ELECTRONIC-PHOTONIC PROCESSORS AND RELATED PACKAGES

    公开(公告)号:WO2022246171A2

    公开(公告)日:2022-11-24

    申请号:PCT/US2022/030215

    申请日:2022-05-20

    Abstract: Electronic-photonic packages and related fabrication methods are described. A package may include a plurality of photonic integrated circuits (PICs), where each PIC comprises a photonic accelerator configured to perform matrix multiplication in the optical domain. The package may further include an application specific integrated circuit (ASIC) configured to control at least one of the photonic accelerators. The package further includes an interposer. The plurality of PICs are coupled to a first side of the interposer and the ASIC is coupled to a second side of the interposer opposite the first side. A first thermally conductive member in thermal contact with at least one of the PICs. The first thermally conductive member may include a heat spreader. A second thermally conductive member in thermal contact with the ASIC. The second thermally conductive member may include a lid. The first thermally conductive member faces the first side of the interposer, and the second thermally conductive member faces the second side of the interposer. In some embodiments, the interposer sits in part on a substrate and in part on the PICs.

    OPTICAL DIFFERENTIAL LOW-NOISE RECEIVERS AND RELATED METHODS

    公开(公告)号:WO2020149871A1

    公开(公告)日:2020-07-23

    申请号:PCT/US2019/032111

    申请日:2019-05-14

    Abstract: Low-noise optical differential receivers are described. Such differential receivers may include a differential amplifier having first and second inputs and first and second outputs, and four photodetectors. A first and a second of such photodetectors are coupled to the first input of the differential amplifier, and a third and a fourth of such photodetectors are coupled to the second input of the differential amplifier. The anode of the first photodetector and the cathode of the second photodetector are coupled to the first input of the differential amplifier. The cathode of the third photodetector and the anode of the fourth photodetector are coupled to the second input of the differential amplifier. The optical receiver may involve two stages of signal subtraction, which may significantly increase noise immunity.

    OPTICALLY INTERFACED STACKED MEMORIES AND RELATED METHODS AND SYSTEMS

    公开(公告)号:WO2019221902A1

    公开(公告)日:2019-11-21

    申请号:PCT/US2019/029803

    申请日:2019-04-30

    Abstract: A memory device is described. The memory device comprises a plurality of stacked memory layers, wherein each of the plurality of stacked memory layers comprises a plurality of memory cells. The memory device further comprises an optical die bonded to the plurality of stacked memory layers and in electrical communication with the stacked memory layers through one or more interconnects. The optical die comprises an optical transceiver, and a memory controller configured to control read and/or write operations of the stacked memory layers. The optical die may be positioned at one end of the plurality of stacked memory layers. The one or more interconnects may comprise one or more through silicon vias (TSV). The plurality of memory cells may comprise a plurality of solid state memory cells. The memory devices described herein can enable all-to-all, point-to-multipoint and ring architectures for connecting logic units with memory devices.

    PARALLELIZATION AND PIPELINING STRATEGIES FOR AN EFFICIENT ANALOG NEURAL NETWORK ACCELERATOR

    公开(公告)号:WO2022104223A1

    公开(公告)日:2022-05-19

    申请号:PCT/US2021/059408

    申请日:2021-11-15

    Abstract: Parallelization and pipelining techniques that can be applied to multi-core analog accelerators are described. The techniques descried herein improve performance of matrix multiplication (e.g., tensor-tensor multiplication, matrix-matrix multiplication or matrix-vector multiplication). The parallelization and pipelining techniques developed by the inventors and described herein focus on maintaining a high utilization of the processing cores. A representative processing systemin includes an analog accelerator, a digital processor, and a controller. The controller is configured to control the analog accelerator to output data using linear operations and to control the digital processor to perform non-linear operations based on the output data.

    INTERFEROMETRIC MODULATION
    5.
    发明申请

    公开(公告)号:WO2021102076A1

    公开(公告)日:2021-05-27

    申请号:PCT/US2020/061169

    申请日:2020-11-19

    Abstract: The techniques described herein relate to methods and apparatus for interferometric modulation. An apparatus includes an interferometric device comprising a first optical path and a second optical path, and at least one Franz-Keldysh (FK) modulator disposed in either the first optical path or the second optical path of the interferometric device. The interferometric device receives input light, wherein a first portion of the input light travels along the first optical path of the interferometric device, and a second portion of the input light travels along the second optical path of the interferometric device. The FK modulator modulates an intensity of either the first portion of the input light or the second portion of the input light.

    QUANTIZED ARCHITECTURE SEARCH FOR MACHINE LEARNING MODELS

    公开(公告)号:WO2021086861A1

    公开(公告)日:2021-05-06

    申请号:PCT/US2020/057551

    申请日:2020-10-27

    Inventor: LAZOVICH, Tomo

    Abstract: Described herein are techniques for determining an architecture of a machine learning model that optimizes the machine learning model. The system obtains a machine learning model configured with a first architecture of a plurality of architectures. The machine learning model has a first set of parameters. The system determines a second architecture using a quantization of the parameters of the machine learning model. The system updates the machine learning model to obtain a machine learning model configured with the second architecture.

    FIBER-COUPLED LASER LIGHT SOURCE
    8.
    发明申请

    公开(公告)号:WO2023034300A1

    公开(公告)日:2023-03-09

    申请号:PCT/US2022/042038

    申请日:2022-08-30

    Abstract: Described herein are photonic sources and related system architectures that can satisfy the optical power requirements of large photonic accelerators. Some embodiments relate to a computer comprising a photonic accelerator configured to perform matrix multiplication; a fiber array optically coupled to the photonic accelerator; and a photonic source optically coupled to the fiber array. The photonic source comprising a laser array comprising a plurality of monolithically co-integrated lasers, and a coupling lens array comprising a plurality of monolithically co-integrated lenses, the coupling lens array optically coupling the laser array to the fiber array. The laser array is configured to output between 0.1 W and 10 W of optical power.

    SYSTEMS AND METHODS FOR UTILIZING PHOTONIC DEGREES OF FREEDOM IN A PHOTONIC PROCESSOR

    公开(公告)号:WO2022020667A1

    公开(公告)日:2022-01-27

    申请号:PCT/US2021/042882

    申请日:2021-07-23

    Abstract: Systems and methods for increasing throughput of a photonic processor by using photonic degrees of freedom (DOF) are provided. The photonic processor includes a multiplexer configured to multiplex, using at least one photonic DOF, multiple encoded optical signals into a multiplexed optical signal. The photonic processor also includes a detector coupled to an output of an optical path including the multiplexer, the detector being configured to generate a first current based on the multiplexed optical signal or a demultiplexed portion of the multiplexed optical signal. The photonic processor further includes a modulator coupled to and output of the detector, the modulator being configured to generate a second current by modulating the first current.

    QUANTIZED INPUTS FOR MACHINE LEARNING MODELS
    10.
    发明申请

    公开(公告)号:WO2021061625A1

    公开(公告)日:2021-04-01

    申请号:PCT/US2020/051965

    申请日:2020-09-22

    Inventor: LAZOVICH, Tomo

    Abstract: Methods and apparatus for pre-processing first data for use with a trained machine learning model. In some embodiments, the method may comprise accessing the first data, wherein the first data has a first precision; generating, based on at least a first portion of the first data, second data having a second precision lower than the first precision; and providing the second data as input to the trained machine learning model to generate model output.

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