Multi-cluster Interrupt Migration for Power Efficiency
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Solution Overview
Problem
In multi-cluster computing systems with multiple processor types, existing management frameworks face challenges in balancing power consumption and performance, often leading to underutilization of processor capacity or increased hardware costs due to the need for multiple voltage regulators.
Innovation Solution
A method and system that detect frequency changes in active clusters, identify target clusters with different energy efficiency characteristics, activate or deactivate processor cores, and migrate interrupt requests to optimize performance and power usage based on workload demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple processor types operate at the same time with different operating frequencies, then performance of each processor type is optimized, but hardware cost increases due to requiring multiple voltage regulators
Solution Approach 1:
The system dynamically changes operating frequency parameters of processor cores based on workload demands and energy efficiency characteristics. The management module monitors performance requirements and adjusts frequency settings to optimize the balance between productivity and power consumption, allowing different processor types to operate efficiently without requiring separate voltage regulators for each frequency.
Solution Approach 2:
The system implements dynamic frequency adjustment where processor operating frequencies are not fixed but can be changed in real-time based on system conditions. This dynamic approach allows a single voltage regulator to accommodate varying frequency requirements of multiple processor types, reducing hardware complexity while maintaining optimal performance when needed.
2Device complexity
If all processor types are set to the same operating frequency, then hardware cost is reduced by using a single voltage regulator, but performance of different processor types is compromised
Solution Approach 1:
The management module dynamically changes the operating frequency parameter of processor cores based on workload demands and energy efficiency characteristics. This allows the system to use a single voltage regulator (reducing hardware cost) while still achieving optimal performance when needed by adjusting frequencies in real-time rather than being locked into a fixed frequency for all processors.
3Use of energy by stationary object
If only one processor type is allowed to operate at a time, then power consumption is reduced, but processing capacity of other processor types is under-utilized
Solution Approach 1:
The system changes operating frequency parameters dynamically based on workload demands. When workload is low, frequencies are reduced to save power. When workload increases, frequencies are increased or additional processor cores are activated to meet performance demands. This allows the system to utilize multiple processor types simultaneously while managing power consumption through intelligent frequency and core activation decisions.
Solution Approach 2:
The system implements dynamic activation and deactivation of processor cores based on workload conditions. Rather than keeping all processors running at fixed frequencies, the management module dynamically adjusts which cores are active and at what frequencies, allowing the system to scale power consumption with actual workload requirements while maintaining processing capacity when needed.
4Productivity
If operating frequency of a processor is increased to ramp up computing performance, then performance is improved, but power consumption of the processor increases
Solution Approach 1:
The management module monitors computing performance requirements and dynamically adjusts the operating frequency parameter of processor cores. When high computing performance is needed, frequencies are increased. When performance requirements are lower, frequencies are reduced to decrease power consumption. This dynamic parameter adjustment allows the system to optimize the trade-off between productivity and power consumption based on actual workload demands.
Data Source
AI summary
Energy efficiency is managed in a multi-cluster system. The system detects an event in which a current operating frequency of an active cluster enters or crosses any of one or more predetermined frequency spots of the active cluster, wherein the active cluster includes one or more first processor cores. When the event is detected, the system performs the following steps: (1) identifying a target cluster including one or more second processor cores, wherein the each first processor core in the first cluster and each second processor core in the second cluster have different energy efficiency characteristics; (2) activating at least one second processor core in the second cluster; (3) determining whether to migrate one or more interrupt requests from the first cluster to the second cluster; and (4) determining whether to deactivate at least one first processor core of the active cluster based on a performance and power requirement.