Virtual machine instruction management method and device based on machine type specification, equipment and medium

Abstract

The invention relates to the technical field of cloud computing, can be applied to business system platforms of medical health, financial science and technology and the like, and discloses a model specification-based virtual machine instruction management method, which comprises the following steps of: obtaining influence heterogeneous factors of a virtual machine instruction set, and carrying out standardized disassembly on the influence heterogeneous factors to generate metadata fields; according to the metadata fields and software and hardware information of the host machines, determining a machine type specification corresponding to each host machine, and pre-defining a reference instruction set for each machine type specification; on the basis of the reference instruction set, establishing an instruction set fine tuning function of a source host machine, and deploying an instruction set strategy engine in a target host machine; when the virtual machine of the source host machine initiates a live migration request, comparing the model specifications and instruction set states of the source host machine and a target host machine through the instruction set strategy engine, and judging whether the instruction set has compatibility risks or not; and if the compatibility risk exists, executing an instruction set automatic degradation operation.

Description

Technical Field

[0001] This invention relates to the field of cloud computing technology, and in particular to a virtual machine instruction management method, apparatus, device, and storage medium based on machine model specifications. Background Technology

[0002] In mainstream cloud computing architectures, the CPU instruction set upon which virtual machines rely is influenced by multiple underlying factors, including the host CPU model and generation (e.g., Intel Ice Lake, Skylake), the virtualization software version (e.g., QEMU-KVM-1.5.3, QEMU-KVM-4.5.0), the on / off state of the monitor instruction set in the BIOS, the operating system kernel version and its corresponding instruction set masking policy, and the CPU model explicitly specified in the virtual machine configuration. These intertwined factors result in a high degree of uncertainty and uncontrollability in the instruction set configuration during virtual machine creation, leading to numerous core problems in existing technologies.

[0003] First, instruction set configurations are scattered and lack unified management. Related control logic is dispersed across multiple configuration items such as BIOS settings, virtualization versions, and CPU models, failing to form a unified abstract concept and posing significant challenges to centralized management. Second, hot migration failure rates are high. When virtual machines need to migrate between heterogeneous hosts, if the target host does not support the advanced instruction sets used by the source virtual machine (such as AVX512), migration will fail directly, causing service interruption. Third, operational complexity remains high. Administrators need to manually check instruction set compatibility between hosts, lacking automated judgment mechanisms, which is particularly inefficient in large-scale cluster scenarios. Finally, it is difficult to balance differentiated performance requirements. Enabling advanced instruction sets such as AVX512 to improve performance often sacrifices migration compatibility, while prioritizing compatibility requires sacrificing some performance, creating a binary dilemma of "compatibility-performance."

[0004] In the fintech sector, the uncertainties and technical pain points associated with the aforementioned CPU instruction set configurations can trigger critical business risks. Fintech scenarios have extremely high requirements for business continuity, transaction stability, and security. Service interruptions caused by virtual machine hot migration failures can lead to direct economic losses such as transaction delays and payment failures, and may even trigger compliance risks. Furthermore, the fragmented instruction set configurations and lack of unified management increase the operational complexity of core financial systems. In large-scale clustered financial cloud environments, the inefficiency of manually troubleshooting compatibility can lead to delayed fault response, further amplifying risks. Simultaneously, the "compatibility-performance" dilemma constrains the differentiated needs of financial businesses—high-frequency trading and quantitative analysis require advanced instruction sets such as AVX512 to improve computing speed, while cross-regional disaster recovery and multi-node load balancing have strong requirements for migration compatibility. Existing technologies struggle to balance both, impacting business efficiency and disaster recovery reliability.

[0005] In the healthcare field, these technical issues directly impact the security, timeliness, and stability of medical data processing. Virtual machines in healthcare scenarios often handle core tasks such as electronic medical record storage, medical image analysis, and gene sequencing computation. Uncontrollable instruction set configurations can lead to computational errors during data processing, especially in scenarios reliant on high-precision computation, such as medical image diagnosis and gene data analysis, where errors can affect diagnostic results or research conclusions. Service interruptions caused by failed hot migrations can result in delays in medical data transmission, system lag, and even impact decision-making efficiency in emergency medical scenarios. Furthermore, high operational complexity increases the burden on healthcare IT teams. In multi-hospital, cross-regional medical cloud deployments, inefficient compatibility checks can restrict the flexible allocation of medical resources. Moreover, scenarios such as medical image analysis and AI-assisted diagnosis have extremely high computational performance requirements, necessitating advanced instruction sets. However, medical data sharing and cross-institutional collaboration require ensuring migration compatibility. This existing technological dilemma hinders the efficient advancement of healthcare digitization. Summary of the Invention

[0006] The main objective of this invention is to provide a virtual machine instruction management method, apparatus, device, and storage medium based on machine model specifications, aiming to solve the problems of scattered virtual machine instruction set configuration and high hot migration failure rate in existing cloud computing virtualization technologies.

[0007] To achieve the above objectives, the present invention provides a virtual machine instruction management method based on machine model specifications, comprising: Obtain the heterogeneous factors affecting the virtual machine instruction set, and standardize and decompose the heterogeneous factors to generate metadata fields; Based on the metadata fields and the host machine's hardware and software information, determine the machine model and specifications corresponding to each host machine, and predefine a baseline instruction set for each machine model and specifications; Based on the baseline instruction set, an instruction set fine-tuning function is built on the source host machine, and an instruction set policy engine is deployed on the target host machine; When the virtual machine on the source host initiates a hot migration request, the instruction set policy engine compares the machine specifications and instruction set status of the source host and the target host to determine whether there is a compatibility risk in the instruction set. If there is a compatibility risk, an automatic instruction set downgrade operation will be performed.

[0008] Furthermore, to achieve the above objectives, the present invention provides a virtual machine instruction management device based on machine model specifications, comprising: The data processing module is used to acquire the heterogeneous factors affecting the virtual machine instruction set, and to standardize and decompose the heterogeneous factors to generate metadata fields. The instruction set module is used to determine the model specification corresponding to each host machine based on the metadata field and the host machine's hardware and software information, and to predefine a baseline instruction set for each model specification; The mechanism construction module is used to build the instruction set fine-tuning function of the source host machine based on the benchmark instruction set, and to deploy the instruction set policy engine on the target host machine; The risk assessment module is used to determine whether there is a compatibility risk of the instruction set when the virtual machine of the source host initiates a hot migration request, by comparing the machine specifications and instruction set status of the source host and the target host through the instruction set policy engine. The risk handling module is used to perform automatic instruction set downgrade operations if there are compatibility risks.

[0009] Furthermore, to achieve the above objectives, the present invention also provides a computer device, the computer device including a memory, a processor, and a machine-specific virtual machine instruction manager stored in the memory and executable on the processor, wherein the machine-specific virtual machine instruction manager, when executed by the processor, implements the steps of the machine-specific virtual machine instruction management method as described above.

[0010] Furthermore, to achieve the above objectives, the present invention also provides a computer-readable storage medium storing a machine-specific virtual machine instruction management program, wherein the machine-specific virtual machine instruction management program, when executed by a processor, implements the steps of the machine-specific virtual machine instruction management method described above.

