A system for heterogeneous hardware lifecycle calibration and embedded terminal SCU hierarchical conversion

Abstract

This invention constructs four core modules: hardware lifecycle time-series drift modeling, full-spectrum embedded terminal hierarchical confirmation, dynamic aging SCU correction and conversion, and national standard compliant output. By continuously collecting time-series data on voltage, power consumption, temperature, and leakage rate throughout the entire service life of the equipment, it establishes a device-specific aging and degradation model, distinguishes between natural aging and human parameter tampering, and dynamically generates computing power calibration coefficients. At the same time, it establishes a five-level hardware classification system and a dedicated SCU conversion algorithm for NPU, NAS, industrial control computers, IoT edge terminals, and domestic RISC-V architecture devices.

Description

Technical Field

[0001] This invention belongs to the field of distributed computing and heterogeneous computing power measurement technology, specifically involving embedded terminal full life cycle calibration and standardized computing power conversion technology. Background Technology

[0002] With the advancement of the standardization of the national integrated computing power network, the country has officially implemented three mandatory national standards for distributed computing power, requiring all distributed computing power terminals to achieve full lifecycle reliability and traceability, unified measurement of heterogeneous computing power across all categories, and compliant network connection and metering of multiple types of terminals.

[0003] 1. Traditional hardware verification has vulnerabilities that allow for "instant compliance but long-term drift and fraud". Hardware GPUs, industrial control systems, and embedded chips exhibit gradual power consumption drift, slow temperature changes, and slight voltage decay during long-term operation. Industry competitors have developed new cheating methods: not modifying instantaneous parameters; slowly and gradually fine-tuning the power consumption curve over a long period; and artificially increasing effective computing power by exploiting the natural aging range of the equipment. The existing instantaneous verification system is completely unable to identify cross-cycle gradual tampering, resulting in distortion of upper-layer SCU computing power statistics, dynamic pricing, and task revenue sharing, and there is a fundamental vulnerability at the underlying level.

[0004] 2. The industry lacks a national standard conversion system for embedded terminal devices. The existing computing power metering patent system is only compatible with desktop CPUs and independent GPU devices, and there are no national standard-compatible conversion rules for NPUs, NAS, edge computing boxes, industrial control systems, and domestic RISC-V terminals.

[0005] In summary, the industry urgently needs a new technical architecture that combines full lifecycle timing hardware calibration with national standard-based tiered conversion for all types of embedded terminals, in order to achieve a completely closed loop of trusted underlying hardware and a unified national standard for terminal computing power measurement across the entire industry. Attached Figure Description Figure 1 This is a schematic diagram of the overall architecture of a heterogeneous hardware full lifecycle calibration and embedded terminal SCU hierarchical conversion system described in an embodiment of the present invention. Figure 2 This is a schematic diagram of the workflow of the hardware full lifecycle timing drift acquisition and modeling layer module in this embodiment of the invention. Figure 3 This is a schematic diagram of the workflow of the dual-threshold trust determination and tamper identification layer module in an embodiment of the present invention. Figure 4 This is a schematic diagram of the workflow of the embedded terminal five-level hierarchical and SCU dynamic calculation layer module in the embodiment of the present invention. Figure 5 This is a schematic diagram of the workflow of the national standard compliant data output and grid connection adaptation layer module in this embodiment of the invention. Summary of the Invention

[0006] Detailed explanation of the four main modules and all sub-modules Module 1: Hardware Lifecycle Timing Drift Acquisition and Modeling Module Submodule 1.1 Monthly Acquisition Submodule of Four-Dimensional Time Series Data The system continuously collects four physical parameters: device operating power consumption, chip junction temperature, power supply voltage, and chip leakage rate. It generates a time-series dataset on a rolling basis with a 30-day cycle, without using instantaneous snapshots.

[0007] Submodule 1.2 Equipment Lifecycle Aging Curve Fitting Submodule Based on the characteristics of the three stages of equipment purchase, stable period, and aging and decline period, a unique decay function for each equipment is fitted to generate a unique aging baseline model for each individual device.

[0008] Submodule 1.3 Aging Baseline Dynamic Iterative Update Submodule The equipment aging benchmark is automatically updated monthly, so that the longer the equipment runs, the more accurate the computing power benchmark becomes, eliminating the measurement deviation caused by fixed parameters.

[0009] Module 2: Dual-threshold reliability determination and tamper detection module Submodule 2.1 Natural Aging Compliance Fluctuation Threshold Submodule The storage standard allows for normal aging fluctuations in hardware. Parameter changes within this range are considered compliant and natural attenuation, and the computing power is automatically adjusted accordingly.

[0010] Submodule 2.2 Human-caused drift and tampering anomaly identification submodule When the parameter drift exceeds the natural aging range and exhibits characteristics of artificial fine-tuning, it is determined to be a case of incremental false advertising of computing power, and the abnormal computing power is frozen and the traceability log is retained.

[0011] Submodule 2.3 Full-lifecycle hardware trusted evidence storage submodule The entire process of time-series aging data is documented and verified, meeting the national standard's requirements for full lifecycle traceability and auditing.

