CN114489867A - Algorithm module scheduling method, algorithm module scheduling device and readable storage medium - Google Patents
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Abstract
The application provides an algorithm module scheduling method, an algorithm module scheduling device and a computer readable storage medium. The algorithm module scheduling method comprises the following steps: acquiring a configuration file, wherein the configuration file comprises a plurality of algorithm modules with sequential dependency relationship of front and back results; configuring the priorities of the algorithm modules by utilizing the sequential dependency relationship of the front and rear results in the configuration file; creating a task queue according to the priorities of the algorithm modules; and processing data based on a scheduling algorithm module of the front-back relation of the queue positions in the task queue. By the method, the algorithm module scheduling method realizes self-adaptive task priority marking and queue sequencing, improves the overall processing efficiency of the algorithm scheme and prevents the algorithm scheme from being stuck.
Description
Technical Field
The present application relates to the technical field of algorithm model processing, and in particular, to an algorithm module scheduling method, an algorithm module scheduling apparatus, and a computer-readable storage medium.
Background
In the execution of the image processing algorithm program, task scheduling execution of the image processing algorithm is mostly managed in a mode of a task queue and a thread pool.
The task queue is mainly managed in a first-in first-out mode, when a task is ready, the task queue is inserted into the tail of the task queue to wait, and when an idle execution thread exists, the task is acquired from the head of the task queue to be executed.
Different algorithm modules in the current algorithm scheme have mutual dependence and sequence relation, and the first-in first-out task queue mode can cause the overall efficiency of the algorithm scheme to be low and cause the overall flow to be stuck under the condition of insufficient thread number.
Disclosure of Invention
The application provides an algorithm module scheduling method, an algorithm module scheduling device and a computer readable storage medium.
The application provides an algorithm module scheduling method, which comprises the following steps:
acquiring a configuration file, wherein the configuration file comprises a plurality of algorithm modules with sequential dependency relationship of front and back results;
configuring the priorities of the algorithm modules by utilizing the sequential dependency relationship of the front and rear results in the configuration file;
creating a task queue according to the priorities of the algorithm modules;
and processing data by a scheduling algorithm module based on the front-back relation of the queue positions in the task queue.
Wherein, the configuring the priorities of the algorithm modules by using the dependency relationship of the sequence of the front and back results in the configuration file comprises:
generating a data flow graph of the plurality of algorithm modules by utilizing the sequential dependency relationship of the front and back results in the configuration file;
and configuring the priorities of a plurality of algorithm modules in the data flow diagram from small to large according to the input and output directions of the data flow diagram.
Wherein, the creating of the task queue according to the priorities of the algorithm modules comprises:
adding a current algorithm module into the tail part of a task queue, wherein the task queue comprises a plurality of algorithm modules;
comparing the priority of the current algorithm module with the priority of the previous algorithm module in the task queue;
and when the priority of the current algorithm module is lower than that of the previous algorithm module, the position of the current algorithm module in the task queue is not adjusted.
After comparing the priority of the current algorithm module with the priority of the previous algorithm module in the task queue, the algorithm module scheduling method further comprises:
when the priority of the current algorithm module is higher than that of the previous algorithm module, exchanging the queue positions of the current algorithm module and the previous algorithm module in the task queue, and updating the task queue;
and continuously comparing the priority of the current algorithm module with the priority of the previous algorithm module in the updated task queue until the priority of the current algorithm module in the updated task queue is lower than the priority of the previous algorithm module, or the current algorithm module is positioned at the head of the updated task queue.
Wherein, the creating of the task queue according to the priorities of the algorithm modules comprises:
acquiring the priority of the current algorithm module and the priorities of all queue algorithm modules in a task queue;
comparing the priority of the current algorithm module with the priorities of all queue algorithm modules;
when the priority of the current algorithm module is higher than the priorities of all queue algorithm modules, adding the current algorithm module into the head of the task queue, and updating the task queue;
and when the priority of the current algorithm module is lower than the priority of one or more queue algorithm modules, adding the current algorithm module to the task queue at the next bit of the queue algorithm module with the lowest priority in the one or more queue algorithm modules.
The data processing based on the queue position front-back relation scheduling algorithm module in the task queue comprises the following steps:
acquiring a resource lock of the task queue, and starting to schedule an algorithm module in the task queue to process data;
acquiring a new algorithm module, and adding the new algorithm module into the task queue according to the priority;
and releasing the resource lock of the task queue after the task queue is updated.
The data processing based on the queue position front-back relation scheduling algorithm module in the task queue comprises the following steps:
acquiring equipment information, wherein the equipment information comprises a processor core number;
judging whether the number of processor cores in the equipment information is larger than a first preset threshold value or not;
if yes, creating a corresponding number of thread pools based on the processor cores, and executing the tasks in the task queue through executing threads in the corresponding number of thread pools;
and if not, creating a plurality of execution threads, putting the execution threads into one thread pool, and executing the tasks in the task queue through the execution threads in the thread pool.
