CN117472550A - Computing power sharing system based on AIGC - Google Patents
Computing power sharing system based on AIGC Download PDFInfo
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Abstract
本发明提供了一种基于AIGC的算力共享系统，所述系统包括资源注册管理模块、智能调度模块、性能监控模块和交互模块；所述资源注册管理模块用于管理参与共享的计算资源；所述智能调度模块用于根据计算资源状态智能分配计算任务至对应的计算资源；所述性能监控模块用于监控各计算资源的运行状态和任务执行情况；所述交互模块用于完成用户与系统之间的交互；本发明通过对于计算资源与计算任务之间的智能匹配，从而提高了系统的资源利用效率。
The invention provides a computing power sharing system based on AIGC. The system includes a resource registration management module, an intelligent scheduling module, a performance monitoring module and an interaction module; the resource registration management module is used to manage the computing resources participating in the sharing; The intelligent scheduling module is used to intelligently allocate computing tasks to corresponding computing resources according to the status of computing resources; the performance monitoring module is used to monitor the running status and task execution of each computing resource; the interactive module is used to complete the interaction between users and the system. The present invention improves the resource utilization efficiency of the system through intelligent matching between computing resources and computing tasks.
Description
Technical Field
The invention relates to the field of computing power sharing systems, in particular to an AIGC-based computing power sharing system.
Background
Under the current technical environment, along with the rapid development of the fields of artificial intelligence, big data analysis, scientific calculation and the like, the demand for efficient and reliable computing resources is rapidly increased; particularly when dealing with complex data analysis, machine learning training, or large-scale computing tasks, it is often difficult for a single user or organization to afford the required high computational resource costs; in addition, with the popularization and development of cloud computing technology, sharing computing resources through networks has become a trend; the traditional resource allocation method often cannot fully utilize the potential of distributed computing resources, and meanwhile, lacks enough flexibility to adapt to the continuously-changing computing demands; the AIGC technology can automatically create, optimize and adjust content using advanced artificial intelligence algorithms, which in the area of computing power sharing means that computing resources can be intelligently managed and scheduled.
Consulting the related published technical proposal, the technology with publication number of CN113535343B provides a computational power sharing method based on network scheduling and related products, which are applied to a distributed computing system, wherein the distributed computing system comprises an application function network element, a computing cooperation end and a computing demand end; the method comprises the following steps: firstly, after receiving computing power service request information from a computing cooperation end or a computing demand end, an application function network element sends computing power service capability inquiry information to a preset target, wherein the preset target comprises the computing cooperation end and/or the computing demand end, then the application function network element receives response information from the preset target, provides computing power sharing method service according to the response information, and finally the application function network element receives notification information, wherein the notification information comprises notification information sent by the preset target when the preset target determines that the computing power sharing method service is completed; by the method, the high efficiency and the convenience of the calculation force sharing method are improved; however, the scheme cannot dynamically allocate the computing tasks according to the service life and the computing power of the computing resources, so that unbalanced use of the computing resources and reduced computing efficiency are caused.
Disclosure of Invention
The invention aims to provide an AIGC-based computing power sharing system aiming at the defects existing at present.
