Granular Energy Measurement for Computer Systems
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Solution Overview
Problem
Existing methods for managing energy consumption in computer systems lack granular control, failing to accurately account and optimize energy usage at the individual component and application levels, which is crucial for efficient resource allocation and billing in dynamic computing environments.
Innovation Solution
A method that measures voltage and current usage over time for each hardware component within a computing environment, allowing for precise energy consumption tracking and accounting at individual execution contexts, enabling optimization, billing, and load balancing by associating energy consumption with specific components or applications and adjusting execution priorities based on calculated energy budgets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If coarse-grained power management strategies are used (e.g., system-level power states, thermal management), then overall energy consumption is reduced, but granular control and measurement at component level is lost
Solution Approach 1:
The patent segments energy measurement and management at the hardware component level, creating independent measurement units for each component (CPU, memory, storage, etc.). This segmentation enables precise tracking of energy consumption by individual components while maintaining system-wide energy optimization capabilities.
Solution Approach 2:
The patent adds a new dimension of granularity to energy management by introducing hardware-level measurement units that operate independently from software contexts. This creates a hierarchical measurement structure spanning from component to system level, enabling both coarse and fine-grained energy analysis simultaneously.
2Measurement precision
If hardware-level energy measurement is implemented, then granular energy tracking is achieved, but system complexity and measurement infrastructure requirements increase
Solution Approach 1:
The measurement units are integrated directly into hardware components, enabling them to self-measure their own energy consumption. This self-service approach eliminates the need for external measurement infrastructure and reduces system complexity while maintaining high measurement precision.
Solution Approach 2:
The measurement units are designed as universal components that can be applied to any hardware component type (CPU, memory, storage, network interfaces). This multi-functionality reduces overall system complexity by using a standardized measurement approach across diverse hardware components.
3Loss of information
If detailed energy tracking per execution context is performed, then accurate billing and resource allocation is enabled, but computational overhead and processing time increase
Solution Approach 1:
Energy measurement occurs continuously at the hardware level before software processing is needed. By pre-measuring and recording energy consumption at the source, the system eliminates the need for complex post-processing calculations, reducing computational overhead and processing time while maintaining accurate energy accounting.
Solution Approach 2:
The patent introduces measurement units as intermediary components between hardware and software layers. These intermediaries capture energy data directly from hardware and present it to software in a processed format, reducing the computational burden on software systems while maintaining detailed energy accounting accuracy.
Data Source
AI summary
Management of energy consumption within a computing environment. Energy consumption of different hardware components are measured in the computing environment. Measurement includes voltage and current versus time used by the hardware components. The different measured values of energy consumption are collected, followed by tracking the hardware component used in time during an execution of an individual execution context within the computing environment. The energy consumption of the individual execution context is calculated by associating the corresponding collected measured energy consumption to the hardware component used.