CN112861346A - Data processing system, method and electronic equipment - Google Patents
Data processing system, method and electronic equipment Download PDFInfo
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Abstract
The embodiment of the application provides a data processing system, a data processing method and electronic equipment, wherein the system comprises a scheduling server and a plurality of cloud computing servers communicated with the scheduling server, and each cloud computing server is prestored with a plurality of specific computing engines and specific computing engine types corresponding to the specific computing engines; based on the method, when the scheduling server responds to a computing request sent by the user terminal, a computing task identifier is generated, and a target cloud computing server is determined from the plurality of cloud computing servers based on a preset scheduling rule, and the target cloud computing server performs data processing on data to be processed to obtain a computing result. In the method, the computing engine is installed on the cloud computing server, the computing engine does not need to be installed in a laboratory computer, the hard disk space is saved, the installation time is saved, and the cloud computing server is faster than the laboratory computer in operation speed, so that the computing speed of simulation computing is improved, and the teaching time is shortened.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a data processing system, a data processing method, and an electronic device.
Background
Simulation deduction is a core link in virtual simulation experiment teaching, and the simulation deduction actually calculates an experiment result by using a mathematical calculation method and simulates real experiment behaviors, at present, common simulation calculation engines comprise Matlab, Multisim, Powerworld and the like, when the simulation calculation is carried out by using the calculation engines, software packages corresponding to the calculation engines need to be installed on a laboratory computer, and the software packages of the calculation engines occupy larger hard disk space and have longer installation time, so that the teaching time is prolonged in the virtual simulation teaching; meanwhile, when the calculation engine is used for calculation, a large amount of CPU (central processing unit) resources and memory resources of the computer are required to be occupied, and when the laboratory computer is used for calculation, the calculation rate is reduced due to poor hardware configuration of the computer, so that the teaching time length is further increased.
Disclosure of Invention
It is therefore an object of the present invention to provide a data processing system, method and electronic device to alleviate the above technical problems.
In a first aspect, an embodiment of the present invention provides a data processing system, where the data processing system includes a scheduling server and a plurality of cloud computing servers in communication connection with the scheduling server, where each cloud computing server stores a plurality of specific computing engines and a specific computing engine type corresponding to each specific computing engine in advance; the scheduling server is used for responding to a computing request sent by the user terminal, generating a computing task identifier, determining a target cloud computing server from the plurality of cloud computing servers based on a preset scheduling rule, and sending the computing request and the computing task identifier to the target cloud computing server; the computing request carries data to be processed and a computing engine type corresponding to a computing engine used for processing the data to be processed; and the target cloud computing server is used for receiving the computing task identifier and the computing request, extracting the data to be processed and the type of the computing engine, searching for a target specific computing engine matched with the type of the computing engine, and performing data processing on the data to be processed based on the target specific computing engine to obtain a computing result carrying the computing task identifier corresponding to the data to be processed.
With reference to the first aspect, an embodiment of the present invention provides a first possible implementation manner of the first aspect, where the specific computing engine includes at least one of: system modeling simulation software, circuit system simulation software, image processing software, voice processing software and natural language processing software.
With reference to the first aspect, an embodiment of the present invention provides a second possible implementation manner of the first aspect, where the data processing system further includes a storage server in communication connection with each of the plurality of cloud computing servers; the target cloud computing server is also used for sending the computing result to the storage server, responding to the computing result to send a completion event, generating a processing completion instruction, and sending the processing completion instruction to the user terminal through the scheduling server; wherein, the processing completion instruction carries a calculation task identifier; and the storage server is used for responding to the downloading request sent by the user terminal, extracting the calculation task identifier carried by the downloading request and returning the calculation result corresponding to the calculation task identifier to the user terminal.
With reference to the second possible implementation manner of the first aspect, an embodiment of the present invention provides a third possible implementation manner of the first aspect, where the scheduling server and the storage server both transmit data with the user terminal through a web browser interface.
