CN115756829A - Online editing algorithm device deployment method - Google Patents
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Abstract
The invention provides a method for deploying an online editing algorithm device, which comprises the following steps: s1, deploying an algorithm operating environment mirror image in a container arrangement management cluster, wherein the container arrangement management cluster is loaded in any GPU computing node formed by GPU physical cloud hosts; s2, arranging a loading algorithm running environment mirror image by the loading program by adopting any container, and detecting an algorithm running environment mirror image parameter according to the current operation environment; and S3, determining whether the parameters of the resource list included in the creation application input by the user accord with the rules determined by arranging the containers or not, and determining the device creation application which accords with the rules as a legal application. According to the invention, a local environment is migrated to a network in a container arrangement mode, a user can write, debug and store codes at any time, an online algorithm editing function is provided, the complexity of construction can be simplified when an algorithm operation environment is constructed, the dependence on a local machine can be reduced, and the performance is improved qualitatively.
Description
Technical Field
The invention relates to the technical field of computer networks, in particular to a deployment method of an online editing algorithm device.
Background
With the rapid development of deep learning, in order to improve the accuracy and generalization capability of the neural network, the data sets and the parameters are all rising exponentially. The online editing algorithm becomes a development trend for solving the performance bottleneck of a super-large-scale network. When an algorithm engineer edits an algorithm, providing a running environment for the algorithm is a very complicated task, and the algorithm depends on installation and script distribution, has many steps and high repeatability, and can cause faults due to negligence.
The method has the advantages that the dependence on the characteristics of different distributed training platforms is realized, the cluster management of heterogeneous equipment is realized, the use threshold of a user is reduced by the cooperative work of multiple machines such as resource distribution, task scheduling and state monitoring of the regular computing nodes, and the user can put more energy on an algorithm.
The large-scale deep learning algorithm is generally completed by multiple algorithm engineers, which means that each algorithm engineer needs to integrate the same algorithm operating environment to ensure the reliability of the algorithm. Meanwhile, many large projects depend on computer hardware, for example, many projects need to use a GPU, if one project does not have an online development environment, a company needs to prepare a GPU server for each algorithm engineer, which wastes a lot of cost, so that technicians in the field expect that the complexity of construction can be simplified when constructing an algorithm operation environment, dependence on the computer can be reduced, performance is improved qualitatively, and the algorithm engineers put more energy on the algorithm.
Therefore, an online editing algorithm device deployment method is provided.
Disclosure of Invention
In view of this, it is desirable to provide an online editing algorithm apparatus deployment method, so as to solve or alleviate technical problems in the prior art, and to provide at least one useful choice.
In order to solve the technical problem, the application adopts a technical scheme that: an online editing algorithm device deployment method, comprising the steps of:
s1, deploying an algorithm operating environment mirror image in a container arrangement management cluster, wherein the container arrangement management cluster is loaded in any GPU computing node formed by GPU physical cloud hosts;
s2, arranging a loading algorithm running environment mirror image by the loading program by adopting any container, and detecting an algorithm running environment mirror image parameter according to the current operation environment;
s3, determining whether parameters of a resource list included in a creation application input by a user accord with rules determined by arranging containers, and determining a device creation application which accords with the rules as a legal application;
and S4, entering an editing interface after the service is started according to the specified mirror image environment, and selecting an environment online editing algorithm.
Further preferred is: the container orchestration management cluster comprises Kubernets, composite, machine or Swarm;
the container arrangement management cluster is used for automatically deploying and managing the application.
Further preferred is: the mirror image environment comprises a plurality of operating environments, wherein the operating environments comprise Python3, oneFlow, pyTorch or TensorFlow, and the mirror images are stored in the local terminal.
Further preferred is: after the user submits the service creation, the instance applies for resource allocation through k8s and dispatches the resource allocation to a specific physical host;
and the GPU physical cloud host is used for computing node scheduling, data uploading and downloading and disaster tolerance.
Further preferred is: and the device is quitted abnormally in the operation process, and occupied exclusive resources are automatically released.
Further preferably: when the container arrangement management cluster and the node are managed, the method comprises the following steps:
creating a cluster: creating a cluster on a designated IP address according to a test environment, determining that a currently created machine becomes a manager node of the cluster after the cluster is created, and outputting a mode that other machines are added into the cluster, wherein the number of the manager nodes is at least three;
and (3) adding a cluster: and other machines are added into the cluster according to the adding mode of the cluster, and when the other machines are added into the cluster, the time zones of the machines added into the cluster are determined to be consistent.
