G06F7/496

DEVICE AND METHOD FOR EXTRACTION AND INSERTION OF BINARY WORDS
20210109713 · 2021-04-15 ·

The present disclosure relates to a device and method for processing masked binary data values, comprising extracting and inserting a first part of a first masked binary data value in a second masked binary data value, in which the first and second masked binary data values stay masked throughout all of the processing.

DEVICE AND METHOD FOR EXTRACTION AND INSERTION OF BINARY WORDS
20210109713 · 2021-04-15 ·

The present disclosure relates to a device and method for processing masked binary data values, comprising extracting and inserting a first part of a first masked binary data value in a second masked binary data value, in which the first and second masked binary data values stay masked throughout all of the processing.

REALIZATION OF NEURAL NETWORKS WITH TERNARY INPUTS AND BINARY WEIGHTS IN NAND MEMORY ARRAYS

Use of a NAND array architecture to realize a binary neural network (BNN) allows for matrix multiplication and accumulation to be performed within the memory array. A unit synapse for storing a weight of a BNN is stored in a pair of series connected memory cells. A binary input is applied as a pattern of voltage values on a pair of word lines connected to the unit synapse to perform the multiplication of the input with the weight by determining whether or not the unit synapse conducts. The results of such multiplications are determined by a sense amplifier, with the results accumulated by a counter. The arrangement can be extended to ternary inputs to realize a ternary-binary network (TBN) by adding a circuit to detect 0 input values and adjust the accumulated count accordingly.

REALIZATION OF NEURAL NETWORKS WITH TERNARY INPUTS AND BINARY WEIGHTS IN NAND MEMORY ARRAYS

Use of a NAND array architecture to realize a binary neural network (BNN) allows for matrix multiplication and accumulation to be performed within the memory array. A unit synapse for storing a weight of a BNN is stored in a pair of series connected memory cells. A binary input is applied as a pattern of voltage values on a pair of word lines connected to the unit synapse to perform the multiplication of the input with the weight by determining whether or not the unit synapse conducts. The results of such multiplications are determined by a sense amplifier, with the results accumulated by a counter. The arrangement can be extended to ternary inputs to realize a ternary-binary network (TBN) by adding a circuit to detect 0 input values and adjust the accumulated count accordingly.

SYSTEMS AND METHODS FOR ENERGY-EFFICIENT ANALOG MATRIX MULTIPLICATION FOR MACHINE LEARNING PROCESSES

A novel energy-efficient multiplication circuit using analog multipliers and adders reduces the distance data has to move and the number of times the data has to be moved when performing matrix multiplications in the analog domain. The multiplication circuit is tailored to bitwise multiply the innermost product of a rearranged matrix formula to output the generate a matrix multiplication result in form of a current that is then digitized for further processing.

SYSTEMS AND METHODS FOR ENERGY-EFFICIENT ANALOG MATRIX MULTIPLICATION FOR MACHINE LEARNING PROCESSES

A novel energy-efficient multiplication circuit using analog multipliers and adders reduces the distance data has to move and the number of times the data has to be moved when performing matrix multiplications in the analog domain. The multiplication circuit is tailored to bitwise multiply the innermost product of a rearranged matrix formula to output the generate a matrix multiplication result in form of a current that is then digitized for further processing.

COMPUTER DATA PROCESSING METHOD AND APPARATUS FOR LARGE NUMBER OPERATIONS
20200167128 · 2020-05-28 · ·

Implementations of this specification provide a method and apparatus for computer data processing for large number operations. An example method performed by a computing device includes splitting a multiplier and a multiplicand into respective four 64-bit numbers from most significant bits to least significant bits; reading the split multipliers and the split multiplicands into a register; and obtaining a multiplication processing result for the multiplier and the multiplicand by performing operations including: classifying the split multipliers and the split multiplicands into groups of data pairs, calculating multiplication results of the groups of data pairs one by one, performing accumulation on multiplication results of data pairs in each group, and storing an accumulation result corresponding to the data pairs in memory as the multiplication processing result for the multiplier and the multiplicand.

COMPUTER DATA PROCESSING METHOD AND APPARATUS FOR LARGE NUMBER OPERATIONS
20200167128 · 2020-05-28 · ·

Implementations of this specification provide a method and apparatus for computer data processing for large number operations. An example method performed by a computing device includes splitting a multiplier and a multiplicand into respective four 64-bit numbers from most significant bits to least significant bits; reading the split multipliers and the split multiplicands into a register; and obtaining a multiplication processing result for the multiplier and the multiplicand by performing operations including: classifying the split multipliers and the split multiplicands into groups of data pairs, calculating multiplication results of the groups of data pairs one by one, performing accumulation on multiplication results of data pairs in each group, and storing an accumulation result corresponding to the data pairs in memory as the multiplication processing result for the multiplier and the multiplicand.

INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND RECORDING MEDIUM
20190265949 · 2019-08-29 · ·

An information processing apparatus includes a memory and a processor coupled to the memory. The processor acquires statistical information on a distribution of bits in floating point number data after executing an instruction on the floating point number data, and converts the floating point number data to fixed point number data.

Transmit/receive beamforming signal generation

Transmit and/or receive beamforming signal generation includes a voltage-controlled oscillator (VCO) for generating a lower or higher master frequency output signal in accordance with a selection of a lower or higher frequency carrier frequency. A local oscillator generates local oscillator signals in quadrature in response to the maser frequency output signal. One or more mixer stages generate sidebands in response to a received information signal and the local oscillator signals in quadrature. The one or more mixer stages generate an output information signal in response to high-side injection of lower sidebands of the developed sidebands when the lower frequency carrier frequency is selected, and generate the output information signal in response to low-side injection of higher sidebands of the developed sidebands when the higher frequency carrier frequency is selected. Multi-band operation of transmit and receive arrays can be performed.