With reference to the first aspect, an embodiment of the present invention provides a fourth possible implementation manner of the first aspect, where the target cloud computing server is further configured to perform data processing on data to be processed or a computing result; wherein the data processing comprises at least one of: adding data, deleting data, decompressing data.
In a second aspect, an embodiment of the present invention further provides a data processing method, where the method is applied to the data processing system; the data processing system comprises a scheduling server and a plurality of cloud computing servers in communication connection with the scheduling server, wherein each cloud computing server is pre-stored with a plurality of specific computing engines and specific computing engine types corresponding to the specific computing engines; the method comprises the following steps: the scheduling server responds to a computing request sent by a user terminal, generates a computing task identifier, determines a target cloud computing server from a plurality of cloud computing servers based on a preset scheduling rule, and sends the computing request and the computing task identifier to the target cloud computing server; the computing request carries data to be processed and a computing engine type corresponding to a computing engine used for processing the data to be processed; the target cloud computing server receives the computing task identifier and the computing request, extracts the data to be processed and the type of the computing engine, searches for a target specific computing engine matched with the type of the computing engine, performs data processing on the data to be processed based on the target specific computing engine, and obtains a computing result carrying the computing task identifier and corresponding to the data to be processed.
In combination with the second aspect, an embodiment of the present invention provides a first possible implementation manner of the second aspect, wherein the specific computing engine includes at least one of: system modeling simulation software, circuit system simulation software, image processing software, voice processing software and natural language processing software.
With reference to the second aspect, an embodiment of the present invention provides a second possible implementation manner of the second aspect, where the data processing system further includes a storage server in communication connection with each of the plurality of cloud computing servers; after obtaining the calculation result corresponding to the data to be processed, the method further includes: the target cloud computing server sends the computing result to the storage server, responds to the computing result and sends a completion event to generate a processing completion instruction, and sends the processing completion instruction to the user terminal through the scheduling server; wherein, the processing completion instruction carries a calculation task identifier; and the storage server responds to the downloading request sent by the user terminal, extracts the calculation task identifier carried by the downloading request and returns the calculation result corresponding to the calculation task identifier to the user terminal.
In a third aspect, an embodiment of the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the data processing method when executing the computer program.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program performs the steps of the data processing method described above.
The embodiment of the invention has the following beneficial effects:
the embodiment of the application provides a data processing system, a method and electronic equipment, wherein the data processing system comprises a scheduling server and a plurality of cloud computing servers in communication connection with the scheduling server, and each cloud computing server is pre-stored with a plurality of specific computing engines and specific computing engine types corresponding to the specific computing engines; based on the method, the scheduling server can generate the calculation task identifier in response to the calculation request sent by the user terminal, determine the target cloud calculation server from the plurality of cloud calculation servers based on the preset scheduling rule, send the calculation request and the calculation task identifier to the target cloud calculation server, and perform data processing on the data to be processed based on the target cloud calculation server to obtain the calculation result. In the method, the computing engine is installed on the cloud computing server, the computing engine does not need to be installed in a laboratory computer, the hard disk space is saved, the installation time is saved, and the cloud computing server is faster than the laboratory computer in operation speed, so that the simulation computing speed is improved, and the teaching time is further shortened.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a block diagram of a data processing system according to an embodiment of the present invention;
fig. 2 is a flowchart of a data processing method according to an embodiment of the present invention;
FIG. 3 is a flow chart of another data processing method according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
At present, common simulation calculation engines include Matlab, Multisim, Powerworld and the like, when the calculation engines are used for simulation calculation, software packages corresponding to the calculation engines need to be installed on a laboratory computer, and the software packages of the calculation engines occupy a large hard disk space and are long in installation time, so that the teaching time is prolonged in virtual simulation teaching; meanwhile, when the calculation engine is used for calculation, a large amount of CPU (central processing unit) resources and memory resources of the computer are required to be occupied, and when the laboratory computer is used for calculation, the calculation rate is reduced due to poor hardware configuration of the computer, so that the teaching time is further prolonged. Accordingly, embodiments of the present invention provide a data processing system, a method and an electronic device to alleviate the above technical problems.
