Patents by Inventor Aditya N. Puranik

Aditya N. Puranik 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).

  • Patent number: 10417252
    Abstract: Embodiments of the present invention provide systems and methods for increasing the efficiency of data conversion in a coprocessor by using the statistical occurrence of data patterns to convert frequently occurring data patterns in one conversion cycle. In one embodiment, a coprocessor system is disclosed containing a converter engine, which includes a parser and a converter, an input buffer, and a result store. The input buffer is configured to transfer a set of source data to the converter engine, which converts the source data from first code format to a second code format, and sends the converted source data to the result store.
    Type: Grant
    Filed: November 3, 2015
    Date of Patent: September 17, 2019
    Assignee: International Business Machines Corporation
    Inventors: Markus M. Helms, Christian Jacobi, Aditya N. Puranik, Parminder Singh
  • Publication number: 20190243894
    Abstract: A method, computer program product, and system includes a processor obtaining data including values and generating a value conversion dictionary by applying a parse tree based compression algorithm to the data, where the value conversion dictionary includes dictionary entries that represent the values. The processor obtains a distribution of the values and estimates a likelihood for each based on the distribution. The processor generates a code word to represent each value, a size of each code word is inversely proportional to the likelihood of the word. The processor assigns a rank to each code word, the rank for each represents the likelihood of the value represented by the code word; and based on the rank associated with each code word, the processor reorders each dictionary entry in the value conversion dictionary to associate each dictionary entry with an equivalent rank, the reordered value conversion dictionary comprises an architected dictionary.
    Type: Application
    Filed: April 15, 2019
    Publication date: August 8, 2019
    Inventors: Jonathan D. Bradbury, Markus Helms, Christian Jacobi, Aditya N. Puranik, Christian Zoellin
  • Patent number: 10303759
    Abstract: A method, computer program product, and system includes a processor obtaining data including values and generating a value conversion dictionary by applying a parse tree based compression algorithm to the data, where the value conversion dictionary includes dictionary entries that represent the values. The processor obtains a distribution of the values and estimates a likelihood for each based on the distribution. The processor generates a code word to represent each value, a size of each code word is inversely proportional to the likelihood of the word. The processor assigns a rank to each code word, the rank for each represents the likelihood of the value represented by the code word; and based on the rank associated with each code word, the processor reorders each dictionary entry in the value conversion dictionary to associate each dictionary entry with an equivalent rank, the reordered value conversion dictionary comprises an architected dictionary.
    Type: Grant
    Filed: December 3, 2015
    Date of Patent: May 28, 2019
    Assignee: International Business Machines Corporation
    Inventors: Jonathan D. Bradbury, Markus Helms, Christian Jacobi, Aditya N. Puranik, Christian Zoellin
  • Patent number: 9716515
    Abstract: Modifying a digital data stream that includes immediately consecutive code words of different length by segmenting, based on a certain block grid, the digital data stream. Each block of the block grid includes a fixed number of bits. It is determined whether all bits of the last block associated with the digital data stream are occupied by data of the digital data stream. If not all bits of the last block are occupied, the unoccupied bits of the last block are padded with bits of an end-of-record (EOR) indicator. If all bits of the last block are occupied, attaching an EOR indicator to the digital data stream is skipped.
    Type: Grant
    Filed: December 14, 2015
    Date of Patent: July 25, 2017
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Deepankar Bhattacharjee, Jonathan D. Bradbury, Christian Jacobi, Aditya N. Puranik, Christian Zoellin
  • Publication number: 20170170844
    Abstract: Modifying a digital data stream that includes immediately consecutive code words of different length by segmenting, based on a certain block grid, the digital data stream. Each block of the block grid includes a fixed number of bits. It is determined whether all bits of the last block associated with the digital data stream are occupied by data of the digital data stream. If not all bits of the last block are occupied, the unoccupied bits of the last block are padded with bits of an end-of-record (EOR) indicator. If all bits of the last block are occupied, attaching an EOR indicator to the digital data stream is skipped.
