Power Controller Instruction Queue Subsystem Gating
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Solution Overview
Problem
Conventional data processing systems face inefficiencies in power management, as they do not adequately account for the status of an instruction queue when turning off subsystems, leading to potential delays in scheduled events and suboptimal power consumption reduction.
Innovation Solution
A data processing system that employs a power management unit to selectively turn on and off subsystems using power gating, coupled with an always-alive module and power controller, which considers the status of the instruction queue to manage power consumption dynamically, allowing for rapid switching between operational states based on user tasks and threads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional timer-based power management is used to turn off subsystems after inactivity, then power consumption is reduced, but scheduled events may be delayed or missed due to premature shutdown
Solution Approach 1:
The system checks the instruction queue status before turning off the subsystem to predict whether scheduled events will be affected. This preliminary check prevents premature shutdown that would delay or miss scheduled events, while still enabling power savings when the queue is truly empty.
Solution Approach 2:
The power management mechanism continuously monitors the instruction queue status and uses this feedback to dynamically control subsystem power states. When the queue contains scheduled events, the subsystem remains active; when empty, it can be powered down, creating a responsive feedback-based power management system.
2Loss of energy
If subsystems are turned off completely using power gating, then power consumption is significantly reduced, but the system cannot respond to scheduled events without wake-up mechanisms
Solution Approach 1:
The system predicts future power needs by examining the instruction queue before shutting down. This preliminary action ensures the subsystem is kept active when scheduled events are pending, eliminating the need for wake-up mechanisms while still enabling deep power savings when appropriate.
Solution Approach 2:
The power management system uses the existing instruction queue information to automatically make power management decisions without requiring external wake-up signals or additional monitoring hardware, making the system self-sufficient in managing its own power state.
3Speed
If the system operates at higher voltage and frequency for immediate responsiveness, then scheduled events are handled promptly, but power consumption increases
Solution Approach 1:
The system dynamically adjusts its operating state based on real-time instruction queue conditions. When scheduled events are present, the subsystem operates at full performance; when the queue is empty, it transitions to low-power state, creating a dynamic adaptation between performance and power consumption.
Solution Approach 2:
The power management mechanism changes the operational parameters (voltage, frequency, power state) of the subsystem based on the predicted workload from the instruction queue. This parameter adjustment enables the system to operate at high performance only when necessary, reducing overall energy consumption.
Data Source
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AI summary
Methods and systems for managing power consumption in data processing systems are described. In one embodiment, a data processing system includes a general purpose processing unit, a graphics processing unit (GPU), at least one peripheral interface controller, at least one bus coupled to the general purpose processing unit, and a power controller coupled to at least the general purpose processing unit and the GPU. The power controller is configured to turn power off for the general purpose processing unit in response to a first state of an instruction queue of the general purpose processing unit and is configured to turn power off for the GPU in response to a second state of an instruction queue of the GPU. The first state and the second state represent an instruction queue having either no instructions or instructions for only future events or actions.