A general-purpose high-performance trusted computing system, method and apparatus

Abstract

This invention discloses a general-purpose high-performance trusted computing system, method, and apparatus. The system includes a central node computing unit and branch node computing units. The central node computing unit includes a central node computing model module, a central node consensus mechanism module, and a central node operation instruction module. The central node consensus mechanism module and the central node operation instruction module are both connected to the central node computing model module. The branch node computing units are respectively connected to the central node consensus mechanism module and the central node operation instruction module. Before sending computing tasks, the health status of the branch nodes is monitored to ensure the rationality of task distribution and the reliability of branch node computing. The distributed computing tasks are trusted through the consensus mechanism, a trusted label is generated for the computing tasks, and the computing results are verified to ensure the reliability of the computing results.

Description

Technical Field

[0001] This invention relates to the fields of artificial intelligence and supercomputing technology, specifically to a general-purpose high-performance trusted computing system, method, and apparatus. Background Technology

[0002] Supercomputers are computer center clusters deployed to support scientific research computing tasks in key national science and technology innovation fields. They are characterized by extremely large capacity, extremely high computing power, and excellent performance. As of 2020, the construction and deployment speed of the national supercomputer centers has gradually failed to keep up with the computing power requirements of key scientific research fields. At the same time, the manufacturing and deployment costs are extremely high, the computing load is extremely high, and the resources invested are not easy to replicate.

[0003] Meanwhile, driven by the demand for computing power, private enterprises are increasingly researching and innovating in cloud computing and distributed computing. However, existing cloud computing and distributed computing suffer from the following shortcomings: after the total computing task is divided and processed by branch nodes, data consistency cannot be guaranteed; the continued health of branch nodes during the computing process cannot be guaranteed, leading to a lack of assurance regarding the reliability of branch nodes. These two issues significantly impact the accuracy requirements of high-performance distributed computing for settlement results. Summary of the Invention

[0004] To address the aforementioned deficiencies, embodiments of the present invention disclose a general-purpose high-performance trusted computing system, method, and apparatus, which can monitor the health status of computing units, ensure the trustworthiness of branch nodes, and guarantee the reliability of computing results.

[0005] The first aspect of this invention discloses a general high-performance trusted computing system, comprising: a central node computing unit and branch node computing units. The central node computing unit includes a central node computing model module, a central node consensus mechanism module, and a central node operation instruction module. The central node consensus mechanism module and the central node operation instruction module are both connected to the central node computing model module. The branch node computing units are respectively connected to the central node consensus mechanism module and the central node operation instruction module.

[0006] The central node computing model module is used to generate multiple computing tasks based on the current total computing task, distribute the computing tasks to at least one branch node computing unit, and process the computing results returned from the branch node computing units; the central node consensus mechanism module is used to perform trust processing on the computing tasks and to perform trust verification on the computing results returned by the branch node computing units; the central node operation instruction module is used to manage the state of the branch node computing units; the branch node computing unit is used to receive computing tasks, perform computing processing on the computing tasks, and return the computing results to the central node computing model module.

[0007] A second aspect of this invention discloses a general high-performance trusted computing method, comprising:

[0008] Obtain the current total computing task and the status information of all current branch node computing units, and generate multiple computing tasks based on the total computing task and the status information. Each computing task includes computing task data and branch node information.

[0009] Each computing task is individually trusted to generate a trusted label for that computing task. The trusted label and the computing task are then combined to generate computing data. The trusted label is used to record the uniqueness and legitimacy of the computing task.

[0010] The computational data is distributed to the branch node computational units corresponding to the branch node information, so that the branch node computational units can perform computations on the computational data and receive the computational results returned by the branch node computational units.

[0011] As an optional implementation, in a second aspect of the present invention, the status information includes the number of CPUs, the types of tasks that can be processed, the memory capacity, the network speed, and the idle state.

[0012] As an optional implementation, in the second aspect of the present invention, before obtaining the status information of all current branch node computing units, the method further includes:

[0013] Receive a registration request from a branch node computing unit, the registration request including the branch node information of the branch node computing unit;

[0014] The legitimacy of the branch node computing unit is verified based on the branch node information. When the branch node computing unit is verified to be legitimate, the registration information of the branch node computing unit is received through the WebSocket protocol to establish an authentication connection with the branch node computing unit.