[0011] Beneficial Effects: This invention relates to the field of cloud computing technology and can be applied to business system platforms such as healthcare and fintech. It discloses a virtual machine instruction management method based on machine specifications, comprising: acquiring the heterogeneous factors affecting virtual machine instruction sets, and standardizing and decomposing the heterogeneous factors to generate metadata fields; determining the machine specifications corresponding to each host based on the metadata fields and the host machine's hardware and software information, and predefining a baseline instruction set for each machine specification; building an instruction set fine-tuning function for the source host based on the baseline instruction set, and deploying an instruction set policy engine on the target host; when a virtual machine on the source host initiates a hot migration request, comparing the machine specifications and instruction set status of the source and target hosts through the instruction set policy engine to determine whether there is a compatibility risk in the instruction set; if a compatibility risk exists, performing an automatic instruction set downgrade operation. This invention first obtains the factors affecting heterogeneity of virtual machine instruction sets and decomposes them into metadata fields. Then, it combines the host machine's hardware and software information to determine the machine model and specifications and predefined baseline instruction sets. It also builds a source host machine instruction set fine-tuning function and deploys a target host machine instruction set policy engine. During migration, it judges compatibility and downgrades if there is a risk, thereby improving the migration success rate and operation and maintenance efficiency. Attached Figure Description

[0012] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a schematic diagram of an application environment for a virtual machine instruction management method based on machine model specifications according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating an embodiment of the virtual machine instruction management method based on machine model specifications according to the present invention; Figure 3 This is a schematic diagram of the functional modules of a preferred embodiment of the virtual machine instruction management device based on machine model specifications of the present invention. Figure 4 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention; Figure 5 This is another structural schematic diagram of a computer device according to one embodiment of the present invention. Detailed Implementation

[0013] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0014] The virtual machine instruction management method based on machine model specifications provided in this embodiment of the invention can be applied to, for example... Figure 1In this application environment, the user terminal communicates with the server via a network. The server can obtain the heterogeneous factors affecting the virtual machine instruction set from the user terminal, and standardize and decompose these factors to generate metadata fields. Based on the metadata fields and the host machine's hardware and software information, the server determines the machine model and specifications corresponding to each host machine, and predefines a baseline instruction set for each machine model and specifications. Based on the baseline instruction set, the server builds an instruction set fine-tuning function for the source host machine and deploys an instruction set policy engine on the target host machine. When a virtual machine on the source host machine initiates a hot migration request, the server compares the machine model and specifications and instruction set status of the source and target host machines through the instruction set policy engine to determine whether there is a compatibility risk. If a compatibility risk exists, an automatic instruction set downgrade operation is performed. This invention improves migration success rate and operational efficiency by first obtaining the heterogeneous factors affecting the virtual machine instruction set and decomposing them into metadata fields, then combining them with host machine hardware and software information to determine the machine model and specifications and predefine a baseline instruction set, and also by building a source host machine instruction set fine-tuning function and deploying a target host machine instruction set policy engine. During migration, compatibility is checked, and downgrades are performed if there is a risk, thus improving migration success rate and operational efficiency. The user terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented using a standalone server or a server cluster consisting of multiple servers. The invention will now be described in detail through specific embodiments.

[0015] Please see Figure 2 , Figure 2 This is a flowchart illustrating an embodiment of the virtual machine instruction management method based on machine specifications provided by the present invention. It should be noted that although the logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0016] like Figure 2 As shown, the virtual machine instruction management method based on machine model specifications proposed in this invention includes the following steps: S100. Obtain the heterogeneous factors affecting the virtual machine instruction set, and standardize and decompose the heterogeneous factors to generate metadata fields. S200. Based on the metadata fields and the host machine's hardware and software information, determine the machine model and specifications corresponding to each host machine, and predefine a baseline instruction set for each machine model and specifications; S300. Based on the baseline instruction set, build the instruction set fine-tuning function of the source host machine and deploy the instruction set policy engine on the target host machine; S400. When the virtual machine of the source host initiates a hot migration request, the instruction set policy engine compares the machine specifications and instruction set status of the source host and the target host to determine whether there is a compatibility risk in the instruction set. If there is a compatibility risk, the S500 will perform an automatic instruction set downgrade operation.

[0017] In this embodiment, the heterogeneous factors affecting the virtual machine instruction set include the host CPU model and generation (e.g., Intel's Ice Lake and Skylake), virtualization software version (e.g., QEMU-KVM-1.5.3 and QEMU-KVM-4.5.0), the instruction set on / off status in the BIOS (monitor instruction set), the operating system kernel version and its instruction set masking policy, and the CPU model explicitly specified in the virtual machine configuration. After standardizing and decomposing these heterogeneous factors, the generated metadata fields include core information such as CPU model, virtualization software version, BIOS configuration policy, and OS kernel version. These fields comprehensively cover the key hardware and software parameters affecting the instruction set, providing a unified basis for the subsequent definition of machine specifications.

[0018] Based on the standardized metadata fields mentioned above, combined with the actual hardware and software information of each host machine, the host machine can be automatically classified into the corresponding Machine Type Specification (MTS). A machine type specification is a configurable, versionable, and reusable logical unit that aggregates key hardware and software metadata of the host machine. For example, a host machine equipped with an Intel Ice Lake CPU, using QEMU-KVM-4.5.0 virtualization software, and matching a specific OS kernel version might be classified as an MTS-Intel-ICX-OS7 machine type specification. Each machine type specification predefines a corresponding Baseline Instruction Set (BIS), which is the set of instruction sets enabled by default for all virtual machines on that type of host machine, achieving unified baseline management of instruction sets.

[0019] Building upon the baseline instruction set, the source host machine supports instruction set fine-tuning, allowing for the dynamic enabling of additional instruction set extensions (such as AVX512, an advanced vector extension instruction set that improves parallel computing performance; and FMA, a fused multiply-accumulate instruction set that optimizes arithmetic operations) for specific virtual machines or application groups (e.g., AI inference, database optimization scenarios). Simultaneously, an instruction set policy engine (a core component for managing instruction set fine-tuning behavior and verifying compatibility) is deployed on the target host machine. This engine controls the fine-tuning operations, ensuring that the fine-tuning only takes effect when the target host machine supports the corresponding extended instruction set, thus guaranteeing the compatibility of the extended instruction set.

[0020] When a virtual machine on the source host initiates a hot migration request (referring to a migration method where a virtual machine is moved from one host to another while still running, without interrupting service), the instruction set policy engine automatically compares the machine specifications and instruction set status of the source and target hosts. The comparison process relies on a system-maintained "machine specification-instruction set compatibility matrix," which records the instruction set support relationships between different machine specifications. By verifying the consistency between the baseline instruction set and the fine-tuned extended instruction set, the engine determines whether there are any compatibility risks.

[0021] If a compatibility risk is found after comparison (such as the target host not supporting the AVX512 extended instruction set enabled by the source virtual machine), the system will automatically perform an instruction set downgrade operation to adjust the instruction set of the source virtual machine to the range supported by the target host, ensuring a smooth hot migration and avoiding service interruption.

