Patents by Inventor Andrei PETRE

Andrei PETRE 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: 12210477
    Abstract: Systems and methods for improving cache efficiency and utilization are disclosed. In one embodiment, a graphics processor includes processing resources to perform graphics operations and a cache controller of a cache coupled to the processing resources. The cache controller is configured to control cache priority by determining whether default settings or an instruction will control cache operations for the cache.
    Type: Grant
    Filed: March 14, 2020
    Date of Patent: January 28, 2025
    Assignee: Intel Corporation
    Inventors: Altug Koker, Joydeep Ray, Ben Ashbaugh, Jonathan Pearce, Abhishek Appu, Vasanth Ranganathan, Lakshminarayanan Striramassarma, Elmoustapha Ould-Ahmed-Vall, Aravindh Anantaraman, Valentin Andrei, Nicolas Galoppo Von Borries, Varghese George, Yoav Harel, Arthur Hunter, Jr., Brent Insko, Scott Janus, Pattabhiraman K, Mike Macpherson, Subramaniam Maiyuran, Marian Alin Petre, Murali Ramadoss, Shailesh Shah, Kamal Sinha, Prasoonkumar Surti, Vikranth Vemulapalli
  • Publication number: 20230359770
    Abstract: A system allows the identification and protection of sensitive data in a multiple ways, which can be combined for different workflows, data situations or use cases. The system scans datasets to identify sensitive data or identifying datasets, and to enable the anonymisation of sensitive or identifying datasets by processing that data to produce a safe copy. Furthermore, the system prevents access to a raw dataset. The system enables privacy preserving aggregate queries and computations. The system uses differentially private algorithms to reduce or prevent the risk of identification or disclosure of sensitive information. The system scales to big data and is implemented in a way that supports parallel execution on a distributed compute cluster.
    Type: Application
    Filed: July 10, 2023
    Publication date: November 9, 2023
    Inventors: Jason Derek MCFALL, Charles Codman CABOT, Timothy James MORAN, Kieron Francois Pascal GUINAMARD, Vladimir Michael EATWELL, Benjamin Thomas PICKERING, Paul David MELLOR, Theresa STADLER, Andrei PETRE, Christopher Andrew SMITH, Anthony Jason DU PREEZ, Igor VUJOSEVIC, George DANEZIS
  • Patent number: 11698990
    Abstract: A system allows the identification and protection of sensitive data in a multiple ways, which can be combined for different workflows, data situations or use cases. The system scans datasets to identify sensitive data or identifying datasets, and to enable the anonymisation of sensitive or identifying datasets by processing that data to produce a safe copy. Furthermore, the system prevents access to a raw dataset. The system enables privacy preserving aggregate queries and computations. The system uses differentially private algorithms to reduce or prevent the risk of identification or disclosure of sensitive information. The system scales to big data and is implemented in a way that supports parallel execution on a distributed compute cluster.
    Type: Grant
    Filed: May 2, 2017
    Date of Patent: July 11, 2023
    Assignee: PRIVITAR LIMITED
    Inventors: Jason Derek McFall, Charles Codman Cabot, Timothy James Moran, Kieron Francois Pascal Guinamard, Vladimir Michael Eatwell, Benjamin Thomas Pickering, Paul David Mellor, Theresa Stadler, Andrei Petre, Christopher Andrew Smith, Anthony Jason Du Preez, Igor Vujosevic, George Danezis
  • Publication number: 20200327252
    Abstract: A system allows the identification and protection of sensitive data in a multiple ways, which can be combined for different workflows, data situations or use cases. The system scans datasets to identify sensitive data or identifying datasets, and to enable the anonymisation of sensitive or identifying datasets by processing that data to produce a safe copy. Furthermore, the system prevents access to a raw dataset. The system enables privacy preserving aggregate queries and computations. The system uses differentially private algorithms to reduce or prevent the risk of identification or disclosure of sensitive information. The system scales to big data and is implemented in a way that supports parallel execution on a distributed compute cluster.
    Type: Application
    Filed: May 2, 2017
    Publication date: October 15, 2020
    Inventors: Jason Derek MCFALL, Charles Codman CABOT, Timothy James MORAN, Kieron Francois Pascal GUINAMARD, Vladimir Michael EATWELL, Benjamin Thomas PICKERING, Paul David MELLOR, Theresa STADLER, Andrei PETRE, Christopher Andrew SMITH, Anthony Jason DU PREEZ, Igor VUJOSEVIC, George DANEZIS