Supercomputing task scheduling method and device based on cloud native architecture, equipment and medium

Abstract

The invention discloses a supercomputing task scheduling method and device based on a cloud native architecture, equipment and a medium. The method comprises the following steps: receiving a service processing application; generating a to-be-processed task corresponding to the business processing application, and configuring a priority for the to-be-processed task; the to-be-processed tasks are issued to task queues with corresponding priorities, the to-be-processed tasks are processed according to the priorities of the task queues, the priorities of the to-be-processed tasks and the priorities of target tasks, the target tasks are currently processed tasks, and the to-be-processed tasks are processed according to the priorities of the task queues, the priorities of the to-be-processed tasks and the priorities of the target tasks. The current system comprises a plurality of task queues with different priorities. According to the technical scheme provided by the embodiment of the invention, large-scale complex tasks are better processed, the execution efficiency of the tasks and the performance of the whole system are improved, and efficient, elastic and extensible cloud computing services are provided.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a supercomputing task scheduling method, device, equipment and storage medium based on a cloud native architecture. Background Art

[0002] Cloud computing is a type of distributed computing, which means breaking down huge data computing programs into countless small programs through the network "cloud", and then processing and analyzing these small programs through multiple servers to obtain results and return them to users. With the development of cloud computing technology, more and more companies are beginning to adopt cloud computing to manage and run their businesses.

[0003] However, existing technologies may encounter problems such as unbalanced resource utilization and low task execution efficiency when processing large-scale and complex supercomputing tasks. Summary of the invention

[0004] The present invention provides a supercomputing task scheduling method, device, equipment and medium based on a cloud native architecture to solve the problem of poor effect in processing large-scale supercomputing tasks.

[0005] In a first aspect, the present invention provides a supercomputing task scheduling method based on a cloud native architecture, which is applied to a system of a cloud native architecture, comprising:

[0006] Receive business processing applications;

[0007] Generate a pending task corresponding to the business processing application, and configure a priority for the pending task;

[0008] The pending task is sent to a task queue of corresponding priority, and processed according to the priority of the task queue, the priority of the pending task and the priority of the target task, wherein the target task is the task currently being processed, and the current system contains multiple task queues of different priorities.

[0009] In a second aspect, the present invention provides a supercomputing task scheduling device based on a cloud native architecture, which is applied to a system of a cloud native architecture, including:

[0010] An application receiving module is used to receive business processing applications;

[0011] A priority configuration module, used to generate pending tasks corresponding to the business processing application and configure priorities for the pending tasks;

[0012] The task processing module is used to send the pending tasks to the task queue of the corresponding priority, and process the pending tasks according to the priority of the task queue, the priority of the pending tasks and the priority of the target task, wherein the target task is the task currently being processed, and the current system contains multiple task queues with different priorities.

[0013] In a third aspect, the present invention provides an electronic device, the electronic device comprising:

[0014] at least one processor;

[0015] and a memory communicatively coupled to the at least one processor;

[0016] Among them, the memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the supercomputing task scheduling method based on cloud native architecture of the first aspect mentioned above.

[0017] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer instructions, which are used to enable a processor to implement the supercomputing task scheduling method based on a cloud-native architecture of the first aspect when executed.

[0018] The supercomputing task scheduling solution based on cloud native architecture provided by the present invention configures the priority of the tasks to be processed in the system of the cloud native architecture based on the supercomputing task scheduling technology in the cloud native architecture where the application program is tightly integrated with the cloud computing infrastructure, and comprehensively judges the timing of processing the tasks to be processed according to the priority of the task queue, the priority of the tasks to be processed and the priority of the tasks currently being processed. This solution combines the cloud native architecture with the supercomputing task scheduling technology. When processing large-scale complex tasks, it better handles large-scale complex tasks through the tight integration of the cloud native architecture and the supercomputing task scheduling technology, improves the execution efficiency of the tasks and the performance of the overall system, and provides efficient, elastic and scalable cloud computing services.

