Patents by Inventor Derssie Mebratu

Derssie Mebratu 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).

  • ADJUSTING WORKLOAD EXECUTION BASED ON WORKLOAD SIMILARITY
    Publication number: 20240134705
    Abstract: Adjusting workload execution based on workload similarity. A processor may determine a similarity of a first workload to a second workload. The processor may adjust execution of the first workload based on execution parameters of the second workload and the similarity of the first workload to the second workload.
    Type: Application
    Filed: December 13, 2023
    Publication date: April 25, 2024
    Applicant: Intel Corporation
    Inventors: Niranjan Hasabnis, Patricia Mwove, Ellick Chan, Derssie Mebratu, Kshitij Doshi, Mohammad Hossain, Gaurav Chaudhary
  • Technologies for predicting computer hardware performance with machine learning
    Patent number: 11609810
    Abstract: Technologies for predicting computer hardware performance with machine learning are disclosed. Analysis of telemetry data through machine learning and statistical modeling is used to determine whether various components of a compute device such as a fan or memory are failing or are otherwise potentially impacting performance of the compute device. For example, machine-learning-based algorithms may be used to determine an impact of a latency of memory accesses may have on time to execute workloads.
    Type: Grant
    Filed: December 7, 2018
    Date of Patent: March 21, 2023
    Assignee: Intel Corporation
    Inventors: Samantha Alt, Derssie Mebratu, Nishi Ahuja
  • TECHNOLOGIES FOR PREDICTING COMPUTER HARDWARE PERFORMANCE WITH MACHINE LEARNING
    Publication number: 20190147364
    Abstract: Technologies for predicting computer hardware performance with machine learning are disclosed. Analysis of telemetry data through machine learning and statistical modeling is used to determine whether various components of a compute device such as a fan or memory are failing or are otherwise potentially impacting performance of the compute device. For example, machine-learning-based algorithms may be used to determine an impact of a latency of memory accesses may have on time to execute workloads.
    Type: Application
    Filed: December 7, 2018
    Publication date: May 16, 2019
    Inventors: Samantha Alt, Derssie Mebratu, Nishi Ahuja