To facilitate understanding of the embodiment, a detailed description will be given of a data processing system disclosed in the embodiment of the present invention.
An embodiment of the present invention provides a data processing system, and fig. 1 shows a schematic structural diagram of a data processing system, as shown in fig. 1, the data processing system includes a scheduling server 100, and a plurality of cloud computing servers 101 communicatively connected to the scheduling server, only the cloud computing servers 101 are shown in fig. 1, and each cloud computing server stores a plurality of specific computing engines and a specific computing engine type corresponding to each specific computing engine in advance.
The particular compute engine includes at least one of: the system modeling simulation software (Matlab), the circuit simulation software (Multisim), the circuit system simulation software (Powerworld), the image processing software, the voice processing software, the natural language processing software and the like, when in actual use, a user can customize a calculation engine according to actual needs, and the method is not limited herein.
The specific calculation engine type may be understood as a unique identifier of the specific calculation engine, for the purpose of facilitating distinguishing the plurality of specific calculation engines, and in the present embodiment, the specific calculation engine type may be represented in the form of numbers, characters, and the like, and is not limited herein.
Specifically, the scheduling server is configured to generate a computation task identifier in response to a computation request sent by a user terminal, determine a target cloud computing server from a plurality of cloud computing servers based on a preset scheduling rule, and send the computation request and the computation task identifier to the target cloud computing server; the computing request carries data to be processed and a computing engine type corresponding to a computing engine used for processing the data to be processed;
the data to be processed carried in the calculation request can be contents such as scripts, files, pictures, videos, audios, compressed packets and the like, and when the calculation request is actually applied, a plurality of calculation engines can be used for processing the data to be processed, so that the calculation request also needs to carry calculation engine types corresponding to the calculation engines used for processing the data to be processed; for example, if the calculation engines used for processing the script M are the calculation engine 1 and the calculation engine 2, the calculation request needs to carry the calculation engine type corresponding to the calculation engine 1 and the calculation engine type corresponding to the calculation engine 2.
When the scheduling server receives the calculation request, a globally unique calculation task identifier is generated to identify a calculation result obtained after processing the data to be processed, where in this embodiment, the calculation task identifier may be composed of english letters and data, or may be represented in other forms, which is not limited herein.
The target cloud computing server determined from the plurality of cloud computing servers based on the preset scheduling rule is the cloud server with the largest current idle performance resources, data processing is performed on data to be processed by using the computing capacity of the target cloud computing server, computing can be completed quickly, the simulation computing time is effectively shortened, and the teaching efficiency is improved.
The scheduling rule may be a greedy policy scheduling algorithm based on task priority, an intelligent load balancing scheduling algorithm based on CPU (central processing unit) priority, or a load balancing scheduling algorithm implemented based on ant colony algorithm, and the scheduling rule may be selected according to actual needs, and is not limited herein.
The target cloud computing server is used for receiving the computing task identifier and the computing request, extracting the data to be processed and the type of the computing engine, searching the target specific computing engine matched with the type of the computing engine, and performing data processing on the data to be processed based on the target specific computing engine to obtain a computing result carrying the computing task identifier corresponding to the data to be processed.
The specific process of searching for the target specific calculation engine matched with the calculation engine type is as follows: firstly, searching a target specific calculation engine type matched with a calculation engine type in a plurality of specific calculation engine types; then, the specific computing engine corresponding to the target specific computing engine type is determined as the target specific computing engine.
For example, the specific computing engines stored in the target cloud computing server are respectively a specific computing engine 1, a specific computing engine 2, a specific computing engine 3, and a specific computing engine 4, where a specific computing engine type corresponding to the specific computing engine 1 is a, a specific computing engine type corresponding to the specific computing engine 2 is B, a specific computing engine type corresponding to the specific computing engine 3 is C, and a specific computing engine type corresponding to the specific computing engine 4 is D, and if a computing engine type carried in the computing request is C, it is determined through the above-mentioned search process that the target specific computing engine matching the computing engine type C is the specific computing engine 3, and the specific computing engine 3 is used to perform data processing on the data to be processed.