[0019] It should be understood that the content described in this section is not intended to identify the key or important features of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 is a flowchart of a supercomputing task scheduling method based on a cloud native architecture provided according to Embodiment 1 of the present invention;

[0022] Figure 2 is a flowchart of a supercomputing task scheduling method based on a cloud native architecture provided according to Embodiment 2 of the present invention;

[0023] Figure 3 It is a structural diagram of a supercomputing task scheduling device based on a cloud native architecture provided according to Embodiment 3 of the present invention;

[0024] Figure 4 It is a schematic diagram of the structure of an electronic device provided according to Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In the description of the present invention, unless otherwise specified, "multiple" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, method, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] Cloud native architecture is an emerging cloud computing architecture that emphasizes the close integration of applications with cloud computing infrastructure to achieve efficient, elastic and scalable cloud computing services. Supercomputing task scheduling technology is a technology used to optimize computer resource utilization. It can dynamically allocate computing resources according to task priority and available resources to improve task execution efficiency.

[0028] Embodiment 1

[0029] Figure 1 A flowchart of a supercomputing task scheduling method based on a cloud native architecture is provided for the first embodiment of the present invention. This embodiment is applicable to the case of processing large-scale supercomputing tasks, the method can be applied to a system of a cloud native architecture, the method can be executed by a supercomputing task scheduling device based on a cloud native architecture, the supercomputing task scheduling device based on a cloud native architecture can be implemented in the form of hardware and / or software, the supercomputing task scheduling device based on a cloud native architecture can be configured in an electronic device, and the electronic device can be composed of two or more physical entities, or can be composed of one physical entity.

[0030] like Figure 1 As shown, the first embodiment of the present invention provides a supercomputing task scheduling method based on a cloud native architecture, which specifically includes the following steps:

[0031] S101. Receive a business processing application.

[0032] In this embodiment, a service processing application sent by a user through a client may be received.

[0033] S102: Generate a pending task corresponding to the business processing application, and configure a priority for the pending task.

[0034] In this embodiment, the corresponding pending tasks can be generated according to the business processing application, and then the priority can be configured for the pending tasks, and the processing ID can be generated. In addition to configuring the priority, the processing path can also be specified for the pending tasks, such as pre-processing, pre-processing and post-processing paths, and the task processing configuration information such as the processing system and processing program can be specified.

[0035] S103: Send the pending task to a task queue of corresponding priority, and process the pending task according to the priority of the task queue, the priority of the pending task and the priority of the target task.

[0036] The target task is the task currently being processed, and the current system includes multiple task queues with different priorities.

[0037] In the present embodiment, before the pending task is sent to the task queue of the corresponding priority, the pending task can be sent to the task processing total queue, which is used to temporarily store the pending task. Then, the pending task can be taken out from the total queue according to the sequence in the task processing total queue, and the pending task can be sent to the task queue corresponding to the priority of the pending task. Finally, the pending task is processed comprehensively according to the priority of the task queue, the priority of the pending task and the priority of the target task. For example, when the priority of the task queue where the pending task is located is the preset priority, and the priority of the pending task is higher than the target task, the target task can be suspended, and the pending task can be processed, thereby realizing the priority processing of the key real-time task.

[0038] The technical solution of the embodiment of the present invention configures the priority of the tasks to be processed in the system of the cloud native architecture based on the supercomputing task scheduling technology in the cloud native architecture where the application program is tightly integrated with the cloud computing infrastructure, and comprehensively determines the timing of processing the tasks to be processed according to the priority of the task queue, the priority of the tasks to be processed, and the priority of the tasks currently being processed. This solution combines the cloud native architecture with the supercomputing task scheduling technology. When processing large-scale complex tasks, through the tight integration of the cloud native architecture and the supercomputing task scheduling technology, large-scale complex tasks can be better processed, the execution efficiency of tasks and the performance of the overall system can be improved, and efficient, elastic, and scalable cloud computing services can be provided.

[0039] Optionally, before receiving the business processing application, it also includes: receiving a registration application for a business service corresponding to the business processing application, and generating configuration information of a new business service according to the application through a preset configuration center module, wherein the business service is a microservice in an out-of-service state; reading the configuration information through a preset service discovery center module, and obtaining service status information of the new business service through heartbeat detection.