The invention adopts the following technical scheme:
an AIGC-based computing power sharing system comprises a resource registration management module, an intelligent scheduling module, a performance monitoring module and an interaction module;
the resource registration management module is used for managing the computing resources participating in sharing; the intelligent scheduling module is used for intelligently distributing the computing tasks to the corresponding computing resources according to the computing resource state; the performance monitoring module is used for monitoring the running state and task execution condition of each computing resource; the interaction module is used for completing interaction between a user and the system;
the resource registration management module manages the specific content of the computing resources, including registering and classifying the computing resource information participating in sharing, including hardware specification information, service life information and computing capability information of each computing resource;
the resource registration management module further comprises an updating unit, wherein the updating unit is used for updating the service life information of each computing resource;
the specific content monitored by the performance monitoring module comprises the running state of each computing resource, the utilization rate of the computing resource and the execution condition of the computing task;
further, the intelligent scheduling module comprises a receiving unit, a matching unit and a scheduling execution unit, wherein the receiving unit is used for receiving a calculation task request sent by a user, the matching unit is used for completing matching between a calculation task and a calculation resource, and the scheduling execution unit is used for controlling the calculation resource to execute a corresponding calculation task according to a matching result of the matching unit;
further, before the matching unit completes the matching between the computing task and the computing resource, a priority index is set for each computing resource based on the AIGC technology according to the computing resource information registered by the resource registration management module, and the priority index satisfies the following formula:
；
wherein,for the priority index of a certain computing resource, +.>For the remaining lifetime of the computing resource, +.>For the total lifetime of the computing resource, +.>Obtaining hardware specification information of the computing resource for the computing capability of the computing resource;
further, the specific process of the matching unit executing the matching between the computing task and the computing resource includes:
s31: acquiring a calculation task in a current receiving unit;
s32: acquiring the current running state and the current utilization rate of each computing resource, and extracting the non-running computing resources and computing resources with the utilization rate less than 100 percent;
s33: sequencing the non-running computing resources according to the priority index, and distributing computing tasks from large to small according to the priority index; after the currently non-running computing resources are distributed with computing tasks, if the computing tasks are not distributed, entering the next step;
s34: sequencing the computing resources with the utilization rate less than 100% in the step S32 according to the priority index, and distributing computing tasks from large to small according to the priority index;
an AIGC-based computational power sharing method applied to an AIGC-based computational power sharing system, the method comprising:
s1: resource registration and update: the computing resource provider registers the computing resource through the resource registration management module;
s2: submitting a computing task: the user uploads and submits the calculation task through the interaction module;
s3: and (3) resource matching: calculating a priority index, and matching corresponding computing resources for each computing task according to the priority index;
s4: performing a computing task: according to the matching result of the previous step, each computing resource executes a corresponding computing task, and the execution condition of the task and the utilization rate of the computing resource are monitored in real time;
s5: and (3) result feedback: after the calculation task is completed, the calculation result is transmitted to the user through the interaction module, so that the user can check and download the calculation result.
The beneficial effects obtained by the invention are as follows:
the invention can ensure that the information of all computing resources is kept up to date through the updating unit of the resource registration management module, thereby improving the accuracy of resource allocation;
by setting the performance monitoring module, the running state and the task execution condition of the resource can be tracked in real time, and the problems can be found and solved in time; the stability and the reliability of the system are ensured;
by arranging the intelligent scheduling module, the system can ensure that computing resources are utilized most effectively, and resource idling conditions are reduced; by setting the priority index, the residual service life and the computing capacity of the computing resource are comprehensively considered, and the intelligent and dynamic resource allocation is realized; the method not only improves the utilization efficiency of resources and prevents the premature wear of the resources, but also shortens the calculation time of calculation tasks according to the intensity of calculation capability; adapting to diversified computing task requirements.
Drawings
The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. Like reference numerals designate corresponding parts throughout the different views.
FIG. 1 is a schematic diagram of the overall module of the present invention.
Fig. 2 is a schematic flow chart of an AIGC-based computing power sharing method of the present invention.
FIG. 3 is a flow chart of a method for matching a computing task with a computing resource performed by a matching unit according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the following examples thereof; it should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the invention; other systems, methods, and/or features of the present embodiments will be or become apparent to one with skill in the art upon examination of the following detailed description; it is intended that all such additional systems, methods, features and advantages be included within this description; included within the scope of the invention and protected by the accompanying claims; additional features of the disclosed embodiments are described in, and will be apparent from, the following detailed description.
The same or similar reference numbers in the drawings of embodiments of the invention correspond to the same or similar components; in the description of the present invention, it should be understood that, if there is an azimuth or positional relationship indicated by terms such as "upper", "lower", "left", "right", etc., based on the azimuth or positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but it is not indicated or implied that the apparatus or component referred to must have a specific azimuth, construction and operation in which the term is described in the drawings is merely illustrative, and it is not to be construed that the term is limited to the patent, and specific meanings of the term may be understood by those skilled in the art according to specific circumstances.
