Thermal-Aware Workload Distribution for Data Center Cooling
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Solution Overview
Problem
Data centers face inefficiencies in cooling servers due to non-uniform cool air distribution, leading to reduced server performance and increased costs, as the power used for cooling often exceeds the power used by the servers themselves.
Innovation Solution
An apparatus and method that determine and utilize correlative thermal efficiency impacts to distribute workloads across servers by establishing a baseline thermal efficiency, measuring deviations, and transferring workloads based on thermal efficiency thresholds, predicting optimal workload placement to minimize fan power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If workloads are distributed without considering thermal efficiency, then server utilization is maximized, but cooling costs and fan power consumption increase significantly
Solution Approach 1:
The system dynamically changes workload distribution parameters based on thermal efficiency metrics. By monitoring fan power consumption and temperature deviations, the system adjusts workload assignment to optimize the balance between server utilization and cooling energy consumption, preventing energy loss while maintaining productivity.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring thermal efficiency indicators such as fan power consumption and temperature deviations. This feedback is used to dynamically adjust workload distribution decisions, creating a closed-loop control system that reduces cooling energy consumption while maintaining optimal server utilization.
2Productivity
If workloads are concentrated on specific servers to improve utilization, then productivity increases, but thermal efficiency deteriorates due to non-uniform cool air distribution
Solution Approach 1:
The system applies local quality by considering the specific thermal characteristics of each server location when distributing workloads. Servers in different physical locations receive different workload assignments based on their individual thermal efficiency profiles, cool air reception capabilities, and proximity to cooling inputs, thereby optimizing both productivity and thermal management.
Solution Approach 2:
The system dynamically adjusts workload distribution in response to changing thermal conditions. By continuously monitoring temperature deviations and fan power consumption, the system adapts workload assignments to maintain optimal thermal efficiency while maximizing productivity, preventing heat accumulation in poorly cooled areas.
3Device complexity
If traditional workload distribution methods are used, then system simplicity is maintained, but thermal management efficiency decreases leading to higher costs
Solution Approach 1:
The system achieves multi-functionality by integrating thermal efficiency monitoring and workload distribution optimization into a unified platform. This universal system simultaneously manages server utilization, thermal monitoring, and energy optimization, reducing cooling power consumption without requiring entirely separate specialized systems.
Solution Approach 2:
The system enables self-service by allowing servers to effectively 'select' their own workload assignments based on their thermal characteristics and current operational state. The automated thermal-aware distribution algorithm independently optimizes workload placement to minimize cooling energy consumption without manual intervention, reducing energy loss while maintaining system simplicity.
Data Source
AI summary
An apparatus for determining and using correlative thermal efficiency impacts to distribute workloads includes a baseline module, a deviation module, and a transfer module. The baseline module determines a baseline system thermal efficiency of a plurality of servers based on a utilization level of the plurality of servers, the baseline system thermal efficiency including a baseline thermal efficiency of a first server of the plurality of servers. The deviation module determines a deviation in a thermal efficiency from the baseline thermal efficiency of the first server of the plurality of servers based on a new workload assigned to the first server of the plurality of servers. The transfer module transfers the new workload to a second server of the plurality of servers in response to the deviation being above a deviation threshold.