Patents by Inventor Siddharth Sharma
Siddharth Sharma 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).
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Patent number: 11928558Abstract: A request is received associated with a review. Within first content, a first field of interest and a second field of interest are identified and within second content, a third field of interest and a fourth field of interest are identified. A review is generated that includes a first indication of the first field of interest and a second indication of the second field of interest within the first content, as well as a third indication of the third field of interest and a fourth indication of the fourth field of interest within the second content. The review is transmitted to a device of a reviewer for reviewing the content.Type: GrantFiled: November 29, 2019Date of Patent: March 12, 2024Assignee: Amazon Technologies, Inc.Inventors: Siddharth Vivek Joshi, Anuj Gupta, Mark Chien, Jonathan Thomas Greenlee, Stefano Stefani, Warren Barkley, Jon I. Turow, Sindhu Chejerla, Kriti Bharti, Prateek Sharma
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Publication number: 20240062003Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing natural language processing operations by generating semantic table representations for table data objects using a token-wise entity type classification mechanism whose output space is defined by a set of defined entity types characterized by an inter-related entity type taxonomy to generate a representation of a table data object that describes per-token semantic inferences and cross-token semantic inferences performed on the table data object in accordance with subject-matter-domain insights as described by the inter-related entity type taxonomy.Type: ApplicationFiled: August 22, 2022Publication date: February 22, 2024Inventors: Mrityunjai Singh, Aviral Sharma, Jatin Lamba, Shreyansh S. Nanawati, Deeksha Thareja, Siddharth Sharma
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Patent number: 11886912Abstract: Data processing approaches are disclosed that include receiving a configuration indicating a plurality of parameters for performing a data processing job, identifying available compute resources from a plurality of public cloud infrastructures, where each public cloud infrastructure of the plurality of public cloud infrastructures supports one or more computing applications, one or more job schedulers, and one or more utilization rates, selecting one or more compute clusters from one or more of the plurality of public cloud infrastructures based on a matching process between the parameters for performing the data processing job and a combination of the one or more computing applications, the one or more job schedulers, and the one or more utilization rates, and initiating the one or more compute clusters for processing the data processing job based on the selecting.Type: GrantFiled: January 29, 2021Date of Patent: January 30, 2024Assignee: Salesforce Inc.Inventors: Amit Martu Kamat, Siddharth Sharma, Raveendrnathan Loganathan, Anil Raju Puliyeril, Kenneth Siu
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Publication number: 20230297485Abstract: Various embodiments include a system for generating performance monitoring data in a computing system. The system includes a unit level counter with a set of counters, where each counter increments during each clock cycle in which a corresponding electronic signal is at a first state, such as a high or low logic level state. Periodically, the unit level counter transmits the counter values to a corresponding counter collection unit. The counter collection unit includes a set of counters that aggregates the values of the counters in multiple unit level counters. Based on certain trigger conditions, the counter collection unit transmits records to a reduction channel. The reduction channel includes a set of counters that aggregates the values of the counters in multiple counter collection units. Each virtual machine executing on the system can access a different corresponding reduction channel, providing secure performance metric data for each virtual machine.Type: ApplicationFiled: March 18, 2022Publication date: September 21, 2023Inventors: Pranav VAIDYA, Alan MENEZES, Siddharth SHARMA, Jin OUYANG, Gregory Paul SMITH, Timothy J. MCDONALD, Shounak KAMALAPURKAR, Abhijat RANADE, Thomas Melvin OGLETREE
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Publication number: 20230007920Abstract: Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.Type: ApplicationFiled: September 15, 2022Publication date: January 12, 2023Inventors: Rouslan L. Dimitrov, Dale L. Kirkland, Emmett M. Kilgariff, Sachin Satish Idgunji, Siddharth Sharma
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Publication number: 20220398291Abstract: Methods, systems, apparatuses, and computer-readable storage mediums described herein are directed to techniques for smart browser history searching. For example, a user may submit natural language-based search queries to a browser application, which searches for various textual features of web pages maintained by a browser's history, as well as various entity object types included on such web pages based on the search queries. The entity object types include various content included on the web pages, including, but not limited to, products, images, and videos. The browser application also searches for textual features and/or entity object types having a semantic similarity to the search terms of the search queries, thereby providing an advanced search that not only aims to locate web pages based on exact keywords, but also based on the intent and contextual significance of the search terms specified by the user.Type: ApplicationFiled: November 18, 2021Publication date: December 15, 2022Inventors: Tulasi MENON, Laalithya BODDAPATI, Parinishtha YADAV, Prasenjit MUKHERJEE, Siddharth SHARMA
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Patent number: 11481950Abstract: Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.Type: GrantFiled: January 29, 2021Date of Patent: October 25, 2022Assignee: NVIDIA CorporationInventors: Rouslan L. Dimitrov, Dale L. Kirkland, Emmett M. Kilgariff, Sachin Satish Idgunji, Siddharth Sharma