Embodiment one: as shown in fig. 1, the present embodiment provides an AIGC-based computing power sharing system, which includes a resource registration management module, an intelligent scheduling module, a performance monitoring module, and an interaction module;
the resource registration management module is used for managing the computing resources participating in sharing; the intelligent scheduling module is used for intelligently distributing the computing tasks to the corresponding computing resources according to the computing resource state; the performance monitoring module is used for monitoring the running state and task execution condition of each computing resource; the interaction module is used for completing interaction between a user and the system;
the resource registration management module manages the specific content of the computing resources, including registering and classifying the computing resource information participating in sharing, including hardware specification information, service life information and computing capability information of each computing resource;
the resource registration management module further comprises an updating unit, wherein the updating unit is used for updating the service life information of each computing resource;
the specific content monitored by the performance monitoring module comprises the running state of each computing resource, the utilization rate of the computing resource and the execution condition of the computing task;
further, the intelligent scheduling module comprises a receiving unit, a matching unit and a scheduling execution unit, wherein the receiving unit is used for receiving a calculation task request sent by a user, the matching unit is used for completing matching between a calculation task and a calculation resource, and the scheduling execution unit is used for controlling the calculation resource to execute a corresponding calculation task according to a matching result of the matching unit;
further, before the matching unit completes the matching between the computing task and the computing resource, a priority index is set for each computing resource based on the AIGC technology according to the computing resource information registered by the resource registration management module, and the priority index satisfies the following formula:
；
wherein,for the priority index of a certain computing resource, +.>For the remaining lifetime of the computing resource, +.>For the total lifetime of the computing resource, +.>Obtaining hardware specification information of the computing resource for the computing capability of the computing resource;
further, as shown in fig. 3, the specific process of the matching unit performing matching between the computing task and the computing resource includes:
s31: acquiring a calculation task in a current receiving unit;
s32: acquiring the current running state and the current utilization rate of each computing resource, and extracting the non-running computing resources and computing resources with the utilization rate less than 100 percent;
s33: sequencing the non-running computing resources according to the priority index, and distributing computing tasks from large to small according to the priority index; after the currently non-running computing resources are distributed with computing tasks, if the computing tasks are not distributed, entering the next step;
s34: sequencing the computing resources with the utilization rate less than 100% in the step S32 according to the priority index, and distributing computing tasks from large to small according to the priority index;
as shown in fig. 2, the present embodiment provides an AIGC-based computing power sharing method, which is applied to an AIGC-based computing power sharing system, and the method includes:
s1: resource registration and update: the computing resource provider registers the computing resource through the resource registration management module;
s2: submitting a computing task: the user uploads and submits the calculation task through the interaction module;
s3: and (3) resource matching: calculating a priority index, and matching corresponding computing resources for each computing task according to the priority index;
s4: performing a computing task: according to the matching result of the previous step, each computing resource executes a corresponding computing task, and the execution condition of the task and the utilization rate of the computing resource are monitored in real time;
s5: and (3) result feedback: after the calculation task is completed, the calculation result is transmitted to the user through the interaction module, so that the user can check and download the calculation result.
Embodiment two: this embodiment should be understood to include at least all of the features of any one of the foregoing embodiments, and be further modified based thereon;
the embodiment provides an AIGC-based computing power sharing system, which comprises a resource registration management module, an intelligent scheduling module, a performance monitoring module and an interaction module;
the resource registration management module is used for managing the computing resources participating in sharing; the intelligent scheduling module is used for intelligently distributing the computing tasks to the corresponding computing resources according to the computing resource state; the performance monitoring module is used for monitoring the running state and task execution condition of each computing resource; the interaction module is used for completing interaction between a user and the system;
the resource registration management module manages the specific content of the computing resources, including registering and classifying the computing resource information participating in sharing, including hardware specification information, service life information and computing capability information of each computing resource;
the resource registration management module further comprises an updating unit, wherein the updating unit is used for updating the service life information of each computing resource;
the specific content monitored by the performance monitoring module comprises the running state of each computing resource, the utilization rate of the computing resource and the execution condition of the computing task;
further, the intelligent scheduling module comprises a receiving unit, a matching unit and a scheduling execution unit, wherein the receiving unit is used for receiving a calculation task request sent by a user, the matching unit is used for completing matching between a calculation task and a calculation resource, and the scheduling execution unit is used for controlling the calculation resource to execute a corresponding calculation task according to a matching result of the matching unit;
further, the computing resource information managed by the resource registration management module further includes computing capability information of a computing resource, where the computing capability of the computing resource is obtained by the following formula:
；
wherein,for the computing power of a certain computing resource, +.>For CPU performance index, ++>For a set maximum CPU performance index, +.>Memory performance index>For a set maximum memory performance index, +.>In order to store the speed performance index,a performance index is stored for the set maximum speed;、And->The value of the weight factor is regulated according to different calculation task types;