The embodiment of the application provides a data processing system, wherein the data processing system comprises a scheduling server and a plurality of cloud computing servers in communication connection with the scheduling server, wherein each cloud computing server is pre-stored with a plurality of specific computing engines and specific computing engine types corresponding to the specific computing engines; based on the method, the scheduling server can generate the calculation task identifier in response to the calculation request sent by the user terminal, determine the target cloud calculation server from the plurality of cloud calculation servers based on the preset scheduling rule, send the calculation request and the calculation task identifier to the target cloud calculation server, and perform data processing on the data to be processed based on the target cloud calculation server to obtain the calculation result. In the method, the computing engine is installed on the cloud computing server, the computing engine does not need to be installed in a laboratory computer, the hard disk space is saved, the installation time is saved, and the cloud computing server is faster than the laboratory computer in operation speed, so that the simulation computing speed is improved, and the teaching time is further shortened.
As shown in fig. 1, the data processing system further includes a storage server 102 communicatively connected to the plurality of cloud computing servers; the target cloud computing server is further used for sending the computing result to the storage server, responding to the computing result and sending a completion event to generate a processing completion instruction, and sending the processing completion instruction to the user terminal through the scheduling server; wherein, the processing completion instruction carries a calculation task identifier; and the storage server is used for responding to the downloading request sent by the user terminal, extracting the calculation task identifier carried by the downloading request and sending the calculation result corresponding to the calculation task identifier to the user terminal.
After the target cloud computing server processes the data to be processed to obtain a computing result, on one hand, the computing result is sent to a storage server to be stored, so that a subsequent user can download the computing result for use. And on the other hand, a processing completion instruction is generated in response to the calculation result sending completion event, and the processing completion instruction is sent to the user terminal through the scheduling server so as to inform the user of the completion of data processing.
In actual use, the completion instruction sent to the user terminal may prompt the user in the form of text, voice, or the like, which is not limited herein.
As shown in fig. 1, the scheduling server 100 and the storage server 102 each transmit data with a user terminal through a network interface 103. In this embodiment, the network Interface 103 is an SDK (Software Development Kit) Interface or an API (Application Programming Interface), and the network Interface may be selected according to actual needs, where the network Interface is not limited.
Generally, the target cloud computing server is further configured to perform data processing on data to be processed or a computing result; wherein the data processing comprises at least one of: adding data, deleting data, decompressing data.
In actual application, the data to be processed or the calculation result may be subjected to data processing according to the requirements of a user, or data processing is not required, in the data processing process, required data may be added to the data to be processed or the calculation result, and unnecessary data may be deleted, and if the data to be processed is in an encrypted form, the data to be processed may be decompressed by the target cloud computing server and then subjected to data processing. In the present embodiment, the specific manner of data processing is not limited.
Corresponding to the system embodiment, an embodiment of the present invention provides a data processing method, where the method is applied to the data processing system; the data processing system comprises a scheduling server and a plurality of cloud computing servers in communication connection with the scheduling server, wherein each cloud computing server is pre-stored with a plurality of specific computing engines and specific computing engine types corresponding to the specific computing engines;
referring to a flow chart of a data processing method shown in fig. 2, the method specifically includes the following steps:
step S202, a scheduling server responds to a computing request sent by a user terminal, generates a computing task identifier, determines a target cloud computing server from a plurality of cloud computing servers based on a preset scheduling rule, and sends the computing request and the computing task identifier to the target cloud computing server; the computing request carries data to be processed and a computing engine type corresponding to a computing engine used for processing the data to be processed;
wherein the specific computing engine comprises at least one of: system modeling simulation software, circuit system simulation software, image processing software, voice processing software, and natural language processing software, where no particular computational engine is limited.
Step S204, the target cloud computing server receives the computing task identifier and the computing request, extracts the data to be processed and the type of the computing engine, searches for a target specific computing engine matched with the type of the computing engine, and performs data processing on the data to be processed based on the target specific computing engine to obtain a computing result carrying the computing task identifier and corresponding to the data to be processed.
