Dynamic Load Balancing for AI Chip Power Stability
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Solution Overview
Problem
AI chips face challenges with instantaneous power consumption spikes during state transitions, leading to voltage drops and overshoots, which can cause damage and are difficult to mitigate through software optimization alone.
Innovation Solution
A method and apparatus that dynamically control the operating state of data processing units by monitoring and predicting changes in input data between clock cycles, using a statistical and control unit to adjust the load conditions and reduce instantaneous power consumption through feedback mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If a large number of transistors hop from idle state to active state at the same time, then computing power is activated, but instantaneous power consumption becomes extremely large causing voltage drops
Solution Approach 1:
The patent predicts future input data in advance and activates data processing units before they are actually needed. By using a prediction mechanism that analyzes input data patterns, the system prepares the appropriate number of processing units ahead of time, distributing their activation across multiple clock cycles rather than activating them all simultaneously. This preliminary action prevents instantaneous power spikes while ensuring computing power is available when needed.
Solution Approach 2:
The patent dynamically adjusts the number of active data processing units based on predicted workload. Instead of a static allocation, the system continuously monitors input data characteristics and modifies the operating state of processing units in real-time. This dynamic approach allows the system to match power consumption to actual computational needs, avoiding both instantaneous spikes and underutilization of resources.
2Power
If a large number of transistors hop from active state to idle state at the same time, then computing power is reduced, but instantaneous voltage overshoot occurs causing damage to power supply network
Solution Approach 1:
The patent uses prediction mechanisms to anticipate workload changes and gradually deactivates data processing units before the actual reduction in computational demand occurs. By predicting future input data patterns, the system can smoothly transition processing units from active to idle state across multiple clock cycles, preventing sudden voltage overshoots that would occur with simultaneous deactivation.
Solution Approach 2:
The patent implements periodic monitoring and adjustment of data processing unit states based on predicted workload patterns. Instead of abrupt transitions, the system uses rhythmic, controlled activation and deactivation cycles that distribute voltage changes over time. This periodic action smooths out power consumption fluctuations and prevents harmful voltage overshoots while maintaining necessary computing power.
3Loss of energy
If software optimization is used to mitigate power consumption issues, then some improvement may be achieved, but the problems are difficult to solve and become very serious in large-area and high-power chips
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors actual power consumption and workload characteristics, then uses this information to adjust the activation state of data processing units. The prediction mechanism incorporates feedback from observed input data patterns to refine future predictions, creating a closed-loop control system that optimizes power consumption automatically without requiring complex software interventions or increasing chip area.
Data Source
AI summary
Embodiments of the present disclosure relate to a method and apparatus for balancing loads, and a computer-readable storage medium. The method includes: for each data processing unit in a set of data processing units in a data processing system, acquiring current input data of the data processing unit for a current clock cycle and next input data of the data processing unit for a next clock cycle; and determining a first metric value indicating changes in input data of said data processing unit in the next clock cycle based on a comparison between the current input data and the next input data. The method further includes controlling an operating state of the set of data processing units in the next clock cycle based on the first metric value determined for the set of data processing units.