Run-Time Firmware Calibration for Adaptive Hardware Tuning
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Solution Overview
Problem
Computing systems often operate with hard-coded tuning parameters that are not optimal for specific system configurations and operating conditions, leading to inefficiencies in performance and energy consumption.
Innovation Solution
Implementing run time firmware calibration that adjusts tuning parameters based on real-time sensor data to optimize system performance and energy efficiency for specific conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If hard-coded tuning parameters with nominal values are used to accommodate a range of system configurations, then the system can operate across diverse conditions, but the parameters are not optimal for any specific configuration or operating condition
Solution Approach 1:
The patent implements dynamic tuning parameters that can be adjusted at runtime based on actual operating conditions. The system transitions from static hard-coded parameters to dynamic parameters that adapt to specific configurations and conditions, resolving the contradiction between versatility and performance efficiency.
Solution Approach 2:
The system changes parameter values based on detected operating conditions and system configurations. By monitoring sensors and adjusting parameters in real-time, the system optimizes performance for specific configurations while maintaining the ability to adapt to various conditions, thus resolving the contradiction between adaptability and efficiency.
2Productivity
If multiple predefined tuning configurations are stored to optimize for different system configurations, then optimal performance for specific conditions can be achieved, but the storage requirements and system complexity increase
Solution Approach 1:
The system performs self-calibration by automatically detecting its own configuration and operating conditions, then adjusting its parameters accordingly. This eliminates the need for extensive predefined configuration tables, reducing storage requirements while maintaining optimization capabilities.
Solution Approach 2:
The system uses sensor feedback to continuously monitor operating conditions and adjusts parameters based on this feedback. This closed-loop approach allows the system to optimize performance dynamically without requiring pre-stored configurations for every possible condition, thereby reducing complexity.
3Productivity
If runtime calibration is implemented to optimize parameters for specific conditions, then performance and energy efficiency improve, but additional calibration workloads and processing are required
Solution Approach 1:
The system performs calibration workloads and parameter optimization in advance, during system initialization or idle periods, before actual operational workloads begin. This preliminary calibration ensures optimal parameters are ready when needed, minimizing the impact on operational time while achieving energy efficiency improvements.
Data Source
AI summary
Run time firmware calibration is described. An example system includes one or more hardware components and a system manager. The system manager is configured to operate the one or more hardware components according to a tuning configuration, execute a calibration workload while adjusting one or more parameters of the tuning configuration, generate an updated tuning configuration that includes adjusted values of the one or more parameters, and operate the one or more hardware components according to the updated tuning configuration.