Further preferably: and in the S3, if the rule is not met, the device is rejected, the establishment application is carried out, information is fed back to the user, and the user is prompted that the parameters are illegal, so that the user can modify the parameters correspondingly.
In order to solve the above technical problem, another technical solution adopted by the present application is: an online editing algorithm apparatus, comprising:
the loading module is used for loading an algorithm operating environment mirror image which is deployed in the container arrangement management cluster by a loading program;
the detection module is used for determining whether the parameters of the resource list included in the establishment application input by the user accord with the rules determined by arranging the containers according to the current operation environment detection algorithm operation environment mirror image parameters;
when the rule is met, determining the device establishment application meeting the rule as a legal application;
when the rule is not met, the rejection device establishes an application, feeds back information to the user, and prompts the user that the parameters are illegal so that the user can modify the parameters correspondingly;
the storage module is used for mapping corresponding data to a specified directory during service creation and directly taking the data from the specified directory during algorithm testing;
and the editing module is used for editing the algorithm on line.
In order to solve the above technical problem, the present application adopts another technical solution that: a computer apparatus comprising a processor, a memory coupled to the processor, having stored therein program instructions that, when executed by the processor, cause the processor to perform the steps of the online editing algorithm apparatus deployment method of any one of the preceding claims.
In order to solve the above technical problem, the present application adopts another technical solution: a storage medium storing program instructions capable of implementing the online editing algorithm device deployment method as claimed in any one of the preceding claims.
Due to the adoption of the technical scheme, the embodiment of the invention has the following advantages:
according to the invention, a local environment is migrated to a network in a container arrangement mode, a user can compile, debug and store codes at any time, an online algorithm editing function is provided, the complexity of construction can be simplified when an algorithm operation environment is constructed, the dependence on a local computer can be reduced, the performance is qualitatively improved, and an algorithm engineer can put more energy on the algorithm.
The foregoing summary is provided for the purpose of description only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features of the present invention will be readily apparent by reference to the drawings and the following detailed description.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the embodiments or technical descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a method for deploying an online editing algorithm device in accordance with the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. 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 application.
The terms "first", "second" and "third" in this application are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any indication of the number of technical features indicated. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of the feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless explicitly specifically limited otherwise. In the embodiments of the present application, all directional indicators (such as upper, lower, left, right, front, rear, 8230; \8230;) are used only to explain the relative positional relationship between the components at a specific posture (as shown in the drawing), the motion, etc., and if the specific posture is changed, the directional indicator is changed accordingly. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein may be combined with other embodiments.
As shown in fig. 1, an embodiment of the present invention provides an online editing algorithm device deployment method, including the following steps:
s1, deploying an algorithm operating environment mirror image in a container arrangement management cluster, wherein the container arrangement management cluster is loaded in any GPU computing node formed by GPU physical cloud hosts;
s2, arranging a loading algorithm running environment mirror image by the loading program by adopting any container, and detecting an algorithm running environment mirror image parameter according to the current operation environment;
s3, determining whether parameters of a resource list included in a creation application input by a user accord with a rule determined by arranging containers or not, and determining a device creation application which accords with the rule as a legal application;
and S4, entering an editing interface after the service is started according to the specified mirror image environment, and selecting an environment online editing algorithm.
In this embodiment, specifically: the container arrangement management cluster comprises any one of Kubernets, composite, machine or Swarm;
the container arrangement management cluster is used for automatically deploying and managing the application.
In this embodiment, specifically: the mirror image environment comprises a plurality of operation environments, the operation environments comprise any one of Python3, oneFlow, pyTorch or TensorFlow, and the mirror image is stored in the local terminal.
In this embodiment, specifically: after the user submits the service creation, the instance applies for resource allocation through k8s and dispatches the resource allocation to a specific physical host;
and the GPU physical cloud host is used for computing node scheduling, data uploading and downloading and disaster tolerance.
In this embodiment, specifically: and the occupied exclusive resource is automatically released because the device exits abnormally in the running process.
