Ati Technologies Ulc

Advanced Micro Devices Corporation

Mohammad Hamed Mousazadeh

Alexander S Duenas

Omer Irshad

Shahriar Pezeshgi

Jun Huang

Gabor Sines

Ian Charles Colbert

Ihab Amer

Arpit Nitinbhai Patel

Joohyun Lee

Muhammad Saad Musani

Xuetao Yan

Zongjie Yan

Philippe John Louis Yu

Stephen Jiacheng Fu

A processing device includes an automated overclocking system and a processor. The automated overclocking system is data-driven and includes an inference engine that executes a machine learning model configured to generate a first output based on a current configuration of the processing device. The first output includes a first set of overclocking parameters. The processor is configured to adjust one or more operating characteristics of at least one component of the processing device based on the first set of overclocking parameters.

Automated data-driven system to optimize overclocking

A processing apparatus is provided which includes memory configured to store hardware parameter settings for each of a plurality of applications. The processing apparatus also includes a processor in communication with the memory configured to store, in the memory, the hardware parameter settings, identify one of the plurality of applications as a currently executing application and control an operation of hardware by tuning a plurality of hardware parameters according to the stored hardware parameter settings for the identified application.

Application profiling for power-performance management

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.

Systems and methods for generating remedy recommendations for power and performance issues within semiconductor software and hardware

Techniques are described for adaptive device power management. The device interface application of a hardware computing unit detects a launch of an application by the operating system (OS) to be executed on the hardware computing unit, in an implementation. The device interface application identifies the launched application and determines whether a hardware profile exists that is associated with the application. The hardware profile includes one or more hardware parameters that yield the optimal performance for power consumption by the hardware computing unit when executing the launched application. Based on determining that the hardware profile exists, the power policy of the OS is updated for the launched application, and thereby, the driver updates the power state(s) of the hardware computing unit based on the new power policy.

Adaptive power management

Growing community of inventors

Markham, Canada

Mohammad Hamed Mousazadeh