further, the CPU performance indexThe method meets the following conditions:
；
wherein,for the CPU core number of the computing resource, +.>Clock frequency for the computing resource CPU;
the memory performance indexThe memory size for the computing resource;
the storage speed performance indexThe method meets the following conditions:
；
wherein,a data read speed for the computing resource;A data write speed for the computing resource;
further, before the matching unit completes the matching between the computing task and the computing resource, a priority index is set for each computing resource based on the AIGC technology according to the computing resource information registered by the resource registration management module, and the priority index satisfies the following formula:
；
wherein,for the priority index of a certain computing resource, +.>For the remaining lifetime of the computing resource, +.>For the total lifetime of the computing resource, +.>Obtaining hardware specification information of the computing resource for the computing capability of the computing resource;
in this embodiment, the specific process of executing the matching between the computing task and the computing resource by the matching unit includes:
s31: acquiring a computing task in a current receiving unit, and classifying the computing task into a computing-intensive task and a data-intensive task according to the type of the computing task; if the video rendering class task is classified as a computation-intensive task, the large-scale log analysis task is classified as a data-intensive task;
s32: acquiring the current running state and the current utilization rate of each computing resource, and extracting the non-running computing resources and computing resources with the utilization rate less than 100 percent;
s33: sequencing the non-running computing resources according to the priority index, distributing computing tasks from large to small according to the priority index, and entering the next step if the computing tasks are not distributed after the computing tasks are distributed to the currently non-running computing resources;
s34: sequencing the computing resources with the utilization rate less than 100% in the step S32 according to the priority index, and distributing computing tasks from large to small according to the priority index;
further, in the step S33, the specific process of allocating the computing task to the computing resource that is not currently running includes:
s331: extracting a computation-intensive task in the current computation task;
s332: extracting non-running computing resources, and computing priority indexes of the computing resources, wherein in the priority index computation of the computing resources, setting is performed，，Distributing the computing resources to compute intensive tasks according to the priority index from large to small;
s333: extracting a data-intensive task in a current computing task;
s334: extracting the computing resources with the utilization rate of less than 100% after the distribution in the step S332, and computing each computing resourceThe priority index of the source is set in the priority index calculation for each calculation resource，，Distributing the data-intensive tasks from large to small according to the priority index of each computing resource;
further, in the step S34, the specific process of allocating the computing task to the computing resource whose current usage rate does not reach 100% includes:
s341: extracting a computation-intensive task in the current computation task;
s342: extracting computing resources with current utilization rate less than 100%, and computing priority index of each computing resource, wherein in the computing of priority index of each computing resource, setting，，Distributing the computing resources to compute intensive tasks according to the priority index from large to small;
s343: extracting a data-intensive task in a current computing task;
s344: extracting the computing resources with the utilization rate of not reaching 100% after the distribution in the step S342, and calculating the priority index of each computing resource, wherein in the calculation of the priority index of each computing resource, the following steps are set，，Distributing the data-intensive tasks from large to small according to the priority index of each computing resource;
further, the interaction module provides an interaction interface for the user to complete the interaction between the user and the system, wherein the interaction interface comprises a manager interface and a user interface, and the manager interface and the specific display content thereof comprise:
resource management interface: displaying all registered computing resource information, including hardware specifications, use states and performance indexes;
system monitoring interface: providing performance monitoring of the whole system, including utilization rate, failure rate and system load of each computing resource;
task management interface: monitoring all the in-process computing task information, including task allocation information, execution state information and historical record information of computing tasks;
user management interface: managing user account information including user authority settings, account status information, and usage history information;
the user interface machine specifically presents content comprising:
task submission interface: users can submit their computing tasks through this interface;
status monitoring interface: providing a real-time monitoring function, so that a user can track the execution state of the task, the use condition of resources and the expected completion time;
results acquisition interface: users can download or directly view the results of their computing tasks through this interface;
according to the embodiment, the priority index is dynamically adjusted according to different calculation task types, so that each calculation task can be further ensured to be allocated to the most suitable calculation resource, the resource utilization rate is remarkably improved, and the performance requirements of different types of tasks are simultaneously ensured to be met;
the embodiment provides an AIGC-based computing power sharing method, which is applied to an AIGC-based computing power sharing system, and includes:
s1: resource registration and update: the computing resource provider registers the computing resource through the resource registration management module;
s2: submitting a computing task: the user uploads and submits the calculation task through the interaction module;
s3: and (3) resource matching: calculating a priority index, and matching corresponding computing resources for each computing task according to the priority index;
s4: performing a computing task: according to the matching result of the previous step, each computing resource executes a corresponding computing task, and the execution condition of the task and the utilization rate of the computing resource are monitored in real time;
s5: and (3) result feedback: after the calculation task is completed, the calculation result is transmitted to the user through the interaction module, so that the user can check and download the calculation result.