[0022] In one embodiment, S100 includes: S101, Pre-build cloud computing architecture; S102. In the environment of the cloud computing architecture, identify the underlying factors of the virtual machine instruction set; S103. Determine the heterogeneous factors affecting the virtual machine instruction set based on the underlying factors; S104. Standardize and decompose the factors affecting heterogeneity to generate metadata fields.

[0023] In this embodiment, a cloud computing architecture is pre-built. The core of this architecture is establishing a virtualization runtime environment that conforms to mainstream technical standards. For example, the commonly used architecture in the industry is the KVM / QEMU architecture (KVM stands for Kernel-based Virtual Machine, a virtualization module in the Linux kernel; QEMU is an open-source virtualization emulator that, when combined with KVM, enables efficient hardware virtualization). This architecture can provide virtual machines with near-physical machine performance while supporting multiple virtual machines running in isolation on the same host machine, serving as the foundational environment for virtual machine instruction set management. In this architecture, it is necessary to ensure that host hardware (such as CPU and memory), virtualization software (QEMU-KVM series versions), BIOS configuration, operating system kernel, and other components are all in a monitorable and configurable state, laying the architectural foundation for subsequent identification and management of virtual machine instruction set-related factors.

[0024] In a well-established cloud computing architecture environment, identifying the underlying factors of the virtual machine instruction set requires starting with the core elements that affect the effectiveness of the instruction set. These underlying factors specifically include: the host CPU model and generation (different models and generations of CPUs support different instruction sets; for example, Intel's Ice Lake CPUs support the AVX512 instruction set, while some earlier Skylake CPUs do not), the virtualization software version (different versions of QEMU-KVM have different instruction set adaptation capabilities; for example, QEMU-KVM-4.5.0 has better compatibility and support for new instruction sets than QEMU-KVM-1.5.3), the instruction set on / off status in the BIOS (i.e., the enable or disable status of the monitor instruction set; as a hardware initialization program, the BIOS's instruction set on / off status directly determines whether a specific instruction set is enabled at the host hardware level), the operating system kernel version and its instruction set masking policy (different versions of the Linux kernel may mask some instruction sets to ensure system stability; the kernel's masking policy directly affects the range of instruction sets that the virtual machine can call), and the CPU model explicitly specified in the virtual machine configuration (if the user manually specifies the CPU model when creating a virtual machine, it will override some of the default instruction set configurations, becoming a key underlying factor affecting the final instruction set).

[0025] Based on the identified underlying factors, the heterogeneous factors affecting virtual machine instruction sets can be further determined. These heterogeneous factors are the core elements among the underlying factors that have a differentiated impact on instruction sets, specifically manifested as: differences in CPU model and generation at the host machine level (different manufacturers and generations of CPUs support different instruction sets, which is the hardware root cause of instruction set differences), differences in virtualization software versions (different software versions have different capabilities in parsing and transmitting instruction sets, which may lead to inconsistencies in virtual machine instruction sets under the same hardware environment), differences in the state of BIOS instruction set switches (if the BIOS switch configuration is different for the same host machine model, some instruction sets may be "hardware supported but cannot be called"), differences in operating system kernel versions and masking policies (different kernel versions have different instruction set management logic, and adjustments to masking policies will directly change the set of instruction sets that the virtual machine can use), and differences in the specification of CPU models in the virtual machine configuration (user-defined CPU model parameters will break the default instruction set configuration, forming a heterogeneous impact). These factors are independent yet intertwined, collectively leading to the uncertainty of virtual machine instruction sets.

[0026] Standardizing and decomposing the aforementioned heterogeneous factors to generate metadata fields is a crucial step in achieving unified instruction set management. This decomposition must adhere to the principles of "quantifiability, comparability, and reusability," transforming heterogeneous factors into structured metadata fields. Specifically, for the host CPU model and generation, the decomposition is into fields such as "CPU Manufacturer," "CPU Model," and "CPU Generation" (e.g., "Intel," "Xeon Platinum 8375C," "Ice Lake"); for the virtualization software version, it is into fields such as "Virtualization Software Type" and "Virtualization Software Version Number" (e.g., "QEMU-KVM," "4.5.0"); for the BIOS instruction set on / off status, it is into fields such as "BIOS Instruction Set On / Off Name" and "On / Off Status" (e.g., "Monitor Instruction Set," "Enabled"); for the operating system kernel version and blocking policy, it is into fields such as "OS Kernel Version" and "Instruction Set Blocking List" (e.g., "Linux 5.14.0," "Blocks SSE4.2 Instruction Set"); and for the CPU model configured in the virtual machine, it is into the field of "Specified CPU Model for Virtual Machine" (e.g., "Skylake-client"). These standardized metadata fields fully cover the key information affecting the instruction set, providing a unified data basis for subsequent definition of machine specifications and association of benchmark instruction sets, and solving the problem of scattered instruction set configuration and lack of a unified abstract dimension in the existing technology.

[0027] In one embodiment, S200 includes: S201. Obtain the hardware and software information of the host machine and preprocess the hardware and software information; S202. Match the preprocessed hardware and software information with the metadata fields, classify each host machine to a unique corresponding machine type specification, and obtain the machine type specification of each host machine. S203. Based on the heterogeneous factors included in the model specifications, predefine a standardized baseline instruction set for each model specification; S204. Use the baseline instruction set as the instruction set set enabled by all virtual machines on the host machine of the corresponding model and specification.

[0028] In this embodiment, the first step is to acquire and preprocess the host machine's hardware and software information. The acquired information must comprehensively cover the key dimensions affecting the virtual machine instruction set, specifically including the host machine's CPU information (such as manufacturer, model, and generation, like Intel's Ice Lake and Skylake CPUs), virtualization software information (such as software type and version, e.g., QEMU-KVM-1.5.3, QEMU-KVM-4.5.0), BIOS configuration information (focusing on instruction set on / off status, i.e., whether the monitor instruction set is enabled or disabled), and operating system kernel information (including kernel version and instruction set masking policy). The preprocessing stage involves standardizing this raw information. For example, it standardizes the naming format for CPU models (avoiding identification errors caused by differences in output formats from different detection tools), verifies the integrity of the virtualization software version number (ensuring the accuracy of subsequent version matching), converts the BIOS instruction set on / off status into standard "enabled / disabled" Boolean values, and organizes the operating system kernel's instruction set masking policy and presents it in a structured list. Preprocessing eliminates redundancy and ambiguity, laying a reliable data foundation for subsequent matching operations.

[0029] Next, the preprocessed hardware and software information is matched with metadata fields to classify each host machine into a unique corresponding Machine Type Specification (MTS, which is a configurable, versionable, and reusable logical unit that aggregates key hardware and software metadata of the host machine). Previously, through standardized decomposition of factors affecting heterogeneity, metadata fields were generated including dimensions such as "CPU manufacturer-model-generation," "virtualization software type-version," "BIOS instruction set on / off status," and "OS kernel version-instruction set mask list." Each machine type specification corresponds to a unique set of metadata field combinations (for example, the metadata combination for MTS-Intel-ICX-OS7 is "Intel-IceLake CPU, QEMU-KVM-4.5.0, BIOS monitor instruction set enabled, Linux 5.14 kernel with no special instruction set mask"). During the matching process, the system compares the preprocessed hardware and software information of the host machine with the metadata fields of each machine type specification, finding a perfectly matching metadata combination, and then uniquely classifying the host machine into the corresponding machine type specification, ensuring that each host machine has a clear and unique machine type specification identifier.

