Server Component Cooling via Predictive Thermal Demand
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Solution Overview
Problem
Current data center cooling systems are inefficient as they provide cooling at a server level based on the hottest component, leading to unnecessary cooling of other components and lack proactive adjustment to anticipated heat demands, resulting in inefficiencies and lag in temperature management.
Innovation Solution
A system that uses server indicators from temperature sensors, task schedulers, and traffic switches to determine the expected cooling demand for individual components, allowing proactive adjustment of cooling mechanisms before task execution, and utilizes machine learning to refine cooling demands based on historical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cooling is provided at server level based on the hottest component, then the hottest component is protected from overheating, but other components receive unnecessary cooling and energy is wasted
Solution Approach 1:
The patent divides the server into multiple thermal zones corresponding to different components (CPU, GPU, storage devices, etc.), each monitored by dedicated temperature sensors. This segmentation allows independent temperature control for each component rather than uniform server-level cooling, enabling the cooling system to target only components that require cooling and adjust cooling intensity per component needs.
Solution Approach 2:
The patent implements component-specific cooling control where each thermal zone receives cooling tailored to its local thermal conditions and requirements. The cooling system adjusts cooling parameters (such as fan speeds, coolant flow rates) based on individual component temperatures and thermal characteristics, providing localized cooling quality rather than uniform server-wide cooling.
2Reliability
If reactive cooling is used based on current temperature, then overheating is prevented, but cooling adjustment lags behind task execution and heat generation
Solution Approach 1:
The patent employs predictive cooling control that uses task scheduling information, workload characteristics, and historical thermal data to anticipate future heat generation before tasks actually execute. The cooling system proactively adjusts cooling parameters in advance of task execution, eliminating the lag between heat generation and cooling response. This preliminary action ensures cooling is already in effect when components begin generating heat from upcoming tasks.
3Device complexity
If uniform cooling is applied to all components, then simplicity is maintained, but different cooling requirements of different components are not met
Solution Approach 1:
The patent implements dynamic cooling control where cooling parameters are continuously adjusted based on real-time temperature measurements, task workload, and component-specific thermal requirements. The system transitions from static uniform cooling to dynamic adaptive cooling, where cooling intensity and distribution change over time and space to match actual thermal conditions of different components during different operational states.
Data Source
AI summary
A system and method for controlling cooling in a server is provided. The method includes receiving one or more server indicators relating to a task to be executed by at least one component of the server. The method also includes determining an expected cooling demand for the at least one component based on the one or more server indicators. The method further includes adjusting a cooling amount provided by a cooling mechanism based on the expected cooling demand of the at least one component. Various embodiments are described herein.