Patents by Inventor Soumya Gollamudi

Soumya Gollamudi 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).

  • Publication number: 20220188108
    Abstract: A method includes receiving an input data at a floating point arithmetic operating unit, wherein the floating point operating unit is configured to perform a floating point arithmetic operation on the input data to generate an output result. The method also includes determining whether the output result is going to cause a floating point hardware exception responsive to the floating point arithmetic operation on the input data. The method further includes converting a value of the output result to a modified value responsive to the determining that the output result is going to cause the floating point hardware exception, wherein the modified value eliminates the floating point hardware exception responsive to the floating point arithmetic operation on the input data.
    Type: Application
    Filed: March 4, 2022
    Publication date: June 16, 2022
    Inventors: Chia-Hsin Chen, Avinash Sodani, Ulf Hanebutte, Rishan Tan, Soumya Gollamudi
  • Publication number: 20220188110
    Abstract: A method includes receiving a first input data and a second input data at a floating point arithmetic operating unit, wherein the first input data and the second input data are associated with operands of a floating point arithmetic operation respectively, wherein the floating point operating unit is configured to perform a floating point arithmetic operation on the first input data and the second input data. The method further includes determining whether the first input data is a qnan (quiet not-a-number) or whether the first input data is an snan (signaling not-a-number) prior to performing the floating point arithmetic operation. A value of the first input data is modified prior to performing the floating point arithmetic operation if the first input data is either qnan or snan, wherein the converting eliminates special handling associated with the floating point arithmetic operation on the first input data being either qnan or snan.
    Type: Application
    Filed: March 4, 2022
    Publication date: June 16, 2022
    Inventors: Chia-Hsin Chen, Avinash Sodani, Ulf Hanebutte, Rishan Tan, Soumya Gollamudi
  • Publication number: 20220188111
    Abstract: A method includes receiving an input data at a floating point arithmetic operating unit, wherein the floating point operating unit is configured to perform a floating point arithmetic operation on the input data. The method also includes determining whether the received input data is positive infinity or negative infinity prior to performing the floating point arithmetic operation. The method further includes converting a value of the received input data to a modified value prior to performing the floating point arithmetic operation if the received input data is positive infinity or negative infinity.
    Type: Application
    Filed: March 4, 2022
    Publication date: June 16, 2022
    Inventors: Chia-Hsin Chen, Avinash Sodani, Ulf Hanebutte, Rishan Tan, Soumya Gollamudi
  • Publication number: 20220188109
    Abstract: A method includes receiving an input data at a floating point arithmetic operating unit, wherein the floating point operating unit is configured to perform a floating point arithmetic operation on the input data. The method includes determining whether the received input data is a qnan (quiet not-a-number) or whether the received input data is an snan (signaling not-a-number) prior to performing the floating point arithmetic operation. The method also includes converting a value of the received input data to a modified value prior to performing the floating point arithmetic operation if the received input data is either qnan or snan, wherein the converting eliminates special handling associated with the floating point arithmetic operation on the input data being either qnan or snan.
    Type: Application
    Filed: March 4, 2022
    Publication date: June 16, 2022
    Inventors: Chia-Hsin Chen, Avinash Sodani, Ulf Hanebutte, Rishan Tan, Soumya Gollamudi
  • Patent number: 11301247
    Abstract: A method includes receiving an input data at a FP arithmetic operating unit configured to perform a FP arithmetic operation on the input data. The method further includes determining whether the received input data generates a FP hardware exception responsive to the FP arithmetic operation on the input data, wherein the determining occurs prior to performing the FP arithmetic operation. The method also includes converting a value of the received input data to a modified value responsive to the determining that the received input data generates the FP hardware exception, wherein the converting eliminates generation of the FP hardware exception responsive to the FP arithmetic operation on the input data.
    Type: Grant
    Filed: April 30, 2020
    Date of Patent: April 12, 2022
    Assignee: Marvell Asia Pte Ltd
    Inventors: Chia-Hsin Chen, Avinash Sodani, Ulf Hanebutte, Rishan Tan, Soumya Gollamudi
  • Publication number: 20210191719
    Abstract: A method includes receiving an input data at a FP arithmetic operating unit configured to perform a FP arithmetic operation on the input data. The method further includes determining whether the received input data generates a FP hardware exception responsive to the FP arithmetic operation on the input data, wherein the determining occurs prior to performing the FP arithmetic operation. The method also includes converting a value of the received input data to a modified value responsive to the determining that the received input data generates the FP hardware exception, wherein the converting eliminates generation of the FP hardware exception responsive to the FP arithmetic operation on the input data.
    Type: Application
    Filed: April 30, 2020
    Publication date: June 24, 2021
    Inventors: Chia-Hsin Chen, Avinash Sodani, Ulf Hanebutte, Rishan Tan, Soumya Gollamudi