The foregoing disclosure is only a preferred embodiment of the present invention and is not intended to limit the scope of the invention, so that all equivalent technical changes made by applying the description of the present invention and the accompanying drawings are included in the scope of the present invention, and in addition, elements in the present invention can be updated as the technology develops.
Claims (5)
1. An AIGC-based computing power sharing system is characterized by comprising a resource registration management module, an intelligent scheduling module, a performance monitoring module and an interaction module;
the resource registration management module is used for managing the computing resources participating in sharing; the intelligent scheduling module is used for intelligently distributing the computing tasks to the corresponding computing resources according to the computing resource state; the performance monitoring module is used for monitoring the running state and task execution condition of each computing resource; the interaction module is used for completing interaction between a user and the system;
the resource registration management module manages the specific content of the computing resources, including registering and classifying the computing resource information participating in sharing, including hardware specification information, service life information and computing capability information of each computing resource;
the resource registration management module further comprises an updating unit, wherein the updating unit is used for updating the service life information of each computing resource;
the specific content monitored by the performance monitoring module comprises the running state of each computing resource, the utilization rate of the computing resource and the execution condition of the computing task.
2. The AIGC-based computing power sharing system of claim 1, wherein the intelligent scheduling module includes a receiving unit for receiving a computing task request sent by a user, a matching unit for completing matching between the computing task and the computing resource, and a scheduling execution unit for controlling the computing resource to execute the corresponding computing task according to a matching result of the matching unit.
3. The AIGC-based computing power sharing system of claim 2, wherein the matching unit sets a priority index for each computing resource based on an AIGC technique according to computing resource information registered by the resource registration management module before matching of the computing task with the computing resource is completed, the priority index satisfying the following formula:
；
wherein,for the priority index of a certain computing resource, +.>For the remaining lifetime of the computing resource, +.>For the total lifetime of the computing resource, +.>And obtaining the hardware specification information of the computing resource for the computing capability of the computing resource.
4. The AIGC based computing power sharing system of claim 3, wherein the matching unit performs the matching between the computing tasks and the computing resources comprising:
s31: acquiring a calculation task in a current receiving unit;
s32: acquiring the current running state and the current utilization rate of each computing resource, and extracting the non-running computing resources and computing resources with the utilization rate less than 100 percent;
s33: sequencing the non-running computing resources according to the priority index, and distributing computing tasks from large to small according to the priority index; after the currently non-running computing resources are distributed with computing tasks, if the computing tasks are not distributed, entering the next step;
s34: and (3) sequencing the computing resources with the utilization rate less than 100% in the step S32 according to the priority index, and distributing computing tasks from large to small according to the priority index.
5. An AIGC-based computational power sharing method applied to an AIGC-based computational power sharing system, the method comprising:
s1: resource registration and update: the computing resource provider registers the computing resource through the resource registration management module;
s2: submitting a computing task: the user uploads and submits the calculation task through the interaction module;
s3: and (3) resource matching: calculating a priority index, and matching corresponding computing resources for each computing task according to the priority index;
s4: performing a computing task: according to the matching result of the previous step, each computing resource executes a corresponding computing task, and the execution condition of the task and the utilization rate of the computing resource are monitored in real time;
s5: and (3) result feedback: after the calculation task is completed, the calculation result is transmitted to the user through the interaction module, so that the user can check and download the calculation result.
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