Cloud-Collaborative Microprocessor Reconfiguration for Performance Optimization
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Solution Overview
Problem
Microprocessor designers face challenges in achieving optimal performance across various software applications due to the need to choose between configurations optimized for one application at the expense of others, as existing solutions like hardcoded settings or dynamically reconfigurable microprocessors do not fully address the requirement for balanced performance optimization.
Innovation Solution
A system with dynamically configurable functional units that collects performance data, sends it to a server for analysis with other systems, and reconfigures based on aggregated best-performing settings, iteratively improving configuration settings for continuous performance optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a microprocessor is configured with hardcoded configuration settings optimized for one software application, then performance for that specific application is improved, but performance for other software applications deteriorates
Solution Approach 1:
The patent implements dynamic reconfiguration of microprocessor functional units through a configuration register that can be modified at runtime. The microprocessor transitions from static hardcoded configuration to dynamic configuration, allowing the system to adapt its architecture to match the requirements of different software applications executing on the processor.
Solution Approach 2:
The patent changes the parameters of functional units by modifying configuration registers that control operational characteristics of pipeline stages, execution units, and other microprocessor components. This allows continuous adjustment of microprocessor behavior to optimize performance for different workloads without requiring physical hardware changes.
2Ease of manufacture
If a microprocessor includes a bank of fuses for selective blowing during manufacturing to alter configuration settings, then limited optimization in manufacturing is achieved, but the ability to achieve optimal performance for target software applications deteriorates due to the need to choose a configuration optimized for some applications at the expense of others
Solution Approach 1:
The patent enables the microprocessor to self-optimize its configuration by automatically selecting and applying optimal configuration settings based on the characteristics of the software application being executed. The system monitors application behavior and dynamically adjusts functional unit configurations without external intervention, achieving continuous performance optimization.
Solution Approach 2:
The patent implements feedback mechanisms where performance data from multiple microprocessor instances is collected and analyzed to determine optimal configuration settings. This feedback loop allows the system to learn from real-world usage patterns and continuously improve configuration decisions, transitioning from static manufacturing-time configuration to dynamic runtime optimization based on empirical data.
3Adaptability or versatility
If a microprocessor uses a balanced configuration to attempt to satisfy multiple software applications, then adaptability across applications is improved, but performance for any specific application deteriorates due to compromise
Solution Approach 1:
The patent resolves this contradiction by making the configuration dynamic rather than static. Instead of selecting a fixed balanced configuration, the microprocessor continuously adapts its configuration based on the currently executing application's requirements, allowing it to achieve both high performance and broad adaptability through runtime reconfiguration.
Data Source
AI summary
A system includes functional units that are dynamically configurable during operation of the system. The system also includes a first module that collects performance data while the system executes a program with the functional units configured according to a configuration setting. The system also includes a second module that sends information to a server. The information includes the performance data, the configuration setting and data from which the program may be identified. The system also includes a third module that instructs the system to re-configure the functional units with a new configuration setting received from the server while the program is being executed by the system. The new configuration setting is based on analysis by the server of the information sent by the system and of similar information sent by other systems that include the dynamically configurable functional units.