In this embodiment, specifically: when the container arrangement management cluster and the node are managed, the method comprises the following steps:
creating a cluster: creating a cluster on a designated IP address according to a test environment, determining that a currently created machine becomes a manager node of the cluster after the cluster is created, and outputting a mode that other machines are added into the cluster, wherein the number of the manager nodes is at least three;
and (3) adding a cluster: and other machines are added into the cluster according to the adding mode of the cluster, and when the other machines are added into the cluster, the time zones of the machines added into the cluster are determined to be consistent.
In this embodiment, specifically: and in the S3, if the rule is not met, the device is rejected, the establishment application is carried out, information is fed back to the user, and the user is prompted that the parameters are illegal, so that the user can modify the parameters correspondingly.
In this embodiment: the device deployment of the online editing algorithm provided by the invention comprises the following steps:
(1) The online algorithm editing device of the present disclosure is based on container orchestration, such as kubernets, which can automatically deploy and manage applications.
(2) According to project requirements, generating an algorithm operating environment mirror image, wherein the mirror image can comprise a plurality of operating environments such as Python3, oneFlow, pyTorch, tensorFlow and the like, and storing the mirror image in a local terminal.
(3) The device provides one-stop hosting service based on high-performance GPU computing nodes, a user does not need to worry about the problems of computing node scheduling, data uploading and downloading, disaster tolerance and the like after submitting service creation, all the nodes are composed of GPU physical cloud hosts, and the instances are scheduled to specific physical hosts through k8s application of resource allocation.
(4) The data source input by the device supports nfs or minio as stored data. When the service is established, the corresponding data is mapped to the specified directory of the device, and when the algorithm is tested, the data can be directly taken from the specified directory of the device.
(5) FIG. 1 is a flow chart of an online editing algorithm apparatus of the present disclosure. Although fig. 1 shows some steps of a deployment method, it is not intended that a method according to the present disclosure necessarily include all of the steps in the illustrated flow chart.
After the user inputs the device, at step S3, it is determined whether the parameters of the resource list included in the creation application input by the user conform to the rules determined by the container arrangement, and the device creation application conforming to the rules is determined as a legal application. If the rules are not met, the establishing application of the rejection device is carried out, information is fed back to the user, and the user is prompted that the parameters are illegal, so that the user can modify the parameters correspondingly.
(6) As described above, the device can be compatible with various deep learning algorithm frameworks, fully utilizes the characteristics of k8s resource isolation and convenient management, realizes the deployment of online editing algorithms, simplifies the complex repeated flow of building environments, and enables algorithm engineers to concentrate on the algorithms. The user only needs to simply deploy for the first time, and the purpose of using by multiple people can be achieved.
(7) When the device exits due to abnormality in the operation process, occupied exclusive resources can be automatically released; (8) The device provides functions of compiling, debugging, saving codes and the like for an algorithm engineer.
For other details of the technical solution for implementing each module in the block-level backup apparatus for excluding files in the foregoing embodiment, reference may be made to the description in the block-level backup method for excluding files in the foregoing embodiment, and details are not repeated here.
It should be noted that, in the present specification, the embodiments are all described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other. For the system-class embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
In order to solve the above technical problem, another technical solution adopted by the present application is: an online editing algorithm apparatus, comprising:
the loading module is used for loading an algorithm operating environment mirror image which is deployed in the container arrangement management cluster by a loading program;
the detection module is used for determining whether the parameters of the resource list included in the creation application input by the user meet the rules determined by arranging the container according to the operation environment mirror image parameters of the current operation environment detection algorithm;
when the rule is met, determining the device establishment application meeting the rule as a legal application;
when the rule is not met, the rejection device establishes an application, feeds back information to the user, and prompts the user that the parameters are illegal so that the user can modify the parameters correspondingly;
the storage module is used for mapping corresponding data to a specified directory during service creation and directly taking the data from the specified directory during algorithm testing;
and the editing module is used for editing the algorithm on line.
In order to solve the above technical problem, the present application adopts another technical solution that: a computer apparatus comprising a processor, a memory coupled to the processor, having stored therein program instructions that, when executed by the processor, cause the processor to perform the steps of the online editing algorithm apparatus deployment method as claimed in any one of the preceding claims.