    Type: Application
    Filed: December 14, 2015
    Publication date: June 15, 2017
    Inventors: Deepankar Bhattacharjee, Jonathan D. Bradbury, Christian Jacobi, Aditya N. Puranik, Christian Zoellin
  • Patent number: 9680653
    Abstract: An instruction to perform ciphering and authentication is executed. The executing includes ciphering one set of data provided by the instruction to obtain ciphered data and placing the ciphered data in a designated location. It further includes authenticating an additional set of data provided by the instruction, in which the authenticating generates at least a part of a message authentication tag. The at least a part of the message authentication tag is stored in a selected location.
    Type: Grant
    Filed: October 13, 2016
    Date of Patent: June 13, 2017
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Jonathan D. Bradbury, Reinhard T. Buendgen, Dan F. Greiner, Christian Jacobi, Volodymyr Paprotski, Aditya N. Puranik, Timothy J. Slegel, Tamas Visegrady, Christian Zoellin
  • Publication number: 20170161362
    Abstract: A method, computer program product, and system includes a processor obtaining data including values and generating a value conversion dictionary by applying a parse tree based compression algorithm to the data, where the value conversion dictionary includes dictionary entries that represent the values. The processor obtains a distribution of the values and estimates a likelihood for each based on the distribution. The processor generates a code word to represent each value, a size of each code word is inversely proportional to the likelihood of the word. The processor assigns a rank to each code word, the rank for each represents the likelihood of the value represented by the code word; and based on the rank associated with each code word, the processor reorders each dictionary entry in the value conversion dictionary to associate each dictionary entry with an equivalent rank, the reordered value conversion dictionary comprises an architected dictionary.
    Type: Application
    Filed: December 3, 2015
    Publication date: June 8, 2017
    Inventors: Jonathan D. BRADBURY, Markus HELMS, Christian JACOBI, Aditya N. PURANIK, Christian ZOELLIN
  • Publication number: 20170163283
    Abstract: A method, computer program product, and system includes a processor obtaining data including values and generating a value conversion dictionary by applying a parse tree based compression algorithm to the data, where the value conversion dictionary includes dictionary entries that represent the values. The processor obtains a distribution of the values and estimates a likelihood for each based on the distribution. The processor generates a code word to represent each value, a size of each code word is inversely proportional to the likelihood of the word. The processor assigns a rank to each code word, the rank for each represents the likelihood of the value represented by the code word; and based on the rank associated with each code word, the processor reorders each dictionary entry in the value conversion dictionary to associate each dictionary entry with an equivalent rank, the reordered value conversion dictionary comprises an architected dictionary.
    Type: Application
    Filed: July 29, 2016
    Publication date: June 8, 2017
    Inventors: Jonathan D. BRADBURY, Markus HELMS, Christian JACOBI, Aditya N. PURANIK, Christian ZOELLIN
  • Publication number: 20160125055
    Abstract: Embodiments of the present invention provide systems and methods for increasing the efficiency of data conversion in a coprocessor by using the statistical occurrence of data patterns to convert frequently occurring data patterns in one conversion cycle. In one embodiment, a coprocessor system is disclosed containing a converter engine, which includes a parser and a converter, an input buffer, and a result store. The input buffer is configured to transfer a set of source data to the converter engine, which converts the source data from first code format to a second code format, and sends the converted source data to the result store.
    Type: Application
    Filed: November 5, 2014
    Publication date: May 5, 2016
    Inventors: Markus M. Helms, Christian Jacobi, Aditya N. Puranik, Parminder Singh
  • Publication number: 20160124732
    Abstract: Embodiments of the present invention provide systems and methods for increasing the efficiency of data conversion in a coprocessor by using the statistical occurrence of data patterns to convert frequently occurring data patterns in one conversion cycle. In one embodiment, a coprocessor system is disclosed containing a converter engine, which includes a parser and a converter, an input buffer, and a result store. The input buffer is configured to transfer a set of source data to the converter engine, which converts the source data from first code format to a second code format, and sends the converted source data to the result store.
    Type: Application
    Filed: November 3, 2015
    Publication date: May 5, 2016
    Inventors: Markus M. Helms, Christian Jacobi, Aditya N. Puranik, Parminder Singh