[0015] As an optional implementation, in a second aspect of the present invention, each of the computing tasks is subjected to trust processing to generate a trust tag for the computing task, including:

[0016] Generate a sequence number for each computing task according to preset rules, and obtain the task information of the computing task;

[0017] Extract keywords from the task information, and generate a unique code for the computing task based on the sequence number and the keywords.

[0018] As an optional implementation, in a second aspect of the present invention, the branch node calculation unit performs calculations on the calculation data, including:

[0019] The branch node computing unit parses the computing data to obtain the computing task and trust label;

[0020] The branch node computing unit compares the trusted label with the first verification data to verify the reliability of the trusted label. Once the verification is successful, the computing task is performed.

[0021] As an optional implementation, in a second aspect of the present invention, receiving the calculation result returned from the branch node computing unit includes:

[0022] Obtain the second verification data carried in the calculation result, and generate a new hash value based on the trust label and the calculation result;

[0023] Compare the new hash value with the second verification data to see if they match.

[0024] A third aspect of this invention discloses a general-purpose high-performance trusted computing device, comprising:

[0025] Task allocation module: used to obtain the current total computing task and the status information of all current branch node computing units, and generate multiple computing tasks based on the total computing task and the status information. Each computing task includes computing task data and branch node information.

[0026] Tag generation module: used to perform trust processing on each of the computing tasks to generate a trust tag for the computing task, and to merge the trust tag and computing task to generate computing data; the trust tag is used to record the uniqueness and legitimacy of the computing task;

[0027] Result return module: used to distribute the calculation data to the branch node calculation unit corresponding to the branch node information, so that the branch node calculation unit can perform calculations on the calculation data and receive the calculation results returned by the branch node calculation unit.

[0028] As an optional implementation, in a third aspect of the present invention, the status information includes the number of CPUs, the types of tasks that can be processed, the memory capacity, the network speed, and the idle state.

[0029] As an optional implementation, in the third aspect of the present invention, before obtaining the status information of all current branch node computing units, the method further includes:

[0030] Receive a registration request from a branch node computing unit, the registration request including the branch node information of the branch node computing unit;

[0031] The legitimacy of the branch node computing unit is verified based on the branch node information. When the branch node computing unit is verified to be legitimate, the registration information of the branch node computing unit is received through the WebSocket protocol to establish an authentication connection with the branch node computing unit.

[0032] As an optional implementation, in a third aspect of the present invention, each of the computing tasks is subjected to trust processing to generate a trust tag for the computing task, including:

[0033] Generate a sequence number for each computing task according to preset rules, and obtain the task information of the computing task;

[0034] Extract keywords from the task information, and generate a unique code for the computing task based on the sequence number and the keywords.

[0035] As an optional implementation, in a third aspect of the present invention, the branch node calculation unit performs calculations on the calculation data, including:

[0036] The branch node computing unit parses the computing data to obtain the computing task and trust label;

[0037] The branch node computing unit compares the trusted label with the first verification data to verify the reliability of the trusted label. Once the verification is successful, the computing task is performed.

[0038] As an optional implementation, in a third aspect of the present invention, receiving the calculation result returned from the branch node computing unit includes:

[0039] Obtain the second verification data carried in the calculation result, and generate a new hash value based on the trust label and the calculation result;

[0040] Compare the new hash value with the second verification data to see if they match.

[0041] A fourth aspect of the present invention discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calling the executable program code stored in the memory to execute the general high-performance trusted computing method disclosed in the second aspect of the present invention.

[0042] The fifth aspect of this invention discloses a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the general high-performance trusted computing method disclosed in the second aspect of this invention.