[0030] Then, based on the heterogeneous factors affecting machine specifications, a standardized baseline instruction set (BIS, referring to the set of instruction sets enabled by default for all virtual machines on a host machine of that type of machine specification) is predefined for each machine specification. The heterogeneous factors affecting machine specifications (such as the range of basic instruction set support determined by the CPU generation, the type of instruction set adapted to the virtualization software version, the instruction sets allowed to be enabled by the BIOS switch, and the instruction sets not masked by the OS kernel) jointly determine the range of instruction sets that this type of host machine can stably support. When defining a baseline instruction set, the intersection of these factors needs to be considered comprehensively. For example, for the MTS-Intel-ICX-OS7 model specification, its Intel Ice Lake CPU supports instruction sets such as SSE4.2, AVX2, and AVX512. The QEMU-KVM-4.5.0 version is compatible with these instruction sets. The relevant instruction sets have been enabled in the BIOS and the OS kernel has not been disabled. Therefore, instruction sets such as SSE4.2, AVX2, and AVX512 can be aggregated into the baseline instruction set for this model specification to ensure that the baseline instruction set covers the hardware capabilities of the host machine and is compatible with the software support conditions, thus possessing standardization and stability.

[0031] Finally, the predefined baseline instruction set is used as the instruction set enabled by all virtual machines on the corresponding host machine. When a virtual machine is created on a host machine of this model, the system automatically uses the baseline instruction set as the default instruction set configuration for the virtual machine, eliminating the need for administrators to manually set multiple scattered instruction set parameters. For example, when creating an AI inference virtual machine or a database virtual machine on a host machine of the MTS-Intel-ICX-OS7 model, both will enable baseline instruction sets such as SSE4.2, AVX2, and AVX512 by default. This ensures the consistency of instruction sets for all virtual machines under the same model and avoids instruction set chaos caused by manual configuration differences. It also provides a unified basic standard for subsequent fine-tuning and hot migration compatibility verification based on the baseline instruction set.

[0032] In one embodiment, S300 includes: S301. Based on the aforementioned baseline instruction set, establish the instruction set fine-tuning function for the source host machine; S302. Obtain the trigger scenario, the target virtual machine of the source host, and the target host through the instruction set fine-tuning function; S303. Deploy an instruction set policy engine on the target host machine based on the baseline instruction set of the source host machine's model and specifications; S304. When the target virtual machine of the source host initiates a fine-tuning request, the instruction set policy engine of the target host extracts the metadata field of the target host's model and specifications. S305. Determine whether the extended instruction set of the fine-tuning request is in the extensible instruction set list based on the metadata field. S306. If the extended instruction set of the fine-tuning request is in the extensible instruction set list, the instruction set policy engine sends an instruction to the virtualization layer to grant fine-tuning permission to the target virtual machine of the source host and records the fine-tuning operation log. S307. If the extended instruction set requested for the fine-tuning is not in the list of extensible instruction sets, the fine-tuning request is immediately blocked, and an unsupported instruction set extension is indicated.

[0033] In this embodiment, an instruction set fine-tuning function for the source host is built upon the baseline instruction set. The core objective is to meet the differentiated performance requirements of specific virtual machines or application scenarios while ensuring general compatibility. This function allows for the dynamic activation of additional extended instruction sets on top of the baseline instruction set for specific virtual machines on the source host (such as virtual machines used for AI inference or database optimization). During the setup process, it is essential to ensure that the fine-tuning function is deeply bound to the machine type specification (MTS, a configurable and versionable logical unit that aggregates key hardware and software metadata of the host machine). Fine-tuning requests should only be initiated within the hardware capabilities and software compatibility supported by the machine type specification to avoid invalid configurations that exceed the actual carrying capacity of the host machine.

[0034] Obtaining the trigger scenario, the target virtual machine on the source host, and the target host through the instruction set fine-tuning function is a prerequisite for fine-tuning control. The "trigger scenario" must clearly define the business requirements for fine-tuning, such as "AI inference tasks require enabling AVX512 to improve computing power" or "database query optimization requires enabling FMA to accelerate computation," with different scenarios corresponding to different extended instruction set requirements. The "target virtual machine on the source host" is the specific virtual machine instance requiring instruction set fine-tuning; its source host machine model and specifications, as well as the currently used baseline instruction set, must be accurately identified. The "target host" is the host machine to which the virtual machine may be migrated later; its model and specifications must be obtained in advance to provide a basis for subsequent compatibility verification. After obtaining this information, the system establishes a "scenario-virtual machine-source / target host" mapping to ensure that fine-tuning operations are traceable and controllable.

[0035] Based on the baseline instruction set of the source host machine's specifications, an instruction set policy engine (a core component for managing instruction set fine-tuning behavior and verifying compatibility) is deployed on the target host machine. This engine deployment must be compatible with the target host machine's specifications. Since the source host machine's baseline instruction set determines the range of the virtual machine's basic instruction sets, the target host machine's instruction set policy engine must first synchronize the core parameters of the source host machine's baseline instruction set, and then combine this with its own machine specifications' metadata fields (such as CPU model, virtualization software version, BIOS configuration, etc.) to construct a dedicated "baseline instruction set - extended instruction set" verification logic. For example, if the source host machine's baseline instruction set includes AVX2, and the target host machine's CPU also supports AVX2 and the virtualization software version is compatible, the instruction set policy engine will include AVX2-related extended instruction sets in the verification scope, ensuring that the engine can accurately identify the extended instruction set types supported by the target host machine.

[0036] When the target virtual machine on the source host initiates a fine-tuning request, the target host's instruction set policy engine first extracts metadata fields related to the target host's machine model and specifications. These fields are derived from a standardized breakdown of factors affecting heterogeneity (CPU model and generation, virtualization software version, BIOS instruction set on / off status, OS kernel version, etc.), including key information such as "CPU manufacturer-model-generation," "virtualization software type-version," "BIOS instruction set on / off status," and "OS kernel instruction set masking list." The purpose of extracting these fields is to infer the target host's hardware capabilities and software compatibility through metadata fields, providing data to determine whether extended instruction sets are supported.

[0037] Based on the extracted metadata fields, the instruction set policy engine determines whether the extended instruction set in the fine-tuning request is in the extensible instruction set list. This list is generated based on the metadata fields of the target host machine's specifications and includes all extended instruction sets that are hardware-supported, software-compatible, and not blocked by the OS kernel. For example, if the metadata fields of the target host machine's specifications show that its CPU is Intel Ice Lake (supports AVX512), its virtualization software is QEMU-KVM-4.5.0 (compatible with AVX512), its BIOS instruction set switch has AVX512 enabled, and its OS kernel has not blocked it, then the extensible instruction set list will include AVX512; if the extended instruction set in the fine-tuning request is AVX512, it can be determined that it is in the list.

