View source for Advanced micro devices, inc. (20240111620). SYSTEMS AND METHODS FOR GENERATING REMEDY RECOMMENDATIONS FOR POWER AND PERFORMANCE ISSUES WITHIN SEMICONDUCTOR SOFTWARE AND HARDWARE simplified abstract

=SYSTEMS AND METHODS FOR GENERATING REMEDY RECOMMENDATIONS FOR POWER AND PERFORMANCE ISSUES WITHIN SEMICONDUCTOR SOFTWARE AND HARDWARE=


==Organization Name==

[[:Category:advanced micro devices, inc.|advanced micro devices, inc.]]


[[Category:advanced micro devices, inc.]]

==Inventor(s)==

[[:Category:Mohammad Hamed Mousazadeh of Markham (CA)|Mohammad Hamed Mousazadeh of Markham (CA)]][[Category:Mohammad Hamed Mousazadeh of Markham (CA)]]

[[:Category:Arpit Patel of Markham (CA)|Arpit Patel of Markham (CA)]][[Category:Arpit Patel of Markham (CA)]]

[[:Category:Gabor Sines of Markham (CA)|Gabor Sines of Markham (CA)]][[Category:Gabor Sines of Markham (CA)]]

[[:Category:Omer Irshad of Markham (CA)|Omer Irshad of Markham (CA)]][[Category:Omer Irshad of Markham (CA)]]

[[:Category:Phillippe John Louis Yu of Markham (CA)|Phillippe John Louis Yu of Markham (CA)]][[Category:Phillippe John Louis Yu of Markham (CA)]]

[[:Category:Zongjie Yan of Markham (CA)|Zongjie Yan of Markham (CA)]][[Category:Zongjie Yan of Markham (CA)]]

[[:Category:Ian Charles Colbert of San Diego CA (US)|Ian Charles Colbert of San Diego CA (US)]][[Category:Ian Charles Colbert of San Diego CA (US)]]

==SYSTEMS AND METHODS FOR GENERATING REMEDY RECOMMENDATIONS FOR POWER AND PERFORMANCE ISSUES WITHIN SEMICONDUCTOR SOFTWARE AND HARDWARE - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240111620 titled 'SYSTEMS AND METHODS FOR GENERATING REMEDY RECOMMENDATIONS FOR POWER AND PERFORMANCE ISSUES WITHIN SEMICONDUCTOR SOFTWARE AND HARDWARE

==Simplified Explanation==

The disclosed computer-implemented method involves generating remedy recommendations for power and performance issues within semiconductor software and hardware. This includes applying rule-based and machine learning models to telemetry data to identify and address failures specific to the client computing device.

* Rule-based and machine learning models are used to analyze telemetry data for power and performance issues in semiconductor software and hardware.
* The method generates rule-based root-cause outputs and telemetry-based unknown outputs to identify failure patterns.
* By applying a root-cause machine learning model to the telemetry-based unknown outputs, specific remedy recommendations are generated for the identified failures and client computing devices.

== Potential Applications ==
This technology could be applied in:
* Semiconductor manufacturing
* Computer hardware troubleshooting
* Software development for optimized performance

== Problems Solved ==
This technology helps in:
* Identifying root causes of power and performance issues
* Providing specific remedy recommendations for failures
* Improving overall efficiency and performance of semiconductor software and hardware

== Benefits ==
The benefits of this technology include:
* Faster identification and resolution of power and performance issues
* Tailored remedy recommendations for specific failures
* Enhanced performance and reliability of semiconductor devices

== Potential Commercial Applications ==
This technology could be commercially applied in:
* Semiconductor companies
* IT support services
* Computer hardware manufacturers

== Possible Prior Art ==
One possible prior art could be the use of rule-based models in analyzing telemetry data for identifying failures in computing devices. Additionally, machine learning models have been used in various industries for pattern recognition and analysis.

=== What are the limitations of this technology in real-world applications? ===

The limitations of this technology in real-world applications may include:
* The need for extensive and accurate telemetry data for effective analysis
* Potential challenges in integrating the remedy recommendations into existing systems

=== How does this technology compare to traditional methods of identifying and resolving power and performance issues in semiconductor devices? ===

This technology offers a more advanced and data-driven approach compared to traditional methods, allowing for more accurate and specific remedy recommendations based on deep analysis of telemetry data.


==Original Abstract Submitted==

the disclosed computer-implemented method for generating remedy recommendations for power and performance issues within semiconductor software and hardware. for example, the disclosed systems and methods can apply a rule-based model to telemetry data to generate rule-based root-cause outputs as well as telemetry-based unknown outputs. the disclosed systems and methods can further apply a root-cause machine learning model to the telemetry-based unknown outputs to analyze deep and complex failure patterns with the telemetry-based unknown outputs to ultimately generate one or more root-cause remedy recommendations that are specific to the identified failure and the client computing device that is experiencing that failure.



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