The processor is called a CPU (Central Processing Unit). The processor may be an integrated circuit chip having signal processing capabilities. The processor may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In order to solve the above technical problem, the present application adopts another technical solution that: a storage medium storing program instructions capable of implementing the method for deploying an online editing algorithm device according to any one of the above methods, wherein the program instructions may be stored in the storage medium in the form of a software product, and include instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the method according to each embodiment 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, or various media capable of storing program codes, or a computer device such as a computer, a server, a mobile phone, or a tablet. The server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), and a big data and artificial intelligence platform.
In the several embodiments provided in the present application, it should be understood that the disclosed terminal, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. The above embodiments are merely examples and are not intended to limit the scope of the present disclosure, and all modifications, equivalents, and flow charts using the contents of the specification and drawings of the present disclosure or those directly or indirectly applied to other related technical fields are intended to be included in the scope of the present disclosure.
Claims (10)
1. An online editing algorithm device deployment method is characterized by comprising the following steps:
s1, deploying an algorithm operating environment mirror image in a container arrangement management cluster, wherein the container arrangement management cluster is loaded in any GPU computing node formed by GPU physical cloud hosts;
s2, arranging a loading algorithm running environment mirror image by the loading program by adopting any container, and detecting an algorithm running environment mirror image parameter according to the current operation environment;
s3, determining whether parameters of a resource list included in a creation application input by a user accord with a rule determined by arranging containers or not, and determining a device creation application which accords with the rule as a legal application;
and S4, entering an editing interface after starting service according to the specified mirror image environment, and selecting an environment online editing algorithm.
2. The method for deploying an online editing algorithm device according to claim 1, wherein: the container arrangement management cluster comprises Kubernets, composite, machine or Swarm;
the container arrangement management cluster is used for automatically deploying and managing the application.
3. The method for deploying an online editing algorithm device according to claim 1, wherein: the mirror image environment comprises a plurality of operation environments, wherein the operation environments comprise Python3, oneFlow, pyTorch or TensorFlow, and the mirror image is stored in a local terminal.
4. The method for deploying an online editing algorithm device according to claim 1, wherein: after the user submits the service creation, the instance applies for resource allocation through k8s and dispatches the resource allocation to a specific physical host;
and the GPU physical cloud host is used for computing node scheduling, data uploading and downloading and disaster tolerance.
5. The method for deploying an online editing algorithm device according to claim 1, wherein: and the device is quitted abnormally in the operation process, and occupied exclusive resources are automatically released.
6. The method for deploying an online editing algorithm device according to claim 1, wherein: when the container arrangement management cluster and the node management are carried out, the method comprises the following steps:
creating a cluster: creating a cluster on a designated IP address according to a test environment, determining that a currently created machine becomes a manager node of the cluster after the cluster is created, and outputting a mode that other machines are added into the cluster, wherein the number of the manager nodes is at least three;
and (3) adding a cluster: and other machines are added into the cluster according to the adding mode of the cluster, and when the other machines are added into the cluster, the time zones of the machines added into the cluster are determined to be consistent.
7. The method for deploying an online editing algorithm device according to claim 1, wherein: and in the S3, if the rule is not met, the device is rejected, the establishment application is carried out, information is fed back to the user, and the user is prompted that the parameters are illegal, so that the user can modify the parameters correspondingly.
8. An online editing algorithm device according to any one of claims 1 to 7, characterized by comprising:
the loading module is used for loading an algorithm operating environment mirror image which is deployed in the container arrangement management cluster by a loading program;
the detection module is used for determining whether the parameters of the resource list included in the creation application input by the user meet the rules determined by arranging the container according to the operation environment mirror image parameters of the current operation environment detection algorithm;
when the rule is met, determining the device establishment application meeting the rule as a legal application;
when the rule is not met, the rejection device establishes an application, feeds back information to the user, and prompts the user that the parameters are illegal so that the user can modify the parameters correspondingly;
the storage module is used for mapping corresponding data to a specified directory during service creation, and directly taking the data from the specified directory during algorithm testing;
and the editing module is used for editing the algorithm on line.
9. A computer device comprising a processor, a memory coupled to the processor, having stored therein program instructions that, when executed by the processor, cause the processor to perform the steps of the online editing algorithm apparatus deployment method of any one of claims 1-7.
10. A storage medium storing program instructions capable of implementing the online editing algorithm apparatus deployment method of any one of claims 1 to 7.
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