[0038] If the extended instruction set requested for fine-tuning is in the list of extensible instruction sets, the instruction set policy engine will send an instruction to the virtualization layer (such as the QEMU-KVM layer, the core layer responsible for virtual machine hardware emulation and instruction set transmission) to grant fine-tuning permissions to the target virtual machine on the source host. After receiving the instruction, the virtualization layer will add the extended instruction set to the instruction set configuration of the target virtual machine to make it effective and improve performance. At the same time, the engine will automatically record the fine-tuning operation log, which includes information such as the fine-tuning initiation time, target virtual machine identifier, extended instruction set type, and source / target host machine model and specifications, to facilitate subsequent operation and maintenance troubleshooting and auditing.

[0039] If the extended instruction set requested for fine-tuning is not in the list of extensible instruction sets (e.g., the target host CPU is of the Skylake generation and does not support AVX512, but the fine-tuning request requires AVX512 to be enabled), the instruction set policy engine will immediately block the fine-tuning request to avoid virtual machine malfunctions or subsequent hot migration failures due to incompatibility of the extended instruction set. At the same time, the engine will output a clear prompt to the administrator or business initiator, informing them that "the current target host does not support this extended instruction set", and may also provide suggestions (such as recommending host models and specifications that support this extended instruction set) to help relevant personnel adjust their fine-tuning requirements or change the target host in a timely manner.

[0040] In one embodiment, S400 includes: S401. Construct a model specification-instruction set compatibility matrix based on the instruction set strategy engine; S402. The reference instruction set compatibility relationship between each model specification and the range of scalable instruction sets supported by each model specification is recorded through the model specification-instruction set compatibility matrix. S403. When the target virtual machine of the source host initiates a hot migration request, the instruction set policy engine extracts the machine type and specifications of the source host and the instruction set status of the target virtual machine of the source host, as well as the machine type and specifications of the target host and the range of instruction sets that the target host can support. S404. Based on the machine model specification-instruction set compatibility matrix, the instruction set policy engine compares whether the machine model specifications of the source host machine and the target host machine are compatible, and whether the instruction set status of the target virtual machine on the source host machine is within the range of instruction sets supported by the target host machine.

[0041] In this embodiment, constructing a machine type specification-instruction set compatibility matrix based on the instruction set policy engine (a core component used to manage instruction set fine-tuning behavior and verify compatibility) is a key step in achieving automatic determination of virtual machine hot migration compatibility. This matrix uses the machine type specification (MTS, a configurable and versionable logical unit aggregating key host hardware and software metadata) as its core dimension, and structurally integrates the metadata fields of each machine type specification stored in the instruction set policy engine, the baseline instruction set (BIS, the set of instruction sets enabled by default for all virtual machines on a specific machine type specification host), and the range of expandable instruction sets. During the construction process, it is necessary to first clarify the composition of the baseline instruction set for each machine model (e.g., the baseline instruction set for MTS-Intel-ICX-OS7 includes SSE4.2, AVX2, and AVX512), then compile a list of extensible instruction sets supported by each machine model (determined based on metadata fields such as CPU capabilities and virtualization software compatibility), and finally establish the relationship between different machine models in matrix form to ensure that the matrix can clearly reflect the corresponding logic of "machine model - baseline instruction set - extensible instruction set", providing a queryable and calculable basis for subsequent compatibility verification.

[0042] The core function of the matrix is ​​to record the baseline instruction set compatibility relationships between various machine specifications and the range of scalable instruction sets supported by each machine specification. In the baseline instruction set compatibility record, the matrix will mark the inclusion or exclusion relationship of baseline instruction sets between different machine specifications. For example, if the baseline instruction set of MTS-Intel-SKL-OS7 is SSE4.2 and AVX2, while the baseline instruction set of MTS-Intel-ICX-OS7 includes SSE4.2, AVX2, and AVX512, the matrix will record "MTS-Intel-ICX-OS7 is compatible with the baseline instruction set of MTS-Intel-SKL-OS7 (the former includes the latter)", and otherwise it will mark incompatibility. In the extended instruction set support range record, the matrix will list the extended instruction sets that each machine specification can support separately (such as MTS-Intel-ICX-OS7 supports extended instruction sets such as FMA and AVX512_VNNI, and MTS-AMD-EPYC-OS7 supports the SVE2 extended instruction set). These ranges are strictly determined based on the metadata fields of the machine specification (such as CPU model and virtualization software version) to ensure that the recorded information is consistent with the actual capabilities of the host machine and avoid misjudgment of compatibility due to information discrepancies.

[0043] When a target virtual machine on the source host initiates a hot migration request (referring to a migration method where a virtual machine is moved from one host to another while still running without interrupting service), the instruction set policy engine automatically extracts three types of key information: First, the machine type and specifications of the source host (e.g., MTS-Intel-ICX-OS7) and the instruction set status of the target virtual machine (including the default enabled base instruction set and the finely tuned enabled extended instruction sets, such as SSE4.2, AVX2, AVX512, and FMA). This information directly reflects the instruction set foundation upon which the virtual machine currently runs. Second, the machine type and specifications of the target host (e.g., MTS-Intel-SKL-OS7). Third, the range of instruction sets supported by the target host (including its base instruction set and list of extended instruction sets, such as SSE4.2, AVX2, and FMA). During the extraction process, the policy engine interacts with the host hardware monitoring module and the virtualization software configuration interface to ensure that the information obtained is real-time and accurate, avoiding migration risks caused by information lag.

[0044] Based on the machine specification-instruction set compatibility matrix, the instruction set policy engine performs compatibility checks in two steps: First, it compares the machine specifications of the source and target hosts to determine compatibility. This involves querying the compatibility relationship of their baseline instruction sets in the matrix. If the baseline instruction set of the source host is completely included by the baseline instruction set of the target host (e.g., the source is MTS-Intel-SKL-OS7, the target is MTS-Intel-ICX-OS7), then the machine specifications are considered compatible. If the source baseline instruction set contains instructions not supported by the target (e.g., the source is MTS-Intel-ICX-OS7, the target is MTS-Intel-SKL-OS7, the source baseline instruction set includes AVX512 while the target does not), then there is a compatibility risk. Second, it compares the instruction set status of the source and target virtual machines to determine if they are within the range of instruction sets supported by the target host. This involves checking if all enabled extended instruction sets (e.g., AVX512 enabled by the source virtual machine) are in the target host's list of extensible instruction sets (this needs to be determined in conjunction with the target host's extensible range recorded in the matrix). Only when both comparison steps pass (machine specifications are compatible and virtual machine instruction set status is within the target support range) is it determined that there is no compatibility risk in hot migration; if either comparison step fails, the subsequent risk handling process will be triggered.

[0045] In one embodiment, S500 specifically includes: S501. If there is no compatibility risk and the instruction set is within the supported range, then perform a hot migration operation. S502. If there is a compatibility risk or / and the target virtual machine is not within the supported instruction set range, the extended instruction set that is incompatible with the source host is disabled through the instruction set policy engine, the instruction set range of the target virtual machine on the source host is downgraded to the instruction set range supported by the target host, and an alarm is generated.