[0040] Specifically, a preset configuration center module, a preset service discovery center module, a preset service monitoring platform and a preset API routing gateway module can be pre-arranged in the system of the cloud native architecture. The preset service discovery center module is the core part of the entire cloud native architecture, and can specifically provide service registration and discovery functions for microservices. The configuration information of the preset API routing gateway module, business services (i.e., microservices without service status) and the preset service monitoring platform module can all be registered with the preset service discovery center module. Through the above registration, the high reliability of the overall backend service can be guaranteed. By splitting the existing business applications into microservices without service status and registering these microservices with the preset service discovery center module, the non-business code part of the business application is stripped to the maximum extent, so that the cloud facilities can take over a large number of original non-functional features in the application, such as elasticity, resilience, security, observability and grayscale, so that the business is no longer troubled by non-functional business interruptions and has the characteristics of lightweight, agile and highly automated. The preset service discovery center module is responsible for managing and coordinating all cloud native services, such as supercomputing task scheduling services, etc., realizing the collaborative work between the cloud native architecture and supercomputing task scheduling technology, and giving full play to their respective advantages.

[0041] Exemplarily, before receiving the business processing application, the registration application of the cloud native business service (i.e., the business service corresponding to the business processing application) can be received through the preset API routing gateway module. Then, the configuration information of the new business service is generated according to the application through the preset configuration center module, and the configuration information is registered to the preset service discovery center module. The configuration information can be read through the preset service discovery center module, and the service status information of the new business service can be obtained by using heartbeat detection.

[0042] Optionally, it also includes: registering configuration information of a preset service monitoring platform to the preset service discovery center module; and controlling the preset service monitoring platform to monitor service status information of business services through the preset service discovery center module.

[0043] Specifically, by registering the configuration information of the preset service monitoring platform to the preset service discovery center module, the preset service monitoring platform can obtain the service status information of the business services registered to the preset service discovery center, thereby realizing the monitoring of the running status information of the business services. Finally, by collecting and displaying the running status of business services in the cloud native architecture service system, the backend service quality can be further guaranteed.

[0044] Optionally, the processing of the task to be processed according to the priority of the task queue, the priority of the task to be processed and the priority of the target task includes: using the minimum connection method to allocate computing nodes to the task to be processed according to the priority of the task queue, the priority of the task to be processed and the priority of the target task, and using the computing nodes to process the task to be processed.

[0045] Specifically, intelligent load balancing algorithms, such as the least-connected method, can be used to dynamically adjust the execution order of tasks and resource allocation according to the current resource usage and task priority (such as the priority of the task queue, the priority of the task to be processed, and the priority of the target task), and allocate computing nodes to the tasks to be processed to achieve optimal resource utilization and efficient task execution. The advantage of this setting is that it expands the system's concurrency, enables efficient resource utilization, and further solves the technical problems of unbalanced resource utilization and low task execution efficiency that may occur when processing large-scale complex tasks.

[0046] Embodiment 2

[0047] Figure 2 A flowchart of a supercomputing task scheduling method based on a cloud native architecture is provided for the second embodiment of the present invention. The technical solution of the embodiment of the present invention is further optimized on the basis of the above-mentioned optional technical solutions, and a specific method for processing large-scale supercomputing tasks is given.

[0048] Optionally, the processing of the pending task according to the priority of the task queue, the priority of the pending task and the priority of the target task includes: when the priority of the task queue is not the highest priority task queue in the current system, judging whether the highest priority task queue is empty; if not, then judging whether the priority of the target task in the current computing node is higher than or equal to the priority of the pending task if the current computing node is not idle; if lower, suspending the processing of the target task and starting to process the pending task. The advantage of such a setting is that the execution order and resource allocation of tasks can be adjusted in real time by the above method to meet the real-time requirements of tasks, thus solving the problem that the real-time requirements of tasks may not be met when processing real-time tasks.

[0049] Optionally, after determining whether the priority of the target task in the current computing node is higher than or equal to the priority of the task to be processed, it also includes: if it is higher than or equal to, then after the processing of the target task is completed, determining whether the priority of the next task to be processed by the current computing node is higher than or equal to the priority of the task to be processed, wherein the next task to be processed is determined according to the order of unprocessed tasks in the task queue associated with the current computing node.