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Publication number: 20220121488Abstract: Data processing approaches are disclosed that include receiving a configuration indicating a plurality of parameters for performing a data processing job, identifying available compute resources from a plurality of public cloud infrastructures, where each public cloud infrastructure of the plurality of public cloud infrastructures supports one or more computing applications, one or more job schedulers, and one or more utilization rates, selecting one or more compute clusters from one or more of the plurality of public cloud infrastructures based on a matching process between the parameters for performing the data processing job and a combination of the one or more computing applications, the one or more job schedulers, and the one or more utilization rates, and initiating the one or more compute clusters for processing the data processing job based on the selecting.Type: ApplicationFiled: January 29, 2021Publication date: April 21, 2022Inventors: Amit Martu Kamat, Siddharth Sharma, Raveendrnathan Loganathan, Anil Raju Puliyeril, Kenneth Siu
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Publication number: 20210174569Abstract: Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.Type: ApplicationFiled: January 29, 2021Publication date: June 10, 2021Inventors: Rouslan L. Dimitrov, Dale L. Kirkland, Emmett M. Kilgariff, Sachin Satish Idgunji, Siddharth Sharma
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Patent number: 10909738Abstract: Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.Type: GrantFiled: January 5, 2018Date of Patent: February 2, 2021Assignee: NVIDIA CorporationInventors: Rouslan L. Dimitrov, Dale L. Kirkland, Emmett M. Kilgariff, Sachin Satish Idgunji, Siddharth Sharma
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Patent number: 10809986Abstract: An system and a method for the optimization of dynamic code translation is disclosed. A cloud-based front-end application receives an input module, rule specification and a translation definition. The cloud-based front-end application transmits the input module, rule specification and translation definition to a back-end processing module. The back-end processing module parses the three inputs and stores them in separate data structures. The back-end processing module performs a non-executing analysis of the translation definition based on the rule specification, generating a set of defects. The back-end processing module performs an execution of the translation definition with the input module, generating a report of system metrics. The set of defects and the system metrics are transmitted back to a GUI running on the cloud-based front-end application.Type: GrantFiled: June 4, 2018Date of Patent: October 20, 2020Assignee: Walmart Apollo, LLCInventors: Madhavan Kalkunte Ramachandra, Siddharth Sharma
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Publication number: 20190317745Abstract: An system and a method for the optimization of dynamic code translation is disclosed. A cloud-based front-end application receives an input module, rule specification and a translation definition. The cloud-based front-end application transmits the input module, rule specification and translation definition to a back-end processing module. The back-end processing module parses the three inputs and stores them in separate data structures. The back-end processing module performs a non-executing analysis of the translation definition based on the rule specification, generating a set of defects. The back-end processing module performs an execution of the translation definition with the input module, generating a report of system metrics. The set of defects and the system metrics are transmitted back to a GUI running on the cloud-based front-end application.Type: ApplicationFiled: June 4, 2018Publication date: October 17, 2019Inventors: Kr Madhavan, Siddharth Sharma
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Publication number: 20190213775Abstract: Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.Type: ApplicationFiled: January 5, 2018Publication date: July 11, 2019Inventors: Rouslan L. Dimitrov, Dale L. Kirkland, Emmett M. Kilgariff, Sachin Satish Idgunji, Siddharth Sharma
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Patent number: 10339039Abstract: A virtualization request is identified to initiate a virtualized transaction involving a first software component and a virtual service simulating a second software component. A reference within the first software component to the second software component is determined, using a plugin installed on the first software component, that is to be used by the first software component to determine a first network location of the second software component. A second network location of a system to host the virtual service is determined and the reference is changed, using the plugin, to direct communications of the first software component to the second network location instead of the first network location responsive to the virtualization request.Type: GrantFiled: January 25, 2017Date of Patent: July 2, 2019Assignee: CA, Inc.Inventors: Rajesh M. Raheja, Dhruv Mevada, Siddharth Sharma, Stephy Nancy Francis Xavier
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Publication number: 20180210745Abstract: A virtualization request is identified to initiate a virtualized transaction involving a first software component and a virtual service simulating a second software component. A reference within the first software component to the second software component is determined, using a plugin installed on the first software component, that is to be used by the first software component to determine a first network location of the second software component. A second network location of a system to host the virtual service is determined and the reference is changed, using the plugin, to direct communications of the first software component to the second network location instead of the first network location responsive to the virtualization request.Type: ApplicationFiled: January 25, 2017Publication date: July 26, 2018Inventors: Rajesh M. Raheja, Dhruv Mevada, Siddharth Sharma, Stephy Nancy Francis Xavier
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Publication number: 20130226944Abstract: Data transformation can be performed across various data structures and formats. Moreover, data transformation can be format agnostic. Output data of a second structure can be generated as a function of input data of a first structure and a transform independent of the format of input and output data. In one instance, the transform can be specified by way of a graphical representation and encoded in a form independent of input and output data formats. Subsequently, data transformation can be performed as a function of the transform and input data.Type: ApplicationFiled: February 24, 2012Publication date: August 29, 2013Applicant: Microsoft CorporationInventors: Sushil Baid, Kranthi K. Mannem, Palavalli R. Sharath, Anil K. Prasad, Siddharth Sharma, Krishnan Srinivasan