[0046] In this embodiment, when the instruction set policy engine completes the comparison using the machine model-instruction set compatibility matrix and determines that there is no compatibility risk and the instruction set status of the target virtual machine on the source host is completely within the range of instruction sets supported by the target host, the system will perform a hot migration (a migration method in which a virtual machine is migrated from the source host to the target host while it is running, without interrupting business services). At this time, the baseline instruction set (BIS, the set of instruction sets enabled by default for virtual machines on a specific machine model) on the target virtual machine on the source host is compatible with the baseline instruction set of the target host, and the extended instruction sets (such as AVX512, FMA, etc.) previously enabled by the virtual machine through the fine-tuning function are also in the list of extensible instruction sets of the target host, fully meeting the operational requirements after migration. During hot migration, the virtualization layer (such as the QEMU-KVM layer, the core layer responsible for virtual machine hardware emulation and instruction set transfer) will smoothly transfer the virtual machine's running environment to the target host while maintaining the continuity of virtual machine memory data and process state. After the migration is completed, the virtual machine can continue to run directly based on the instruction set of the target host without restarting, ensuring the continuity and stability of business services.

[0047] If a compatibility risk is found after comparison (e.g., the base instruction set of the source host machine contains instructions that the target host does not support, or the base instruction sets of the two are not related), or / and the instruction set status of the virtual machine is not within the range of instruction sets supported by the target host (e.g., the AVX512 extended instruction set enabled by the virtual machine is not in the list of extensible instruction sets of the target host), the instruction set policy engine will start an automatic repair process. First, the engine accurately identifies incompatible extended instruction sets (i.e., instruction sets not supported by the target host) in the source host and sends instructions to the virtualization layer to disable these incompatible extended instruction sets, preventing virtual machine crashes or malfunctions after migration due to instruction set mismatch. Next, the engine downgrades the virtual machine's instruction set range to the range supported by the target host—specifically, adjusting the base instruction set to a version compatible with the target host's base instruction set while retaining the extended instruction sets supported by the target host. This ensures that the downgraded instruction set meets the basic operational requirements of the virtual machine while fully adapting to the target host's hardware and software capabilities. Finally, the engine automatically generates alarm information, including the machine type specification (MTS, a logical unit aggregating key hardware and software metadata of the host and target hosts), incompatible instruction set types, and downgrade operation details. This allows administrators to be promptly informed of instruction set adjustments during the migration process and subsequently assess whether to optimize machine type configuration or adjust the virtual machine's instruction set fine-tuning strategy based on business needs. The entire process requires no manual intervention. Through automated degradation and alarm mechanisms, the risk of hot migration failure is effectively avoided, ensuring the smooth progress of the migration process.

[0048] In one embodiment, S203 further includes: S2031. Based on the hardware and software combination of the host machine in the cloud computing architecture, assign a unique machine model specification to each host machine and bind a predefined baseline instruction set to the machine model specification; S2032. Establish a model specification-instruction set mapping library based on the model specification and the baseline instruction set, synchronize the baseline instruction set, the list of expandable instruction sets and the instruction set compatibility rules corresponding to each model specification in real time, and assign a timestamp and version identifier to each record in the model specification-instruction set mapping library. S2033. When the host machine's hardware and software configuration changes, extract the host machine's hardware and software information after the change, compare it with the metadata fields in the machine model specification-instruction set mapping library, and update the host machine's machine model specification and the bound baseline instruction set.

[0049] In this embodiment, a unique Machine Type Specification (MTS) is assigned to each host machine based on the hardware and software combination of the host machine in the cloud computing architecture. This MTS is a logical unit that aggregates key hardware and software metadata of the host machine and possesses configurable, versionable, and reusable characteristics. A predefined Baseline Instruction Set (BIS) is then bound to this MTS, which is the set of instruction sets enabled by default for all virtual machines on a host machine of a specific MTS. This is a fundamental step in achieving unified instruction set management. In mainstream KVM / QEMU cloud computing architectures, the host machine's hardware and software combination encompasses core elements such as CPU model and generation (e.g., Intel's Ice Lake and Skylake), virtualization software version (e.g., QEMU-KVM-1.5.3, QEMU-KVM-4.5.0), BIOS instruction set on / off status (enabling / disabling the monitor instruction set), and operating system kernel version and instruction set masking policies. The system first collects and standardizes the hardware and software information of each host machine, and then classifies it into a uniquely matching machine type specification based on the analysis results. For example, a host machine equipped with an Intel Ice Lake CPU, using QEMU-KVM-4.5.0 virtualization software, with the monitor instruction set enabled in the BIOS, and using the Linux 5.14 kernel will be assigned to the unique machine type specification "MTS-Intel-ICX-OS7". At the same time, based on the hardware and software capabilities covered by this machine type specification (such as the basic instruction set supported by the CPU, the range of instruction sets adapted by the virtualization software, etc.), a predefined baseline instruction set (such as an instruction set set including SSE4.2, AVX2, and AVX512) is bound to it to ensure that the instruction set management of each host machine has a unified baseline.

[0050] The system establishes a machine specification-instruction set mapping library based on machine specifications and baseline instruction sets. This library is the core data source for dynamic instruction set management and compatibility verification. It not only stores the one-to-one correspondence between each machine specification and its corresponding baseline instruction set, but also synchronously records the list of extensible instruction sets supported by each machine specification (such as AVX512_VNNI for AI inference scenarios and FMA for database optimization, determined based on the machine specification's hardware and software capabilities), as well as instruction set compatibility rules (such as the inclusion relationship of baseline instruction sets between different machine specifications and the cross-support of extensible instruction sets). To ensure the traceability and version controllability of the mapping library data, the system assigns a unique timestamp (recording the time of data creation or update) and version identifier (e.g., "MTS-Intel-ICX-OS7_V1.0") to each record in the library. The timestamp can be used to track the timeline of data changes, while the version identifier facilitates quick location of configuration states at different times during mapping library data iteration, avoiding compatibility verification deviations caused by data overwriting. In addition, the mapping library continuously updates the baseline instruction set, extensible instruction set list, and compatibility rules for each machine model through a real-time synchronization mechanism. This ensures that the data in the library remains consistent with the actual hardware and software capabilities and business requirements of the host machine, providing accurate data support for compatibility assessment and instruction set fine-tuning management during subsequent virtual machine hot migration.

[0051] When the host machine's hardware and software configuration changes (such as upgrading the virtualization software version, updating the operating system kernel, adjusting the BIOS instruction set on / off status, or replacing the CPU hardware), the system triggers a dynamic update process for the machine specifications and baseline instruction sets. First, the system automatically extracts the host machine's hardware and software information after the change (e.g., if the virtualization software is upgraded from QEMU-KVM-4.5.0 to QEMU-KVM-6.0.0, the new version information needs to be collected again; if the monitor instruction set in the BIOS is changed from "disabled" to "enabled," the new on / off status needs to be recorded), and performs standardized preprocessing on this information, converting it into a format consistent with the metadata fields (such as "virtualization software version" and "BIOS instruction set on / off status") in the machine specifications-instruction set mapping library. Next, the preprocessed change information is compared with the metadata fields in the mapping library to determine if a matching machine specification exists. If a perfectly matching machine specification exists (e.g., the changed hardware and software combination happens to correspond to "MTS-Intel-ICX-OS8" already in the mapping library), the host machine's machine specification is directly updated to the matching specification, and the corresponding baseline instruction set is bound synchronously. If no matching machine specification exists, the corresponding machine specification and the bound baseline instruction set (based on the predefined capabilities of the changed hardware and software) must first be added to the mapping library before the host machine's machine specification and baseline instruction set are updated. This process ensures that the host machine's machine specification always matches its actual hardware and software configuration, avoiding instruction set management failures or compatibility risks due to configuration changes.