[0050] Optionally, after determining that the priority of the target task in the current computing node is higher than or equal to the priority of the pending task, it also includes: generating real-time task log warning information and displaying the real-time task log warning information, wherein the real-time task log warning information is used to prompt that the pending task is not currently processed immediately. The advantage of such a setting is that by generating the real-time task log warning information, the user can know the processing status of the task in a timely manner.

[0051] like Figure 2 As shown, a supercomputing task scheduling method based on a cloud native architecture provided in Embodiment 2 of the present invention specifically includes the following steps:

[0052] S201. Receive a registration application for a business service corresponding to a business processing application, and generate configuration information of a new business service according to the application through a preset configuration center module, wherein the business service is a microservice in an out-of-service state; read the configuration information through a preset service discovery center module, and obtain service status information of the new business service through heartbeat detection.

[0053] S202: registering the configuration information of the preset service monitoring platform to the preset service discovery center module; and controlling the preset service monitoring platform to monitor the service status information of the business service through the preset service discovery center module.

[0054] S203, receiving a business processing application; generating a pending task corresponding to the business processing application, and configuring a priority for the pending task.

[0055] S204: Send the pending task to a task queue of corresponding priority.

[0056] S205 . When the priority of the task queue is not the highest priority task queue in the current system, determine whether the highest priority task queue is empty. If not, execute step 206 . If yes, execute step 212 .

[0057] S206. If the current computing node is not idle, determine whether the priority of the target task in the current computing node is higher than or equal to the priority of the task to be processed. If not, execute step 207; if yes, execute step 208.

[0058] Specifically, the current computing node is a computing node associated with the task queue of the current priority.

[0059] S207: Pause processing of the target task, and start processing of the pending task.

[0060] Specifically, when a real-time task (i.e., a pending task) that needs to be processed and completed within a specified time and is highly urgent is received, the computing resources of other low-priority tasks (i.e., the target task) can be preempted, a snapshot of the low-priority target task can be saved, and the target task can be paused to give up the computing resources, so that the real-time task can obtain the computing resources and be executed immediately.

[0061] S208 , generating real-time task log alarm information, and displaying the real-time task log alarm information, and executing step 209 .

[0062] The real-time task log warning information is used to prompt that the pending task is not being processed immediately.

[0063] S209, after the target task is processed, determine whether the priority of the next task to be processed by the current computing node is higher than or equal to the priority of the task to be processed, if not, execute step 210, if yes, execute step 211.

[0064] The next task to be processed is determined according to the order of unprocessed tasks in the task queue associated with the current computing node.

[0065] Specifically, the next task to be processed by the current computing node is usually the first unprocessed task in the associated task queue.

[0066] S210: Start processing the pending tasks.

[0067] S211, start processing the next task to be processed.

[0068] S212, determining whether the task queues of the lower priority level are empty, and ending when it is determined that the task queues are all empty, if not, executing step 206, if yes, executing step 212.

[0069] The supercomputing task scheduling method based on cloud native architecture provided by the embodiment of the present invention meets the real-time requirements of tasks by adjusting the execution order and resource allocation of tasks in real time, solves the problem that the real-time requirements of tasks may not be met when processing real-time tasks, and generates real-time task log alarm information to enable users to know the processing status of tasks in a timely manner, thereby realizing the collaborative work of cloud native architecture and supercomputing task scheduling.

[0070] Embodiment 3

[0071] Figure 3 This is a schematic diagram of the structure of a supercomputing task scheduling device based on a cloud native architecture provided in Embodiment 3 of the present invention. Figure 3As shown, the device is applied to a system of a cloud native architecture, and the device includes: an application receiving module 301, a priority configuration module 302 and a task processing module 303, wherein:

[0072] An application receiving module is used to receive business processing applications;

[0073] A priority configuration module, used to generate pending tasks corresponding to the business processing application and configure priorities for the pending tasks;

[0074] The task processing module is used to send the pending tasks to the task queue of the corresponding priority, and process the pending tasks according to the priority of the task queue, the priority of the pending tasks and the priority of the target task, wherein the target task is the task currently being processed, and the current system contains multiple task queues with different priorities.

