Node Power Architecture for Dynamic Processor State Management
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Solution Overview
Problem
There is a need for an improved method to effectively manage and control power in portable computing devices as their increased functionality and processing power requirements become more complex, necessitating efficient power management to optimize performance and efficiency.
Innovation Solution
The Node Power Architecture (NPA) system, which includes a distributed architecture that allows clients to issue requests to resources, enabling dynamic power optimization by using hints, deadlines, and workload requirements, and provides an event mechanism for notification of resource state changes, allowing for separate power optimization from resource definition and dynamic profiling of resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If processing power is increased to support enhanced functionality, then device capability is improved, but power consumption increases
Solution Approach 1:
The system dynamically adjusts processor operational states based on workload requirements. The power management system transitions the processor between different power states (active, idle, sleep) and adjusts frequency/voltage levels in real-time according to the actual computing needs, ensuring high performance when required while minimizing power consumption during low-demand periods
Solution Approach 2:
The system changes key operational parameters including processor frequency, voltage levels, and power state transitions based on workload analysis. By dynamically adjusting these parameters rather than maintaining fixed high-performance settings, the system achieves enhanced functionality when needed while reducing power consumption during normal operation
2Use of energy by moving object
If power management control is tightened to optimize power consumption, then energy efficiency is improved, but system complexity increases
Solution Approach 1:
The power management system operates autonomously by monitoring workload conditions and automatically making power state decisions without requiring manual intervention or complex external control logic. The system self-adjusts processor power states based on real-time workload analysis, simplifying the overall control architecture while maintaining effective power optimization
Solution Approach 2:
The system implements continuous feedback loops that monitor processor workload, power consumption, and thermal conditions. This feedback information is used to dynamically adjust power management decisions, creating a self-regulating system that optimizes power efficiency without requiring overly complex external control mechanisms
3Adaptability or versatility
If dynamic power optimization is implemented, then power management flexibility is improved, but processing time may increase due to state transitions
Solution Approach 1:
The system performs preliminary workload analysis and predicts future power needs, allowing it to proactively transition to appropriate power states before workload changes occur. By anticipating workload patterns and preparing power state transitions in advance, the system minimizes actual transition delays while maintaining power management flexibility
Solution Approach 2:
The power management system operates on periodic evaluation cycles, assessing workload conditions at regular intervals and making power state adjustments accordingly. This periodic approach balances the need for responsive power management with the overhead of state transitions, achieving flexibility while controlling processing time impacts
Data Source
AI summary
A method of utilizing a node power architecture (NPA) system, the method includes receiving a request to create a client, determining whether a resource is compatible with the request, and returning a client handle when the resource is compatible with the request.