[0052] In one embodiment, a virtual machine instruction management device based on machine model specifications is provided, which corresponds one-to-one with the virtual machine instruction management method based on machine model specifications described in the above embodiments. (Refer to...) Figure 3 , Figure 3 This is a schematic diagram of the functional modules of a preferred embodiment of the virtual machine instruction management device based on machine specifications according to the present invention. The modules include a data processing module 10, an instruction set module 20, a mechanism construction module 30, a risk assessment module 40, and a risk handling module 50. Detailed descriptions of each functional module are as follows: The data processing module 10 is used to acquire the heterogeneous factors affecting the virtual machine instruction set, and to standardize and decompose the heterogeneous factors to generate metadata fields. The instruction set module 20 is used to determine the model specification corresponding to each host machine based on the metadata field and the host machine's hardware and software information, and to predefine a baseline instruction set for each model specification; The mechanism construction module 30 is used to build the instruction set fine-tuning function of the source host machine on the basis of the benchmark instruction set, and to deploy the instruction set policy engine on the target host machine. The risk assessment module 40 is used to determine whether there is a compatibility risk in the instruction set by comparing the machine specifications and instruction set status of the source host and the target host through the instruction set policy engine when the virtual machine of the source host initiates a hot migration request. Risk handling module 50 is used to perform automatic instruction set downgrade operations if there is a compatibility risk.

[0053] In one embodiment, the data processing module 10 includes: Pre-built cloud computing architecture; In the context of the cloud computing architecture, identify the underlying factors of the virtual machine instruction set; Based on the underlying factors, determine the heterogeneous factors affecting the virtual machine instruction set; The aforementioned factors affecting heterogeneity are standardized and decomposed to generate metadata fields.

[0054] In one embodiment, the instruction set module 20 includes: Obtain the host machine's hardware and software information, and preprocess the hardware and software information; The preprocessed hardware and software information is matched with the metadata fields to classify each host machine into a unique corresponding model specification, thus obtaining the model specification of each host machine; Based on the heterogeneous factors included in the aforementioned model specifications, a standardized baseline instruction set is predefined for each model specification; The baseline instruction set is used as the instruction set set enabled by all virtual machines on the corresponding host machine.

[0055] In one embodiment, the mechanism construction module 30 includes: Based on the aforementioned baseline instruction set, a fine-tuning function for the source host instruction set is built. The trigger scenario, the target virtual machine of the source host, and the target host are obtained through the instruction set fine-tuning function; Based on the baseline instruction set of the source host machine's model and specifications, deploy an instruction set policy engine on the target host machine; When the target virtual machine of the source host initiates a fine-tuning request, the instruction set policy engine of the target host extracts the metadata field of the target host's model and specifications. Determine whether the extended instruction set of the fine-tuning request is in the list of extensible instruction sets based on the metadata fields. If the extended instruction set requested for the fine-tuning is in the list of extensible instruction sets, the instruction set policy engine sends an instruction to the virtualization layer to grant fine-tuning permission to the target virtual machine of the source host and records the fine-tuning operation log. If the extended instruction set requested for the fine-tuning is not in the list of extensible instruction sets, the fine-tuning request is immediately blocked, and an unsupported instruction set extension is indicated.

[0056] In one embodiment, the risk assessment module 40 includes: A model specification-instruction set compatibility matrix is ​​constructed based on the instruction set strategy engine. The model specification-instruction set compatibility matrix records the baseline instruction set compatibility relationship between various model specifications, as well as the range of scalable instruction sets supported by each model specification. When the target virtual machine on the source host initiates a hot migration request, the instruction set policy engine extracts the machine type and specifications of the source host and the instruction set status of the target virtual machine on the source host, as well as the machine type and specifications of the target host and the range of instruction sets that the target host can support. Based on the machine model specification-instruction set compatibility matrix, the instruction set policy engine compares whether the machine model specifications of the source host machine and the target host machine are compatible, and whether the instruction set status of the target virtual machine on the source host machine is within the range of instruction sets supported by the target host machine.

[0057] In one embodiment, the risk processing module 50 specifically includes: If there is no compatibility risk and the instruction set is within the supported range, then perform a hot migration operation; If there is a compatibility risk or / and the target virtual machine is not within the supported instruction set range, the extended instruction set that is incompatible with the source host is disabled through the instruction set policy engine, the instruction set range of the target virtual machine on the source host is downgraded to the instruction set range supported by the target host, and an alarm is generated.

[0058] In one embodiment, based on the heterogeneous factors included in the model specification, a standardized baseline instruction set is predefined for each model specification, further comprising: Based on the hardware and software combination of the host machine in the cloud computing architecture, a unique machine model specification is assigned to each host machine, and a predefined baseline instruction set is bound to the machine model specification; Establish a model specification-instruction set mapping library based on model specifications and baseline instruction sets, synchronize the baseline instruction sets, expandable instruction set lists and instruction set compatibility rules corresponding to each model specification in real time, and assign a timestamp and version identifier to each record in the model specification-instruction set mapping library. When the host machine's hardware and software configuration changes, the host machine's hardware and software information after the change is extracted and compared with the metadata fields in the machine specification-instruction set mapping library to update the host machine's machine specification and the bound base instruction set.

[0059] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used for communication with external user terminals via a network connection. When the computer program is executed by the processor, it implements the functions or steps of a machine-specific virtual machine instruction management method on the server side.

[0060] In one embodiment, a computer device is provided, which may be a user terminal, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The network interface is used to communicate with an external server via a network connection. When the computer program is executed by the processor, it implements the functions or steps on the user side of a virtual machine instruction management method based on machine specifications. In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps: Obtain the heterogeneous factors affecting the virtual machine instruction set, and standardize and decompose the heterogeneous factors to generate metadata fields; Based on the metadata fields and the host machine's hardware and software information, determine the machine model and specifications corresponding to each host machine, and predefine a baseline instruction set for each machine model and specifications; Based on the baseline instruction set, an instruction set fine-tuning function is built on the source host machine, and an instruction set policy engine is deployed on the target host machine; When the virtual machine on the source host initiates a hot migration request, the instruction set policy engine compares the machine specifications and instruction set status of the source host and the target host to determine whether there is a compatibility risk in the instruction set. If there is a compatibility risk, an automatic instruction set downgrade operation will be performed.

[0061] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor: Obtain the heterogeneous factors affecting the virtual machine instruction set, and standardize and decompose the heterogeneous factors to generate metadata fields; Based on the metadata fields and the host machine's hardware and software information, determine the machine model and specifications corresponding to each host machine, and predefine a baseline instruction set for each machine model and specifications; Based on the baseline instruction set, an instruction set fine-tuning function is built on the source host machine, and an instruction set policy engine is deployed on the target host machine; When the virtual machine on the source host initiates a hot migration request, the instruction set policy engine compares the machine specifications and instruction set status of the source host and the target host to determine whether there is a compatibility risk in the instruction set. If there is a compatibility risk, an automatic instruction set downgrade operation will be performed.