[0075] The supercomputing task scheduling device based on the cloud native architecture provided by the embodiment of the present invention configures the priority of the tasks to be processed in the system of the cloud native architecture based on the supercomputing task scheduling technology in the cloud native architecture where the application program is tightly integrated with the cloud computing infrastructure, and comprehensively determines the timing of processing the tasks to be processed according to the priority of the task queue, the priority of the tasks to be processed, and the priority of the tasks currently being processed. This device combines the cloud native architecture with the supercomputing task scheduling technology. When processing large-scale complex tasks, it better handles large-scale complex tasks through the tight integration of the cloud native architecture and the supercomputing task scheduling technology, improves the execution efficiency of the tasks and the performance of the overall system, and provides efficient, elastic, and scalable cloud computing services.

[0076] Optionally, the system further includes:

[0077] A configuration information generation module, used for receiving a registration application for a business service corresponding to the business processing application before receiving the business processing application, and generating configuration information of a new business service according to the registration application through a preset configuration center module, wherein the business service is a microservice in an out-of-service state;

[0078] The information acquisition module is used to read the configuration information through a preset service discovery center module and obtain the service status information of the new business service by using heartbeat detection.

[0079] Optionally, the system further includes:

[0080] A registration module, used to register the configuration information of the preset service monitoring platform to the preset service discovery center module;

[0081] The monitoring module is used to control the preset service monitoring platform to monitor the service status information of the business service through the preset service discovery center module.

[0082] Optionally, the task processing module includes:

[0083] A first judging unit, configured to judge whether the task queue with the highest priority is empty when the priority of the task queue is not the task queue with the highest priority in the current system;

[0084] A second judgment unit is used to judge whether the priority of the target task in the current computing node is higher than or equal to the priority of the task to be processed if the information returned by the first judgment unit is no and if the current computing node is not idle;

[0085] The task suspension and processing unit is used to suspend the processing of the target task and start processing the to-be-processed task if the information returned by the second judgment unit is lower than.

[0086] Optionally, the task processing module also includes:

[0087] A third judgment unit is used to judge whether the priority of the target task in the current computing node is higher than or equal to the priority of the task to be processed after judging whether the priority of the target task in the current computing node is higher than or equal to the priority of the task to be processed, if the information returned by the second judgment unit is higher than, then after the processing of the target task is completed, whether the priority of the next task to be processed by the current computing node is higher than or equal to the priority of the task to be processed, wherein the next task to be processed is determined according to the order of unprocessed tasks in the task queue associated with the current computing node.

[0088] Optionally, the task processing module includes:

[0089] The load balancing unit is used to allocate computing nodes to the tasks to be processed according to the priority of the task queue, the priority of the tasks to be processed and the priority of the target task by using the least connection method, and use the computing nodes to process the tasks to be processed.

[0090] Optionally, the task processing module also includes:

[0091] An alarm unit is used to generate real-time task log alarm information after determining that the priority of the target task in the current computing node is higher than or equal to the priority of the task to be processed, and display the real-time task log alarm information, wherein the real-time task log alarm information is used to prompt that the task to be processed is not currently being processed immediately.

[0092] The supercomputing task scheduling device based on cloud native architecture provided in an embodiment of the present invention can execute the supercomputing task scheduling method based on cloud native architecture provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0093] Embodiment 4

[0094] Figure 4 A schematic diagram of the structure of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0095] like Figure 4 As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0096] A number of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0097] The processor 41 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 executes the various methods and processes described above, such as a supercomputing task scheduling method based on a cloud native architecture.

[0098] In some embodiments, the supercomputing task scheduling method based on the cloud native architecture may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the supercomputing task scheduling method based on the cloud native architecture described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to execute the supercomputing task scheduling method based on the cloud native architecture by any other appropriate means (e.g., by means of firmware).

[0099] Various implementations of the methods and techniques described above herein can be implemented in digital electronic circuit methods, integrated circuit methods, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), methods on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable method including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage method, at least one input device, and at least one output device, and transmit data and instructions to the storage method, the at least one input device, and the at least one output device.