The process of processing the data to be processed in the data processing method is the same as the process of processing the data to be processed in the data processing system, and is not described in detail herein.
The embodiment of the application provides a data processing method, wherein the data processing system comprises a scheduling server and a plurality of cloud computing servers in communication connection with the scheduling server, wherein each cloud computing server is pre-stored with a plurality of specific computing engines and specific computing engine types corresponding to the specific computing engines; based on the method, the scheduling server can generate the calculation task identifier in response to the calculation request sent by the user terminal, determine the target cloud calculation server from the plurality of cloud calculation servers based on the preset scheduling rule, send the calculation request and the calculation task identifier to the target cloud calculation server, and perform data processing on the data to be processed based on the target cloud calculation server to obtain the calculation result. In the method, the computing engine is installed on the cloud computing server, the computing engine does not need to be installed in a laboratory computer, the hard disk space is saved, the installation time is saved, and the cloud computing server is faster than the laboratory computer in operation speed, so that the simulation computing speed is improved, and the teaching time is further shortened.
Generally, the data processing system further comprises a storage server in communication connection with each of the plurality of cloud computing servers; the embodiment provides another data processing method, which is implemented on the basis of the above embodiment; the embodiment focuses on a specific implementation after obtaining a calculation result corresponding to data to be processed. As shown in fig. 3, another data processing method is a flowchart, and the data processing method in this embodiment includes the following steps:
step S302, a scheduling server responds to a computing request sent by a user terminal, generates a computing task identifier, determines a target cloud computing server from a plurality of cloud computing servers based on a preset scheduling rule, and sends the computing request and the computing task identifier to the target cloud computing server; the computing request carries data to be processed and a computing engine type corresponding to a computing engine used for processing the data to be processed;
step S304, the target cloud computing server receives the computing task identifier and the computing request, extracts the data to be processed and the type of the computing engine, searches for a target specific computing engine matched with the type of the computing engine, and performs data processing on the data to be processed based on the target specific computing engine to obtain a computing result carrying the computing task identifier corresponding to the data to be processed;
step S306, the target cloud computing server sends the computing result to a storage server, responds to the computing result and sends a completion event to generate a processing completion instruction, and sends the processing completion instruction to the user terminal through the scheduling server; wherein, the processing completion instruction carries a calculation task identifier;
step S308, the storage server responds to the downloading request sent by the user terminal, extracts the calculation task identifier carried by the downloading request, and sends the calculation result corresponding to the calculation task identifier to the user terminal.
The process of storing and downloading the calculation result is the same as the process of storing and downloading the calculation result in the data processing system, and therefore, the detailed description is omitted here.
The data processing method provided by the embodiment of the invention has the same technical characteristics as the data processing system provided by the embodiment, so that the same technical problems can be solved, and the same technical effects can be achieved.
An electronic device is further provided in the embodiment of the present application, as shown in fig. 4, which is a schematic structural diagram of the electronic device, where the electronic device includes a processor 121 and a memory 120, the memory 120 stores computer-executable instructions capable of being executed by the processor 121, and the processor 121 executes the computer-executable instructions to implement the data processing method.
In the embodiment shown in fig. 4, the electronic device further comprises a bus 122 and a communication interface 123, wherein the processor 121, the communication interface 123 and the memory 120 are connected by the bus 122.
The Memory 120 may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 123 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like may be used. The bus 122 may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus 122 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one double-headed arrow is shown in FIG. 4, but that does not indicate only one bus or one type of bus.
The processor 121 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 121. The Processor 121 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and the processor 121 reads information in the memory and completes the steps of the data processing method of the foregoing embodiment in combination with hardware thereof.
The embodiment of the present application further provides a computer-readable storage medium, where the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are called and executed by a processor, the computer-executable instructions cause the processor to implement the data processing method, and specific implementation may refer to the foregoing system embodiment, and is not described herein again.
The data processing system, the data processing method, and the computer program product of the electronic device provided in the embodiments of the present application include a computer-readable storage medium storing a program code, where instructions included in the program code may be used to execute the method described in the foregoing method embodiments, and specific implementations may refer to the method embodiments and are not described herein again.
