Intel Corporation

Deepak Dasalukunte

Richard Dorrance

Hechen Wang

Satish Chandra Jha

Kathiravetpillai Sivanesan

Ignacio Javier Alvarez

David Israel Gonzalez Aguirre

S M Iftekharul Alam

Sridhar G Sharma

Lu Lu

Ranganath Krishnan

Maria Soledad Elli

Arvind Merwaday

Renzhi Liu

David Gonzales Aguirre

Niranjan Mylarappa Gowda

Andrey Belogolovy

Sundar Krishnamurthy

Le Liang

A processor may include an interface configured to receive input data and instructions, and to provide processed data, a shared memory configured to store the received input data, an instruction memory configured to store the received instructions, a plurality of processing elements configured to perform a first set of arithmetic operations. The processor may further include a controller configured to control the plurality of processing elements and one or more accelerators based on the received instructions to obtain the processed data, by which the plurality of processing elements performs the first set of arithmetic operations and the one or more accelerators perform a second set of arithmetic operations based on the received input data stored in the shared memory.

Methods and devices for signal processing

A wireless communication device, including a radiofrequency frontend, configured to wirelessly receive a radiofrequency signal; perform one or more analog baseband operations on the received radiofrequency signal, according to a radio access technology; and output an analog signal representing an output of the analog baseband operations on the received radiofrequency signal; an error corrector, configured to perform an error correction operation on the analog signal; and output an error corrected signal in analog domain; and the analog-digital converter, configured to convert the error corrected signal to digital domain.

Analog forward error correction

Systems, methods, apparatuses, and computer-readable media. An analog router of a first supertile of a plurality of supertiles of a network on a chip (NoC) may receive a first analog output from a first compute-in-memory tile of a plurality of compute-in-memory tiles of the first supertile. The analog router may determine, based on a configuration of a neural network executing on the NoC, that a destination of the first analog output includes a second supertile of the plurality of supertiles. An analog-to-digital converter (ADC) of the analog router may convert the first analog output to a first digital output and transmit the first digital output to the second supertile via a communications bus of the NoC.

Hierarchical hybrid network on chip architecture for compute-in-memory probabilistic machine learning accelerator

Various embodiments provide apparatuses, systems, and methods for multibit analog representation, e.g., for in-memory computing. Embodiments may include a single-ended or differential ladder network to generate an analog value (e.g., a voltage or charge) based on a set of bits from a memory array. The ladder network may include a plurality of branches coupled to an output line, wherein individual branches include a capacitor with a first terminal coupled to the output line and a switch coupled to a second terminal of the capacitor. The switch may be controlled by a respective bit of the set of bits to selectively couple the second terminal of the capacitor to a first voltage node or a second voltage node based on a value of the respective bit. Other embodiments may be described and claimed.

Techniques for analog multibit data representation for in-memory computing

Techniques and mechanisms providing a mode of random number generation to satisfy a requirement for a consumer of random numbers. In an embodiment, a device comprises a Gaussian random number generator (GRNG) circuit, multiple uniform random number generator URNG circuits, and circuitry which is coupled between the GRNG circuit and the URNG circuits. Based on an indication of one or more required performance characteristics and/or one or more required statistical characteristics, a controller identifies a corresponding one of multiple available random number generation (RNG) modes. The controller communicates control signals to provide the mode with the circuitry. In another embodiment, the control signals configure the circuitry to select one or more of the URNG circuits for use in calculating random numbers with the GRNG circuit.

Device, method and system to selectively provide a mode of random number generation

Methods, apparatus, systems, and articles of manufacture providing an improved Bayesian neural network and methods and apparatus to operate the same are disclosed. An example apparatus includes an oscillator to generate a first clock signal; a resistive element to adjust a slope of a rising edge of a second clock signal; a voltage sampler to generate a sample based on at least one of (a) a first voltage of the first clock signal when a second voltage of the second clock signal satisfies a threshold or (b) a third voltage of the second clock signal when a fourth voltage of the first clock signal satisfies the threshold; and a charge pump to adjust a weight based on the sample, the weight to adjust data in a model.

Bayesian neural network and methods and apparatus to operate the same

Bayesian Inference based communication receiver employs Markov-Chain Monte-Carlo (MCMC) sampling for performing several of the main receiver functionalities. The channel estimator estimates the multipath channel coefficients corresponding to a signal received with fading. The symbol demodulator demodulates the received signal according to a QAM constellation, so as to generate a demodulated signal, and estimate the transmitted symbols. The decoder reliably decodes the demodulated signals to generate an output bit sequence, factoring in redundancy induced at a certain code rate. A universal sampler may be configured to use MCMC sampling for generating estimates of channel coefficients, transmitted symbols or decoder bits, for aforementioned functionalities, respectively. The samples may then be used in one or more of the receiver tasks: channel estimation, signal demodulation, and decoding, which leads to a more scalable, reusable, power/area efficient receiver.

Communication devices and methods based on markov-chain monte-carlo (MCMC) sampling

A communication device for a vehicle to communicate features about the vehicle's environment includes one or more processors configured to receive a communication from another device, wherein the communication includes a global reference coordinate system for an area covered by the other device and a number of allowed transmissions to be sent from the vehicle; transform stored data about the vehicle's environment based on the global reference coordinate system; divide the transformed stored data into a plurality of subsets of data; and select one or more subsets of data from the plurality of subsets for transmission according to the number of allowed transmissions.

Devices and methods for updating maps in autonomous driving systems in bandwidth constrained networks

According to various embodiments, a method for operating a vehicle may include determining a vehicular area having traffic conditions or characteristics different from traffic conditions of a current or previous location of the vehicle; obtaining traffic and driving information for the determined vehicular region; changing or updating one or more of driving model parameters of a safety driving model during operation of the vehicle based on the obtained traffic and driving information; and controlling the vehicle to operate in accordance with the safety driving model using the one or more changed or updated driving model parameters. A vehicle may seamlessly update operational rules and/or handover of traffic and driving information for transitioning from one region to another.

Systems, methods, and devices for driving control

Vehicle navigation control systems in autonomous driving rely on the accuracy of maps which include features about a vehicle's environment so that a vehicle may safely navigate through its surrounding area. Accordingly, this disclosure provides methods and devices which implement mechanisms for communicating features observed about a vehicle's environment for use in updating maps so as to provide vehicles with accurate and 'real-time' features of its surroundings while taking network resources, such as available frequency-time resources, into consideration.

Growing community of inventors

Beaverton, OR, United States of America

Deepak Dasalukunte