[0100] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0101] The computer device provided above can be used to execute the supercomputing task scheduling method based on cloud native architecture provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0102] Embodiment 5

[0103] In the context of the present invention, a computer-readable storage medium may be a tangible medium, and the computer-executable instructions, when executed by a computer processor, are used to execute a supercomputing task scheduling method based on a cloud native architecture, the method comprising:

[0104] Receive business processing applications;

[0105] Generate a pending task corresponding to the business processing application, and configure a priority for the pending task;

[0106] The pending task is sent to a task queue of corresponding priority, and processed according to the priority of the task queue, the priority of the pending task and the priority of the target task, wherein the target task is the task currently being processed, and the current system contains multiple task queues of different priorities.

[0107] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use with or in conjunction with an instruction execution method, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor methods, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0108] The computer device provided above can be used to execute the supercomputing task scheduling method based on cloud native architecture provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0109] It is worth noting that in the above-mentioned embodiment of the supercomputing task scheduling device based on cloud-native architecture, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0110] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A supercomputing task scheduling method based on cloud native architecture, characterized in that: Applied in cloud-native architecture systems, including: Receive business processing applications; Generate a pending task corresponding to the business processing application, and configure a priority for the pending task; The pending task is sent to a task queue of corresponding priority, and processed according to the priority of the task queue, the priority of the pending task and the priority of the target task, wherein the target task is the task currently being processed, and the current system contains multiple task queues of different priorities.

2. The method according to claim 1, characterized in that: Before receiving the business processing application, the method further includes: Receive a registration application for a business service corresponding to the business processing application, and generate configuration information of a new business service according to the registration application through a preset configuration center module, wherein the business service is a microservice in an out-of-service state; The configuration information is read through a preset service discovery center module, and the service status information of the new business service is obtained by using heartbeat detection.

3. The method according to claim 2, characterized in that Also includes: Registering the configuration information of the preset service monitoring platform to the preset service discovery center module; The preset service monitoring platform is controlled to monitor the service status information of the business service through the preset service discovery center module.

4. The method according to claim 1, characterized in that: The processing of the task to be processed according to the priority of the task queue, the priority of the task to be processed and the priority of the target task includes: When the priority of the task queue is not the highest priority task queue in the current system, determining whether the highest priority task queue is empty; If not, if the current computing node is not idle, determining whether the priority of the target task in the current computing node is higher than or equal to the priority of the task to be processed; If it is lower, the processing of the target task is suspended and the processing of the pending task begins.

5. The method according to claim 4, characterized in that After determining whether the priority of the target task in the current computing node is higher than or equal to the priority of the task to be processed, the method further includes: If it is higher than or equal to, then after the target task is processed, determine whether the priority of the next task to be processed by the current computing node is higher than or equal to the priority of the task to be processed, wherein the next task to be processed is determined according to the order of unprocessed tasks in the task queue associated with the current computing node.

6. The method according to claim 1, characterized in that The processing of the task to be processed according to the priority of the task queue, the priority of the task to be processed and the priority of the target task includes: By using the minimum connection method, according to the priority of the task queue, the priority of the task to be processed and the priority of the target task, a computing node is allocated to the task to be processed, and the task to be processed is processed by using the computing node.

7. The method according to claim 4, characterized in that After determining that the priority of the target task in the current computing node is higher than or equal to the priority of the task to be processed, the method further includes: Generate real-time task log warning information, and display the real-time task log warning information, wherein the real-time task log warning information is used to prompt that the pending task is not currently processed immediately.

8. A supercomputing task scheduling device based on cloud native architecture, characterized in that: Applied in cloud-native architecture systems, including: An application receiving module is used to receive business processing applications; A priority configuration module, used to generate pending tasks corresponding to the business processing application and configure priorities for the pending tasks; The task processing module is used to send the pending tasks to the task queue of the corresponding priority, and process the pending tasks according to the priority of the task queue, the priority of the pending tasks and the priority of the target task, wherein the target task is the task currently being processed, and the current system contains multiple task queues with different priorities.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the supercomputing task scheduling method based on cloud native architecture as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the processor to implement the supercomputing task scheduling method based on cloud native architecture described in any one of claims 1 to 7 when executed.

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