Patents by Inventor Jacob Bucci

Jacob Bucci has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Artificial neural network functionality using dynamic random-access memory
    Patent number: 10818344
    Abstract: Techniques are disclosed for artificial neural network functionality within dynamic random-access memory. A plurality of dynamic random-access cells is accessed within a memory block. Data within the plurality of dynamic random-access cells is sensed using a plurality of sense amplifiers associated with the plurality of dynamic random-access cells. A plurality of select lines coupled to the plurality of sense amplifiers is activated to facilitate the sensing of the data within the plurality of dynamic random-access cells, wherein the activating is a function of inputs to a layer within a neural network, and wherein a bit within the plurality of dynamic random-access cells is sensed by a first sense amplifier and a second sense amplifier within the plurality of sense amplifiers. Resulting data is provided based on the activating wherein the resulting data is a function of weights within the neural network.
    Type: Grant
    Filed: July 22, 2019
    Date of Patent: October 27, 2020
    Assignee: Green Mountain Semiconductor, Inc.
    Inventors: Wolfgang Hokenmaier, Jacob Bucci, Ryan Jurasek
  • Artificial neural network functionality within dynamic random-access memory
    Patent number: 10360971
    Abstract: Techniques are disclosed for artificial neural network functionality within dynamic random-access memory. A plurality of dynamic random-access cells is accessed within a memory block. Data within the plurality of dynamic random-access cells is sensed using a plurality of sense amplifiers associated with the plurality of dynamic random-access cells. A plurality of select lines coupled to the plurality of sense amplifiers is activated to facilitate the sensing of the data within the plurality of dynamic random-access cells, wherein the activating is a function of inputs to a layer within a neural network, and wherein a bit within the plurality of dynamic random-access cells is sensed by a first sense amplifier and a second sense amplifier within the plurality of sense amplifiers. Resulting data is provided based on the activating wherein the resulting data is a function of weights within the neural network.
    Type: Grant
    Filed: April 24, 2018
    Date of Patent: July 23, 2019
    Assignee: Green Mountain Semiconductor, Inc.
    Inventors: Wolfgang Hokenmaier, Jacob Bucci, Ryan Jurasek