[0062] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the server side and user side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0063] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0064] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0065] It should be noted that if any software tools or components not belonging to this company appear in the embodiments of this application, they are merely illustrative examples and do not represent actual use. The embodiments described above are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A virtual machine instruction management method based on machine model specifications, characterized in that, Includes the following steps: Obtain the heterogeneous factors affecting the virtual machine instruction set, and standardize and decompose the heterogeneous factors to generate metadata fields; Based on the metadata fields and the host machine's hardware and software information, determine the machine model and specifications corresponding to each host machine, and predefine a baseline instruction set for each machine model and specifications; Based on the baseline instruction set, an instruction set fine-tuning function is built on the source host machine, and an instruction set policy engine is deployed on the target host machine; When the virtual machine on the source host initiates a hot migration request, the instruction set policy engine compares the machine specifications and instruction set status of the source host and the target host to determine whether there is a compatibility risk in the instruction set. If there is a compatibility risk, an automatic instruction set downgrade operation will be performed.

2. The virtual machine instruction management method based on machine model specifications as described in claim 1, characterized in that, The process involves acquiring the heterogeneous factors affecting the virtual machine instruction set, standardizing and decomposing these heterogeneous factors, and generating metadata fields, including: Pre-built cloud computing architecture; In the context of the cloud computing architecture, identify the underlying factors of the virtual machine instruction set; Based on the underlying factors, determine the heterogeneous factors affecting the virtual machine instruction set; The aforementioned factors affecting heterogeneity are standardized and decomposed to generate metadata fields.

3. The virtual machine instruction management method based on machine model specifications as described in claim 1, characterized in that, The step involves determining the machine model and specifications corresponding to each host machine based on the metadata fields and the host machine's hardware and software information, and predefining a baseline instruction set for each machine model and specifications, including: Obtain the host machine's hardware and software information, and preprocess the hardware and software information; The preprocessed hardware and software information is matched with the metadata fields to classify each host machine into a unique corresponding model specification, thus obtaining the model specification of each host machine; Based on the heterogeneous factors included in the aforementioned model specifications, a standardized baseline instruction set is predefined for each model specification; The baseline instruction set is used as the instruction set set enabled by all virtual machines on the corresponding host machine.

4. The virtual machine instruction management method based on machine model specifications as described in claim 1, characterized in that, The step involves building an instruction set fine-tuning function on the source host machine based on the baseline instruction set, and deploying an instruction set policy engine on the target host machine, including: Based on the aforementioned baseline instruction set, a fine-tuning function for the source host instruction set is built. The trigger scenario, the target virtual machine of the source host, and the target host are obtained through the instruction set fine-tuning function; Based on the baseline instruction set of the source host machine's model and specifications, deploy an instruction set policy engine on the target host machine; When the target virtual machine of the source host initiates a fine-tuning request, the instruction set policy engine of the target host extracts the metadata field of the target host's model and specifications. Determine whether the extended instruction set of the fine-tuning request is in the list of extensible instruction sets based on the metadata fields. If the extended instruction set requested for the fine-tuning is in the list of extensible instruction sets, the instruction set policy engine sends an instruction to the virtualization layer to grant fine-tuning permission to the target virtual machine of the source host and records the fine-tuning operation log. If the extended instruction set requested for the fine-tuning is not in the list of extensible instruction sets, the fine-tuning request is immediately blocked, and an unsupported instruction set extension is indicated.

5. The virtual machine instruction management method based on machine model specifications as described in claim 1, characterized in that, When the virtual machine on the source host initiates a hot migration request, the instruction set policy engine compares the machine specifications and instruction set status of the source and target host to determine whether there are any compatibility risks with the instruction sets, including: A model specification-instruction set compatibility matrix is ​​constructed based on the instruction set strategy engine. The model specification-instruction set compatibility matrix records the baseline instruction set compatibility relationship between various model specifications, as well as the range of scalable instruction sets supported by each model specification. When the target virtual machine on the source host initiates a hot migration request, the instruction set policy engine extracts the machine type and specifications of the source host and the instruction set status of the target virtual machine on the source host, as well as the machine type and specifications of the target host and the range of instruction sets that the target host can support. Based on the machine model specification-instruction set compatibility matrix, the instruction set policy engine compares whether the machine model specifications of the source host machine and the target host machine are compatible, and whether the instruction set status of the target virtual machine on the source host machine is within the range of instruction sets supported by the target host machine.

6. The virtual machine instruction management method based on machine model specifications as described in claim 1, characterized in that, If there is a compatibility risk, an automatic instruction set downgrade operation will be performed, specifically including: If there is no compatibility risk and the instruction set is within the supported range, then perform a hot migration operation; If there is a compatibility risk or / and the target virtual machine is not within the supported instruction set range, the extended instruction set that is incompatible with the source host is disabled through the instruction set policy engine, the instruction set range of the target virtual machine on the source host is downgraded to the instruction set range supported by the target host, and an alarm is generated.

7. The virtual machine instruction management method based on machine model specifications as described in claim 3, characterized in that, Based on the heterogeneous factors included in the aforementioned model specifications, a standardized baseline instruction set is predefined for each model specification, and also includes: Based on the hardware and software combination of the host machine in the cloud computing architecture, a unique machine model specification is assigned to each host machine, and a predefined baseline instruction set is bound to the machine model specification; Establish a model specification-instruction set mapping library based on model specifications and baseline instruction sets, synchronize the baseline instruction sets, expandable instruction set lists and instruction set compatibility rules corresponding to each model specification in real time, and assign a timestamp and version identifier to each record in the model specification-instruction set mapping library. When the host machine's hardware and software configuration changes, the host machine's hardware and software information after the change is extracted and compared with the metadata fields in the machine specification-instruction set mapping library to update the host machine's machine specification and the bound base instruction set.

8. A virtual machine instruction management device based on machine model specifications, characterized in that, The virtual machine instruction management device based on machine model specifications includes: The data processing module is used to acquire the heterogeneous factors affecting the virtual machine instruction set, and to standardize and decompose the heterogeneous factors to generate metadata fields. The instruction set module is used to determine the model specification corresponding to each host machine based on the metadata field and the host machine's hardware and software information, and to predefine a baseline instruction set for each model specification; The mechanism construction module is used to build the instruction set fine-tuning function of the source host machine based on the benchmark instruction set, and to deploy the instruction set policy engine on the target host machine; The risk assessment module is used to determine whether there is a compatibility risk of the instruction set when the virtual machine of the source host initiates a hot migration request, by comparing the machine specifications and instruction set status of the source host and the target host through the instruction set policy engine. The risk handling module is used to perform automatic instruction set downgrade operations if there are compatibility risks.

9. A computer device, characterized in that, The computer device includes a memory, a processor, and a machine-specific virtual machine instruction manager stored in the memory and executable on the processor. When executed by the processor, the machine-specific virtual machine instruction manager implements the steps of the machine-specific virtual machine instruction management method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a virtual machine instruction manager based on machine specifications. When the virtual machine instruction manager based on machine specifications is executed by the processor, it implements the steps of the virtual machine instruction management method based on machine specifications as described in any one of claims 1-7.

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