Distributed Cooling Control for Power-Constrained Compute Systems
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Solution Overview
Problem
High-performance computing systems, such as data centers and edge computing environments, face thermal management challenges due to increased thermal design power, where traditional air cooling systems are inadequate, and liquid cooling systems consume more power, leading to potential overheating and downtime in remote or power-constrained environments.
Innovation Solution
A system that predicts power and cooling requirements using telemetry data and models based on workload, ambient conditions, and historical records, allowing for proactive mitigation of power shortfalls by adjusting power output, core frequency, and workload redeployment, while optimizing power usage to prevent overheating.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If liquid cooling systems are used to cool high-performance computing systems, then cooling efficiency is improved, but power consumption increases
Solution Approach 1:
The system performs preliminary actions by predicting future power and cooling requirements using telemetry data and machine learning models before power shortfalls occur. This allows proactive adjustment of power output and cooling strategies, preventing overheating while optimizing power consumption in advance rather than reacting to thermal emergencies
Solution Approach 2:
The system implements continuous feedback loops by monitoring telemetry data from sensors throughout the computing system, comparing actual performance against predicted values, and dynamically adjusting power output and cooling strategies. This closed-loop control optimizes the balance between cooling efficiency and power consumption by making real-time adjustments based on actual system conditions
2Power
If power output is increased to meet computing demands, then system performance is improved, but thermal management becomes more difficult
Solution Approach 1:
The system predicts upcoming power requirements and thermal conditions before they occur, allowing proactive thermal management strategies to be implemented. By anticipating high-power demand periods, the system can pre-cool components or prepare cooling infrastructure, enabling higher power output without compromising thermal management
Solution Approach 2:
The system dynamically changes operational parameters including power output levels, cooling fluid flow rates, and component operational states based on predicted and actual conditions. This allows the system to optimize the balance between power performance and thermal management by adjusting parameters in real-time rather than operating at fixed settings
3Use of energy by moving object
If traditional air cooling systems are used, then power consumption is reduced, but cooling capability is insufficient for high thermal design power
Solution Approach 1:
The system dynamically selects between different cooling approaches and adjusts cooling intensity based on actual thermal conditions and power requirements. Rather than using a static cooling infrastructure, the system adapts cooling capacity in real-time, enabling efficient operation at lower power levels while providing sufficient cooling capability when high thermal design power is required
Data Source
AI summary
Methods and apparatus for maintaining the cooling systems of distributed compute systems are disclosed. An example apparatus disclosed herein includes memory, machine readable instructions, and programmable circuitry to at least one of instantiate or execute the machine readable instructions to input operational data into a machine-learning model, the operational data including first information relating to a workload of a server and second information relating to an ambient condition of the server, compare a predicted cooling power requirement for a time period with a predicted cooling power availability for the time period, the predicted cooling power requirement based on an output of the machine-learning model, and generate a cooling plan based on the comparison, the cooling plan to define operation of at least one of the server or a cooling system used to cool the server during the time period.