HPC Power Cap Allocation Across Heterogeneous Equipment Pools
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Solution Overview
Problem
Managing power consumption across heterogeneous high-performance computing (HPC) systems is challenging due to diverse equipment architectures, varying power cap values, and the need for efficient utilization of a system-wide power budget, which conventional methods fail to address effectively.
Innovation Solution
A system and method for distributing a system-wide power cap among HPC equipment by considering individual equipment characteristics and end-user defined tradeoffs, using an out-of-band control mechanism to set optimal power caps on a per-equipment basis, ensuring efficient utilization and compliance with specified power limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional power management methods are used in heterogeneous HPC systems, then system simplicity is maintained, but power consumption efficiency deteriorates due to inability to account for diverse equipment characteristics
Solution Approach 1:
The patent segments the heterogeneous HPC system into multiple equipment groups based on similar power characteristics and architectural features. Each group is assigned a tailored power cap policy, allowing efficient power management for diverse equipment types while avoiding the need to manage each device individually. This segmentation resolves the contradiction by organizing complexity into manageable categories.
Solution Approach 2:
The patent applies local quality by assigning different power cap values and management policies to different equipment groups based on their specific characteristics. Instead of a uniform power management approach, each equipment type receives customized power allocation, improving overall power efficiency while maintaining systematic control through the power cap manager.
2Use of energy by moving object
If uniform power caps are applied to all HPC equipment, then device complexity is reduced, but power consumption efficiency deteriorates due to ignoring individual equipment characteristics
Solution Approach 1:
The patent changes the power cap parameter dynamically based on equipment characteristics, workload requirements, and system-wide power policies. The power cap manager adjusts power cap values for different equipment groups, transforming a static uniform approach into a dynamic adaptive system that optimizes power efficiency without excessive complexity.
Solution Approach 2:
The patent implements local quality by applying customized power cap values to specific equipment groups rather than uniform caps. Each equipment type receives power allocation tailored to its characteristics, improving power efficiency while the power cap manager maintains overall system coordination to prevent excessive complexity.
3Measurement precision
If detailed individual equipment monitoring is implemented, then power consumption precision is improved, but system complexity increases due to management overhead
Solution Approach 1:
The patent merges individual equipment monitoring into group-level monitoring by aggregating power consumption data from multiple devices within the same equipment group. The power cap manager monitors and enforces power caps at the group level rather than tracking each device separately, maintaining measurement precision for power management while significantly reducing administrative complexity.
Solution Approach 2:
The patent segments monitoring complexity by organizing equipment into groups with similar characteristics, allowing the system to monitor group-level power consumption rather than individual devices. This segmentation maintains sufficient measurement precision for effective power management while reducing the overhead of tracking each piece of equipment separately.
Data Source
AI summary
Automated systems and methods are provided for distributing a system power cap amongst system equipment for efficient utilization of power cap ranges without requiring an understanding of intricacies of the system architecture. Examples of the systems and methods automatically, responsive to trigger events, distribute the system power cap amongst system equipment. Another example provides for grouping of system equipment into multiple pools and distributing the system power cap to system equipment on a per-pool basis, according to a prioritized order.