AI Chip Frequency Control via Self-Monitoring Load
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing power consumption control methods for AI chips face challenges in balancing computing power and dynamic power consumption, leading to inefficiencies such as excessive power usage, performance degradation, and increased chip area and cost, particularly due to traditional frequency and voltage regulation algorithms.
Innovation Solution
A method and system that monitor load conditions to dynamically adjust the operating frequency of AI chip modules, entering a lowest peak power consumption state when loads exceed a threshold, maintaining the original state within certain limits, and increasing frequency levels when necessary, to ensure peak power consumption does not exceed the load threshold, thereby optimizing power usage without increasing area, cost, or power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional frequency and voltage regulation algorithms are used, then power consumption can be controlled, but control delay and hysteresis occur causing performance degradation
Solution Approach 1:
The system uses the to-be-controlled module itself to monitor its own load and control its own frequency, eliminating the need for external control units. The module autonomously adjusts its working frequency based on real-time load monitoring, removing the control delay inherent in traditional CPU or microprocessor-based control systems.
Solution Approach 2:
The control function is segmented from the CPU and integrated directly into the to-be-controlled module. This segmentation allows the module to independently manage its frequency based on local load conditions without waiting for CPU instructions, thereby eliminating control hysteresis and delay.
2Speed
If a specialized microprocessor is used to control frequency and voltage, then response time improves, but chip area and cost increase significantly
Solution Approach 1:
The control functions are merged directly into the to-be-controlled module, eliminating the need for a separate specialized microprocessor. This integration maintains fast response time while significantly reducing chip area by removing redundant control hardware.
Solution Approach 2:
The control functionality is extracted from a separate microprocessor and embedded directly into the to-be-controlled module. This extraction eliminates the need for additional microprocessor hardware while preserving the fast local response capability.
3Loss of energy
If frequency and voltage are controlled through the central processing unit, then power consumption is regulated, but performance degradation occurs during frequent task switching
Solution Approach 1:
The to-be-controlled module independently monitors its own load and adjusts its frequency without CPU intervention. This self-service capability eliminates the performance degradation caused by CPU involvement in frequent task switching, as the module can autonomously maintain optimal frequency during task transitions.
Solution Approach 2:
The frequency control function is extracted from the CPU and embedded in the to-be-controlled module. This extraction removes the bottleneck caused by CPU-mediated control during task switching, allowing the module to maintain high performance while the CPU focuses on task management.
Data Source
AI summary
The present disclosure provides a method and system for controlling peak power consumption, which dynamically controls frequency by monitoring the load in real-time, thereby reducing the power consumption, and providing sufficient computing performance while controlling peak power consumption. The method and system for controlling peak power consumption of the present disclosure monitor the load in real-time, and reduce power consumption by dynamically and intelligently controlling the operating frequency, to achieve a balance between performance and power consumption, such that the chip works at the highest frequency when the peak power consumption does not exceed the load threshold, thereby effectively improving the work efficiency while achieving the power consumption control.