Inferred Processor Core Layout for Thermal Workload Distribution
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Solution Overview
Problem
Processor manufacturers do not disclose the spatial layout of processor cores on a die, which affects performance, power efficiency, and heat distribution, making it difficult to optimize workload distribution and cooling systems effectively.
Innovation Solution
Infer the physical layout of processor cores by recording temperature data during power-intensive workloads and using machine learning techniques, such as linear regression and cluster analysis, to determine the spatial positioning of cores, allowing for more even temperature distribution and improved cooling efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the physical layout of processor cores is kept confidential, then the manufacturer's intellectual property is protected, but the ability to optimize workload distribution and cooling systems is reduced
Solution Approach 1:
The patent creates a virtual copy or model of the physical processor core layout by inferring spatial relationships from thermal data. Instead of exposing the actual confidential layout, the system generates a replicated representation that captures the essential spatial information needed for optimization purposes, allowing workload distribution to be improved without revealing the true manufacturing details
Solution Approach 2:
The patent introduces thermal data and machine learning inference as an intermediary layer between the confidential physical layout and the workload distribution system. This intermediary enables optimization by translating thermal patterns into spatial relationship information without directly exposing the actual core positions or manufacturing secrets
2Reliability
If the physical layout of processor cores is kept confidential, then the manufacturer's intellectual property is protected, but the cooling system efficiency is reduced
Solution Approach 1:
The system creates a thermal-based virtual model of the processor layout that replicates the spatial information needed for cooling optimization. This copy allows the cooling system to be tuned effectively without requiring access to the actual confidential manufacturing layout
Solution Approach 2:
The patent implements a feedback mechanism where thermal data from the processor cores is continuously collected and used to infer spatial relationships. This feedback loop enables the cooling system to adapt and optimize its performance based on actual thermal patterns, improving efficiency while maintaining layout confidentiality
3Measurement precision
If temperature data is collected from all processor cores during workloads, then the physical layout can be inferred, but additional measurement and processing overhead is introduced
Solution Approach 1:
The patent enables the processor system to self-characterize its own physical layout by utilizing its existing thermal sensors and workload execution capabilities. The system performs self-measurement of temperature data and self-processing through machine learning inference, eliminating the need for external measurement equipment or complex additional hardware
Solution Approach 2:
The patent makes the processor's existing thermal sensors and computation resources serve multiple functions: they continue to monitor thermal management needs while simultaneously enabling physical layout inference. This multi-functionality reduces the need for dedicated measurement infrastructure and leverages existing system components
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables better energy efficiency, reduces the likelihood of thermal throttling, and extends the longevity of processor components by optimizing workload distribution based on core proximity and thermal affinity.
Implementation Method 1
Each of the plurality of processor cores is controlled to execute a respective power-intensive workload... obtain temperature measurement data from each processor core... acquired during the executing of the respective workloads
Data Source
AI summary
It is provided an apparatus comprising interface circuitry, machine-readable instructions, and processing circuitry to execute the machine-readable instructions. The machine-readable instructions comprise instructions to control each processor core of a plurality of processor cores of a first processing circuitry to execute a respective workload. The machine-readable instructions further comprise instructions to obtain temperature measurement data from each processor core of the plurality of processor cores. The temperature measurement data is acquired during the executing the respective workloads by the respective processor core of plurality of processor cores. The machine-readable instructions further comprise instructions to determine a physical layout of the first processing circuitry based on the obtained temperature measurement data from each processor core of the plurality of processor cores of the first processing circuitry.