[0043] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0044] In this embodiment of the invention, the central node computing model module generates multiple computing tasks based on the current total computing task, distributes the computing tasks to at least one branch node computing unit, and processes the computing results returned from the branch node computing units. The central node consensus mechanism module performs trust processing on the computing tasks and verifies the trustworthiness of the computing results returned by the branch node computing units. The central node operation instruction module manages the status of the branch node computing units. The branch node computing units receive computing tasks, perform computing processing on the tasks, and return the computing results to the central node computing model module. Monitoring the health status of branch nodes before sending computing tasks ensures the rationality of task distribution and the reliability of branch node computing. Furthermore, for branch nodes whose health status does not meet the standards, planning can be done in advance, and other branch nodes can be selected to reassign computing tasks. The embodiment also uses a consensus mechanism to perform trust processing on the distributed computing tasks, generates trust labels for the computing tasks, and verifies the trustworthiness of the computing results to ensure the reliability of the computing results. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a schematic diagram of the module structure of a general high-performance trusted computing system disclosed in an embodiment of the present invention;

[0047] Figure 2 This is a flowchart illustrating a general high-performance trusted computing method disclosed in an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram of the structure of a general-purpose high-performance trusted computing device provided in an embodiment of the present invention;

[0049] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] It should be noted that the terms "first," "second," "third," "fourth," etc., in the specification and claims of this invention are used to distinguish different objects, not to describe a specific order. The terms "comprising" and "having," and any variations thereof, in the embodiments of this invention are intended to cover non-exclusive inclusion. Exemplarily, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

[0052] This invention discloses a general-purpose high-performance trusted computing system, method, apparatus, electronic device, and storage medium. The central node computing model module generates multiple computing tasks based on the current total computing task, distributes these tasks to at least one branch node computing unit, and processes the computing results returned from the branch node computing units. The central node consensus mechanism module performs trusted processing on the computing tasks and verifies the trusted results returned by the branch node computing units. The central node operation instruction module manages the status of the branch node computing units. The branch node computing units receive computing tasks, perform computational processing on the tasks, and return the computational results to the central node computing model module. Monitoring the health status of branch nodes before sending computing tasks ensures the rationality of task distribution and the reliability of branch node computation. Furthermore, for branch nodes whose health status does not meet the standards, pre-planning can be implemented, and computing tasks can be reassigned to other branch nodes. The embodiment also uses a consensus mechanism to perform trusted processing on the distributed computing tasks, generates trusted tags for the computing tasks, and verifies the trusted results to ensure the reliability of the computational results.

[0053] Example 1

[0054] Please see Figure 1 , Figure 1 This invention discloses a general high-performance trusted computing system, including a central node computing unit and branch node computing units. The central node computing unit includes a central node computing model module, a central node consensus mechanism module, and a central node operation instruction module. The central node consensus mechanism module and the central node operation instruction module are both connected to the central node computing model module. The branch node computing units are respectively connected to the central node consensus mechanism module and the central node operation instruction module.

[0055] Specifically, the central node computing model module generates multiple computing tasks based on the current total computing task, distributes the computing tasks to at least one branch node computing unit, and processes the computing results returned from the branch node computing units; the central node consensus mechanism module performs trust processing on the computing tasks and verifies the trustworthiness of the computing results returned by the branch node computing units; the central node operation instruction module manages the state of the branch node computing units; and the branch node computing units receive computing tasks, perform computing processing on the computing tasks, and return the computing results to the central node computing model module.

[0056] The central node operation instruction module manages the status of computing branch nodes. First, it issues a CA digital certificate to each branch node. Before receiving a computing task, each branch node computing unit proactively registers with the central node operation instruction module. After registration, the branch node is authenticated by the central node operation instruction module before starting the computing task. Additionally, the central node operation instruction module uses a heartbeat mechanism to detect the online status of each branch node computing unit after the distributed computing deployment. The registration-authentication process between the branching phase and the central node operation instruction module uses the WebSocket protocol. The central node operation instruction module evaluates the health status of branch nodes by assessing whether the task type, CPU count, memory capacity, and network speed match those at the time of registration, etc.

[0057] Example 2

[0058] Please see Figure 2 , Figure 2This is a flowchart illustrating a general high-performance trusted computing method disclosed in an embodiment of the present invention. The execution entity of the method described in this embodiment is an execution entity composed of software and / or hardware. This execution entity can receive relevant information via wired or / or wireless means and can send certain instructions. It may also have certain processing and storage functions. This execution entity can control multiple devices, such as remote physical servers or cloud servers and related software, or local hosts or servers and related software that perform related operations on devices located in a certain location. In some scenarios, it can also control multiple storage devices, which may be placed in the same location as the devices or in different locations. Figure 2 As shown, this reliable and high-performance general computing method includes the following steps:

[0059] 201. Obtain the current total computing task and the status information of all current branch node computing units, and generate multiple computing tasks based on the total computing task and the status information. Each computing task includes computing task data and branch node information.

