog PHS signal. NVM weight arrays are configured to compute vector matrix multiplication (VMM) arrays based on the analog input signal and the analog PHS signal. The NVM weight arrays are coupled to the first DAC and the second DAC. The one or more ADCs are coupled to the plurality of NVM weight arrays and are configured to convert the VMM arrays into digital VMM values. The neural circuit is configured to process the digital VMM values into a new hidden state.
CROSSBAR ALLOCATION FOR MATRIX-VECTOR MULTIPLICATIONS
Repeating patterns are identified in a matrix. Based on the identification of the repeating patterns, instructions are generated, which are executable by processing cores of a dot product engine to allocate analog multiplication crossbars of the dot product engine to perform multiplication of the matrix with a vector.