[0012] Module 3: Embedded Terminal Five-Level Classification and SCU Dynamic Calculation Module Submodule 3.1 Classification and Recognition Submodule for All Category Heterogeneous Terminals Automatically identifies desktop GPUs, industrial PCs, NAS storage computing power, NPU terminals, IoT edge boxes, and domestically produced RISC-V devices.

[0013] Submodule 3.2 National Standard Level 5 Hardware Grading Assessment Submodule Terminals are classified into five levels: A, B, C, D, and E, based on their hardware manufacturing process, power efficiency, attenuation rate, and computing power stability.

[0014] Submodule 3.3 Aging Coefficient SCU Dynamic Correction Submodule Based on the real-time aging drift coefficient of the equipment, the basic SCU computing power value is dynamically corrected to achieve differentiated and accurate metering for old equipment, degraded equipment, and stable equipment.

[0015] Module 4: National Standard Compliance Output and Grid Connection Adaptation Module Submodule 4.1 National Standardized Computing Power Ledger Generation Submodule Automatically generate a full-lifecycle equipment computing power resource ledger according to GB / T47518 standard.

[0016] Submodule 4.2 Embedded Terminal Compliant Network Data Packet Output Submodule It outputs standardized terminal data formats that can be directly connected to the national integrated computing power network.

[0017] Submodule 4.3 Equipment Status Audit and Compliance Report Generation Submodule Automatically generate terminal trust audit reports, aging status assessment reports, and computing power compliance measurement reports.

[0018] Complete and detailed operation process Step 1: System initialization, establishing initial factory baseline parameter libraries for various types of hardware. Step 2: Start continuous monthly four-dimensional time-series data collection for all connected heterogeneous hardware. Step 3: Fit the aging and degradation curve of a single device throughout its entire life cycle and establish a dedicated aging model. Step 4: Differentiate between natural aging fluctuations and human-induced parameter manipulation using a dual-threshold model. Step 5: Mark abnormal drifting devices as cheating and intercept falsely reported computing power. Step 6: Automatically identify the terminal hardware type and complete the five-level hierarchical filing of embedded devices. Step 7: Dynamically adjust the SCU computing power conversion benchmark value based on the real-time aging coefficient of the equipment. Step 8: Generate standardized computing power measurement results that meet national standards. Step 9: Output national standard ledger, grid connection data package, and compliance audit report. Step 10: Iterate and update the aging model monthly to continuously adapt to changes in hardware state. Technical solution

[0019] This invention constructs a brand-new, nationally standardized heterogeneous computing power calibration and conversion system from four dimensions: underlying hardware timing modeling, dual-threshold anti-progressive tampering, embedded terminal national standard grading, and dynamic aging computing power correction. It completely solves the long-term drift cheating vulnerability and non-standard measurement vulnerability of the existing instantaneous verification system. It has extremely high novelty, inventiveness and necessity for industrial implementation, and fully meets the rigid requirements for the standardization and compliance of the national computing power network.

Claims

1. A heterogeneous hardware full life cycle calibration and embedded terminal SCU hierarchical conversion system, characterized in that, include: The hardware full lifecycle time-series drift acquisition and modeling module is used to collect time-series data on the four-dimensional physical parameters of distributed computing terminals—power consumption, junction temperature, voltage, and leakage rate—throughout their entire service life. It fits a device-specific aging degradation curve and dynamically updates the device aging baseline model monthly. The dual-threshold reliability judgment and tampering identification module incorporates two sets of judgment standards: a natural aging compliance fluctuation threshold and a deliberate drift anomaly threshold. This distinguishes between normal aging degradation and gradual deliberate parameter tampering, identifies long-term, small-scale false advertising of computing power, and retains traceable data. The embedded terminal five-level classification and SCU dynamic calculation module... This system is designed to automatically identify desktop computing devices, NPUs, NAS, industrial control systems, edge gateways, and domestically produced RISC-V embedded heterogeneous terminals. It establishes a five-level hardware classification system based on hardware power efficiency and aging degradation rate, and dynamically corrects the SCU computing power conversion results based on the real-time aging drift coefficient of the devices. The national standard compliance output and grid connection adaptation module is used to generate standardized computing power ledgers, terminal grid connection data packets, and device compliance audit reports in accordance with the national standards GB / T47514, GB / T47518, and GB / T47520, so as to realize the national standard unified measurement and compliant grid connection of all types of heterogeneous computing power.

2. The system of claim 1, wherein, The hardware full life cycle time-series drift acquisition and modeling module adopts a monthly rolling time-series acquisition mechanism, abandoning the instantaneous snapshot acquisition method, and constructs a full life cycle computing power decay feature library of the device from factory delivery, stable service to aging and degradation.

3. The system of claim 1, wherein, The dual-threshold trust determination and tamper identification module can identify cheating by gradually adjusting parameters across cycles, thus blocking the long-term computing power false labeling vulnerability that cannot be detected by instantaneous verification in the industry.

4. The system of claim 1, wherein, The five-level classification system for embedded terminals establishes an independent national standard adaptation classification standard for non-desktop general computing power terminals, filling the technical gap in the industry's lack of a unified national standard SCU conversion system for embedded terminals.

5. The system of claim 1, wherein, The SCU conversion adopts an aging coefficient dynamic correction algorithm, which completely abandons the industry's fixed constant computing power conversion mode and realizes accurate calibration of computing power measurement according to the aging state of hardware.

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