[0060] In this step, the central node computing unit distributes the overall computing task, generating multiple computing tasks. Furthermore, the status of the branch node computing units is monitored, including evaluating the number of CPUs, the types of tasks they can handle, memory capacity, network speed, and idle status. Only when the branch node computing units are in a healthy state can their computing results be more secure and reliable.

[0061] Furthermore, before obtaining the status information of all current branch node computing units, the embodiment further includes: receiving a registration request from a branch node computing unit, the registration request including the branch node information of the branch node computing unit; verifying the legitimacy of the branch node computing unit based on the branch node information, and when the branch node computing unit is verified to be legitimate, receiving the registration information of the branch node computing unit through the WebSocket protocol to establish an authentication connection with the branch node computing unit.

[0062] 202. Perform trust processing on each of the computing tasks to generate a trust label for the computing task, and merge the trust label and the computing task to generate computing data; the trust label is used to record the uniqueness and legitimacy of the computing task.

[0063] The embodiment generates trustworthy tags by performing trustworthy processing on the computing tasks, so as to facilitate the subsequent verification of the computing results returned by the branch node computing units.

[0064] Specifically, a sequence number for each computing task is generated according to preset rules, and task information for the computing task is obtained; keywords from the task information are extracted, and a unique code for the computing task is generated based on the sequence number and the keywords.

[0065] The sequence number in the trust processing is equivalent to an encoding of the assigned computing task, while the task information refers to the computational content to be performed. Each computing task may include different computational directions, may require different computational methods, may involve different computational items, etc. Keywords from the task information are extracted, and a unique code is generated by combining the keywords with the sequence number. Specifically, different characters can be pre-defined to correspond to different codes, forming a character encoding relationship pairing table. By querying this relationship pairing table, the code corresponding to the keyword can be found, and then this code is combined with the sequence number to obtain a unique code.

[0066] 203. Distribute the computation data to the branch node computation unit corresponding to the branch node information, so that the branch node computation unit performs computation on the computation data and receives the computation result returned by the branch node computation unit.

[0067] In this step, the branch node computing unit performs calculations on the computational data, including: the branch node parses the computational data to obtain the computational task and the trust label; wherein, the trust label is the unique code obtained earlier. The branch node computing unit compares the trust label with the first verification data to verify the reliability of the trust label. If the verification is successful, the computational task is performed. The first verification data is verification data stored in the branch node computing unit; it can be a hash value or a direct unique code. For example, the branch node computing unit generates a hash value based on the sequence number sent directly from the central node computing unit, parses the unique data to obtain the sequence number, generates a new hash value from the sequence number, and compares the two to see if they match, thereby verifying the reliability of the current computational task.

[0068] Furthermore, upon receiving the calculation result returned by the branch node computing unit, the process includes: obtaining the second verification data carried in the calculation result, and generating a new hash value based on the trust label and the calculation result; comparing whether the new hash value is consistent with the second verification data.

[0069] In this step, the central node computing unit performs a trust verification on the received computing results. The computing results carry second verification data, which is a hash value generated by the branch node computing unit in combination with the trust label and the computing results. The central node computing unit generates a new hash value based on the trust label and the computing results for comparison. This can determine whether the computing results received this time are the computing results corresponding to the computing task originally sent out by the central node computing unit, thereby increasing the reliability of the computing results.

[0070] Example 3

[0071] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of a general-purpose high-performance trusted computing device disclosed in an embodiment of the present invention. Figure 3 As shown, this reliable and high-performance general-purpose computing device may include: a task allocation module 301, a tag generation module 302, and a result return module 303. The task allocation module 301 is used to obtain the current total computing task and the status information of all current branch node computing units, and generate multiple computing tasks based on the total computing task and the status information. Each computing task includes computing task data and branch node information. The tag generation module 302 is used to perform trustworthy processing on each computing task to generate a trustworthy tag for the computing task, and merge the trustworthy tag and the computing task to generate computing data. The trustworthy tag is used to record the uniqueness and legitimacy of the computing task. The result return module 303 is used to distribute the computing data to the branch node computing units corresponding to the branch node information, so that the branch node computing units can perform calculations on the computing data and receive the calculation results returned by the branch node computing units.

