Patents by Inventor Diana Jeanne Arroyo
Diana Jeanne Arroyo 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: 11727309Abstract: Techniques for estimating runtimes of one or more machine learning tasks are provided. For example, one or more embodiments described herein can regard a system that can comprise a memory that stores computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise an extraction component that can extract a parameter from a machine learning task. The parameter can define a performance characteristic of the machine learning task. Also, the computer executable components can comprise a model component that can generate a model based on the parameter. Further, the computer executable components can comprise an estimation component that can generate an estimated runtime of the machine learning task based on the model.Type: GrantFiled: October 28, 2021Date of Patent: August 15, 2023Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Parijat Dube, Gauri Joshi, Priya Ashok Nagpurkar, Stefania Costache, Diana Jeanne Arroyo, Zehra Noman Sura
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Publication number: 20230214257Abstract: Systems, computer-implemented methods, and computer program products to facilitate using multiple quota trees in resource scheduling are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components comprise an evaluation component that executes admissibility of a job request based on a scope property of one or more quota trees that apply to the job request.Type: ApplicationFiled: January 5, 2022Publication date: July 6, 2023Inventors: Lior Aronovich, Alaa S. Youssef, Asser Nasreldin Tantawi, Diana Jeanne Arroyo, Marius Ion Danciu
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Publication number: 20230214267Abstract: Systems, computer-implemented methods, and computer program products to facilitate optimization of resource usage based on quota trees are provided. According to an embodiment, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components comprise a determination component that determines one or more quota trees that classify a job request as inadmissible. The computer executable components further comprise an optimization component that optimizes resource usage to enable admissibility of the job request based on the one or more quota trees.Type: ApplicationFiled: January 5, 2022Publication date: July 6, 2023Inventors: Lior Aronovich, Alaa S. Youssef, Asser Nasreldin Tantawi, Diana Jeanne Arroyo, Marius Ion Danciu
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Publication number: 20220051142Abstract: Techniques for estimating runtimes of one or more machine learning tasks are provided. For example, one or more embodiments described herein can regard a system that can comprise a memory that stores computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise an extraction component that can extract a parameter from a machine learning task. The parameter can define a performance characteristic of the machine learning task. Also, the computer executable components can comprise a model component that can generate a model based on the parameter. Further, the computer executable components can comprise an estimation component that can generate an estimated runtime of the machine learning task based on the model.Type: ApplicationFiled: October 28, 2021Publication date: February 17, 2022Inventors: Parijat Dube, Gauri Joshi, Priya Ashok Nagpurkar, Stefania Costache, Diana Jeanne Arroyo, Zehra Noman Sura
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Patent number: 11200512Abstract: Techniques for estimating runtimes of one or more machine learning tasks are provided. For example, one or more embodiments described herein can regard a system that can comprise a memory that stores computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise an extraction component that can extract a parameter from a machine learning task. The parameter can define a performance characteristic of the machine learning task. Also, the computer executable components can comprise a model component that can generate a model based on the parameter. Further, the computer executable components can comprise an estimation component that can generate an estimated runtime of the machine learning task based on the model.Type: GrantFiled: February 21, 2018Date of Patent: December 14, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Parijat Dube, Gauri Joshi, Priya Ashok Nagpurkar, Stefania Costache, Diana Jeanne Arroyo, Zehra Noman Sura
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Publication number: 20190258964Abstract: Techniques for estimating runtimes of one or more machine learning tasks are provided. For example, one or more embodiments described herein can regard a system that can comprise a memory that stores computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise an extraction component that can extract a parameter from a machine learning task. The parameter can define a performance characteristic of the machine learning task. Also, the computer executable components can comprise a model component that can generate a model based on the parameter. Further, the computer executable components can comprise an estimation component that can generate an estimated runtime of the machine learning task based on the model.Type: ApplicationFiled: February 21, 2018Publication date: August 22, 2019Inventors: Parijat Dube, Gauri Joshi, Priya Ashok Nagpurkar, Stefania Victoria Costache, Diana Jeanne Arroyo, Zehra Noman Sura
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Patent number: 9110729Abstract: Systems and methods for admission control to a physical host system are provided herein. One aspect provides for receiving at least one resource request at an admission control component of a distributed computing system, the at least one resource request comprised of at least one system type; processing the at least one resource request utilizing at least one physical host accessible to the distributed computing system; specifying a number of resource request slots to be reserved for at least one system type based on at least one future reservation threshold accessible to the admission control component; and blocking resource requests from entering the system through the admission control component based on a number of available resource request slots and the at least one future reservation threshold. Other embodiments and aspects are also described herein.Type: GrantFiled: February 17, 2012Date of Patent: August 18, 2015Assignee: International Business Machines CorporationInventors: Diana Jeanne Arroyo, Zohar Feldman, Michael Masin, Malgorzata Steinder, Asser Nasreldin Tantawi, Ian Nicholas Whalley
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Publication number: 20130219066Abstract: Systems and methods for admission control to a physical host system are provided herein. One aspect provides for receiving at least one resource request at an admission control component of a distributed computing system, the at least one resource request comprised of at least one system type; processing the at least one resource request utilizing at least one physical host accessible to the distributed computing system; specifying a number of resource request slots to be reserved for at least one system type based on at least one future reservation threshold accessible to the admission control component; and blocking resource requests from entering the system through the admission control component based on a number of available resource request slots and the at least one future reservation threshold. Other embodiments and aspects are also described herein.Type: ApplicationFiled: February 17, 2012Publication date: August 22, 2013Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Diana Jeanne Arroyo, Zohar Feldman, Michael Masin, Malgorzata Steinder, Asser Nasreldin Tantawi, Ian Nicholas Whalley