Unless specifically stated otherwise, the relative steps, numerical expressions, and values of the components and steps set forth in these embodiments do not limit the scope of the present application.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present application. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. The data processing system is characterized by comprising a scheduling server and a plurality of cloud computing servers in communication connection with the scheduling server, wherein each cloud computing server is stored with a plurality of specific computing engines and specific computing engine types corresponding to the specific computing engines in advance;
the scheduling server is used for responding to a computing request sent by a user terminal, generating a computing task identifier, determining a target cloud computing server from a plurality of cloud computing servers based on a preset scheduling rule, and sending the computing request and the computing task identifier to the target cloud computing server; the computing request carries data to be processed and a computing engine type corresponding to a computing engine used for processing the data to be processed;
the target cloud computing server is configured to receive the computing task identifier and the computing request, extract the data to be processed and the computing engine type, search for a target specific computing engine matched with the computing engine type, perform data processing on the data to be processed based on the target specific computing engine, and obtain a computing result carrying the computing task identifier corresponding to the data to be processed.
2. The data processing system of claim 1, wherein the particular compute engine comprises at least one of: system modeling simulation software, circuit system simulation software, image processing software, voice processing software and natural language processing software.
3. The data processing system of claim 1, further comprising a storage server communicatively coupled to each of the plurality of cloud computing servers;
the target cloud computing server is further configured to send the computing result to the storage server, respond to the computing result and send a completion event to generate a processing completion instruction, and send the processing completion instruction to the user terminal through the scheduling server; wherein, the processing completion instruction carries the calculation task identifier;
and the storage server is used for responding to a downloading request sent by the user terminal, extracting the calculation task identifier carried by the downloading request and returning a calculation result corresponding to the calculation task identifier to the user terminal.
4. The data processing system of claim 3, wherein the dispatch server and the storage server each communicate data with the user terminal via a network interface.
5. The data processing system of claim 1, wherein the target cloud computing server is further configured to perform data processing on the data to be processed or the computing result; wherein the data processing comprises at least one of: adding data, deleting data, decompressing data.
6. A data processing method, characterized in that the method is applied to a data processing system according to any one of claims 1 to 4; the data processing system comprises a scheduling server and a plurality of cloud computing servers in communication connection with the scheduling server, wherein each cloud computing server stores a plurality of specific computing engines and specific computing engine types corresponding to the specific computing engines in advance; the method comprises the following steps:
the scheduling server responds to a computing request sent by a user terminal, generates a computing task identifier, determines a target cloud computing server from a plurality of cloud computing servers based on a preset scheduling rule, and sends the computing request and the computing task identifier to the target cloud computing server; the computing request carries data to be processed and a computing engine type corresponding to a computing engine used for processing the data to be processed;
the target cloud computing server receives the computing task identifier and the computing request, extracts the data to be processed and the type of the computing engine, searches for a target specific computing engine matched with the type of the computing engine, and performs data processing on the data to be processed based on the target specific computing engine to obtain a computing result carrying the computing task identifier corresponding to the data to be processed.
7. The method of claim 6, wherein the particular compute engine comprises at least one of: system modeling simulation software, circuit system simulation software, image processing software, voice processing software and natural language processing software.
8. The method of claim 6, wherein the data processing system further comprises a storage server communicatively coupled to each of the plurality of cloud computing servers;
after obtaining the calculation result corresponding to the data to be processed, the method further includes:
the target cloud computing server sends the computing result to the storage server, responds to the computing result and sends a completion event to generate a processing completion instruction, and sends the processing completion instruction to the user terminal through the scheduling server; wherein, the processing completion instruction carries the calculation task identifier;
and the storage server responds to a downloading request sent by the user terminal, extracts the calculation task identifier carried by the downloading request, and returns a calculation result corresponding to the calculation task identifier to the user terminal.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the steps of the data processing method according to any of the preceding claims 6 to 8 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, performs the steps of the data processing method of any one of the preceding claims 6 to 8.
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