[0072] Before the task allocation module 301, there is also a registration module, which is used to receive the registration request of the branch node computing unit, the registration request including the branch node information of the branch node computing unit; verify the legitimacy of the branch node computing unit based on the branch node information, and when the branch node computing unit is verified to be legitimate, receive the registration information of the branch node computing unit through the WebSocket protocol to establish an authentication connection with the branch node computing unit.

[0073] The tag generation module 302 includes a tag generation submodule: used to generate a sequence number for each computing task according to preset rules, obtain task information for the computing task, extract keywords from the task information, and generate a unique code for the computing task based on the sequence number and the keywords. The preset rules for generating the sequence number can be the date the computing task was assigned, plus the timestamp at that time, and the task order.

[0074] The result return module 303 includes a calculation submodule, which is used by the branch node calculation unit to parse the calculation data to obtain the calculation task and the trust label; the branch node calculation unit compares the trust label with the first verification data to verify the reliability of the trust label, and performs calculation on the calculation task after the verification is passed.

[0075] A further embodiment also includes a result verification module, used to obtain second verification data carried in the calculation result, and generate a new hash value based on the trust label and the calculation result; and compare whether the new hash value is consistent with the second verification data.

[0076] Example 4

[0077] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. The electronic device can be a computer, a server, etc. Of course, in certain cases, it can also be a mobile phone, tablet computer, monitoring terminal, or other smart device, as well as an image acquisition device with processing capabilities. Figure 4 As shown, the electronic device may include:

[0078] Memory 401 storing executable program code;

[0079] Processor 402 coupled to memory 401;

[0080] In this process, the processor 402 calls the executable program code stored in the memory 401 to execute some or all of the steps in the general high-performance trusted computing method in Embodiment 2.

[0081] This invention discloses a computer-readable storage medium storing a computer program that causes a computer to perform some or all of the steps in the general high-performance trusted computing method of Embodiment 2.

[0082] This invention also discloses a computer program product, wherein when the computer program product is run on a computer, the computer performs some or all of the steps in the general high-performance trusted computing method of Embodiment 2.

[0083] This invention also discloses an application publishing platform, which is used to publish computer program products. When the computer program products are run on a computer, the computer performs some or all of the steps in the general high-performance trusted computing method in Embodiment 2.

[0084] In various embodiments of the present invention, it should be understood that the sequence number of each process does not necessarily imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0085] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they can be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0086] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0087] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-accessible memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several requests to cause a computer device (which can be a personal computer, server, or network device, specifically a processor in the computer device) to execute some or all of the steps of the methods described in the various embodiments of the present invention.

[0088] In the embodiments provided by this invention, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information.

[0089] Those skilled in the art will understand that some or all of the steps in the various methods of the embodiments described can be implemented by a program instructing related hardware. This program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0090] The foregoing has provided a detailed description of the general-purpose high-performance trusted computing system, method, apparatus, electronic device, and storage medium disclosed in the embodiments of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A general-purpose high-performance trusted computing system, characterized in that, include: The system includes a central node computing unit and branch node computing units. The central node computing unit comprises a central node computing model module, a central node consensus mechanism module, and a central node operation instruction module. The central node consensus mechanism module and the central node operation instruction module are both connected to the central node computing model module. The branch node computing units are respectively connected to the central node consensus mechanism module and the central node operation instruction module. The central node computing model module is used to receive registration requests from branch node computing units, and the registration request includes the branch node information of the branch node computing unit. The legitimacy of the branch node computing unit is verified based on the branch node information. When the branch node computing unit is verified to be legitimate, the registration information of the branch node computing unit is received through the WebSocket protocol to establish an authentication connection with the branch node computing unit. Multiple computing tasks are generated based on the current total computing task. These tasks are distributed to at least one branch node computing unit, and the computing results returned from the branch node computing units are processed. The central node consensus mechanism module generates a sequence number for each computing task according to preset rules, which is an encoding for that computing task. It obtains the task information of the computing task, which includes the computing direction and the corresponding computing method. Keywords from the task information are extracted, and encodings corresponding to different characters in the keywords are pre-defined to form a character encoding relationship pairing table. A unique encoding for the computing task is generated based on the sequence number and the character encoding relationship pairing table as a trust label. The trust label and the computing task are merged to generate computing data, and the computing results returned by the branch node computing units are verified for trustworthiness. After receiving the calculation result, the central node computing unit combines the calculation result returned by the branch node computing unit with the hash value generated by the trusted label as the second verification data. This hash value is then compared with the hash value generated by the trusted label and the calculation result stored locally in the central node computing unit to verify consistency. The central node operation instruction module manages the status of the branch node computing unit. The branch node computing unit receives and processes the calculation data. It uses the hash value generated from the sequence number received during registration with the central node computing unit as the first verification data. This hash value is then compared with the new hash value generated from the sequence number obtained after parsing the trusted label to verify the reliability of the trusted label. The calculation result is then returned to the central node computing model module.

2. A general high-performance trusted computing method, characterized in that, include: Receive a registration request from a branch node computing unit, the registration request including the branch node information of the branch node computing unit; The legitimacy of the branch node computing unit is verified based on the branch node information. When the branch node computing unit is verified to be legitimate, the registration information of the branch node computing unit is received through the WebSocket protocol to establish an authentication connection with the branch node computing unit. Obtain the current total computing task and the status information of all current branch node computing units, and generate multiple computing tasks based on the total computing task and the status information. Each computing task includes computing task data and branch node information. Each computing task is assigned a sequence number according to a preset rule, which is then used as an encoding for that computing task. The task information of the computing task is obtained, which is the content to be calculated by the computing task. The computing task includes the calculation direction and the corresponding calculation method. Keywords of the task information are extracted, and the encoding corresponding to different characters in the keywords is preset to form a character encoding relationship pairing table. Based on the sequence number and the character encoding relationship pairing table, a unique encoding for the computing task is generated as a trust label. The trust label and the computing task are then merged to generate computing data. The trust label is used to record the uniqueness and legitimacy of the computing task; The computational data is distributed to the branch node computational units corresponding to the branch node information, so that the branch node computational units can parse the computational data to obtain the computational task and the trust label. The branch node computing unit uses the hash value generated by the sequence number received by the branch node computing unit when registering with the central node computing unit as the first verification data. It then compares the hash value generated by the sequence number obtained after parsing the trustworthy tag with the new hash value to verify the reliability of the trustworthy tag. Once the verification is successful, the computing task is performed. The central node computing unit receives the calculation results returned by the branch node computing unit. Specifically, after receiving the calculation results, the central node computing unit compares the calculation results returned by the branch node computing unit with the hash value generated by the trusted label as the second verification data, and compares it with the hash value generated by the trusted label and the calculation results stored locally in the central node computing unit to verify whether they are consistent.

3. The general high-performance trusted computing method according to claim 2, characterized in that, The status information includes the number of CPUs, the types of tasks that can be processed, the memory capacity, the network speed, and the idle status.

4. A general-purpose, high-performance, trusted computing device, characterized in that, include: Task allocation module: used to obtain the current total computing task and the status information of all current branch node computing units, and generate multiple computing tasks based on the total computing task and the status information. Each computing task includes computing task data and branch node information. The tag generation module is used to generate a sequence number for each computing task according to preset rules, which is an encoding for that computing task; to obtain the task information of the computing task, which is the content to be calculated by the computing task, including the computing direction and the corresponding computing method; to extract keywords from the task information; to pre-set the encoding corresponding to different characters in the keywords to form a character encoding relationship pairing table; to generate a unique encoding for the computing task as a trust label based on the sequence number and the character encoding relationship pairing table; and to merge the trust label and the computing task to generate computing data. The trust label is used to record the uniqueness and legitimacy of the computing task; Result return module: used to distribute the calculation data to the branch node calculation unit corresponding to the branch node information, so that the branch node calculation unit can perform calculations on the calculation data and receive the calculation results returned by the branch node calculation unit.

5. An electronic device, characterized in that, include: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the general high-performance trusted computing method according to any one of claims 2 to 3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program causes a computer to perform the general high-performance trusted computing method according to any one of claims 2 to 3.

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