Wherein the creating a corresponding number of thread pools based on the processor cores comprises:
setting a one-to-one corresponding relation between the thread pool and the processor;
and setting a plurality of execution threads in each thread pool, and setting the affinity of each execution thread and the processor corresponding to the thread pool.
After the device information is acquired, the algorithm module scheduling method further includes:
judging whether the number of processor cores in the equipment information is greater than a first preset threshold value or not, and whether an algorithm module node in the configuration file is greater than a second preset threshold value or not;
if yes, creating a corresponding number of thread pools based on the processor cores, and executing the tasks in the task queue through executing threads in the corresponding number of thread pools;
and if not, creating a plurality of execution threads, putting the execution threads into one thread pool, and executing the tasks in the task queue through the execution threads in the thread pool.
The algorithm module scheduling method further comprises the following steps:
analyzing the configuration file to obtain a plurality of algorithm nodes in the configuration file, wherein each algorithm node corresponds to at least one algorithm module;
obtaining a node input stream and a node output stream of each algorithm node;
determining the pipeline sequence of the algorithm nodes according to the node input streams and the node output streams of the algorithm nodes;
and determining the sequential dependency relationship of the front and rear results of the corresponding algorithm modules by using the pipeline sequence of the algorithm nodes.
The application also provides an algorithm module scheduling device, which comprises an acquisition module, a configuration module, a creation module and a scheduling module; wherein the content of the first and second substances,
the acquisition module is used for acquiring a configuration file, wherein the configuration file comprises a plurality of algorithm modules with sequential dependency relationship of front and back results;
the configuration module is used for configuring the priorities of the algorithm modules by utilizing the sequential dependency relationship of the front and rear results in the configuration file;
the creating module is used for creating a task queue according to the priorities of the algorithm modules;
and the scheduling module is used for processing data based on the queue position front-back relation scheduling algorithm module in the task queue.
The application also provides another algorithm module scheduling device, which comprises a processor and a memory, wherein the memory is stored with program data, and the processor is used for executing the program data to realize the algorithm module scheduling method.
The present application also provides a computer-readable storage medium for storing program data which, when executed by a processor, is used to implement the algorithm module scheduling method described above.
The beneficial effect of this application is: the method comprises the following steps that an algorithm module scheduling device obtains a configuration file, wherein the configuration file comprises a plurality of algorithm modules with sequential dependency relationship of front and back results; configuring the priorities of the algorithm modules by utilizing the sequential dependency relationship of the front and rear results in the configuration file; creating a task queue according to the priorities of the algorithm modules; and processing data by a scheduling algorithm module based on the front-back relation of the queue positions in the task queue. By the method, the algorithm module scheduling method realizes self-adaptive task priority marking and queue sequencing, improves the overall processing efficiency of the algorithm scheme and prevents the algorithm scheme from being stuck.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts. Wherein:
FIG. 1 is a schematic flow chart diagram illustrating an embodiment of an algorithm module scheduling method provided herein;
FIG. 2 is a detailed flow chart of the algorithm module scheduling method shown in FIG. 1;
FIG. 3 is a schematic diagram of one embodiment of a configuration file format provided herein;
FIG. 4 is a schematic flow chart diagram illustrating another embodiment of an algorithm module scheduling method provided herein;
FIG. 5 is a detailed flow chart of the algorithm module scheduling method shown in FIG. 4;
FIG. 6 is a schematic flow chart diagram illustrating a method for scheduling algorithm modules according to yet another embodiment of the present disclosure;
FIG. 7 is a detailed flow chart of the algorithm module scheduling method of FIG. 6;
FIG. 8 is a schematic structural diagram of an embodiment of an algorithm module scheduling apparatus provided in the present application;
FIG. 9 is a schematic structural diagram of another embodiment of an algorithm module scheduling device provided in the present application;
FIG. 10 is a schematic structural diagram of an embodiment of a computer-readable storage medium provided in the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the 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.
In order to solve the problems in the prior art, the method and the device optimize the realization of the algorithm task queue in the image processing algorithm scheme, realize self-adaptive task priority marking and queue sequencing, improve the overall processing efficiency of the algorithm scheme and prevent the algorithm scheme from being stuck, and realize the establishment and scheduling of the self-adaptive thread pool according to the complexity of the algorithm scheme and the device difference of deployment and operation, thereby improving the utilization of device resources and the overall scheme processing efficiency.
Referring to fig. 1 and fig. 2 in detail, fig. 1 is a schematic flowchart of an embodiment of an algorithm module scheduling method provided in the present application, and fig. 2 is a detailed flowchart of the algorithm module scheduling method shown in fig. 1.
The algorithm module scheduling method is applied to an algorithm module scheduling device, wherein the algorithm module scheduling device can be a server or a system formed by the cooperation of the server and terminal equipment. Correspondingly, each part, for example, each unit, sub-unit, module, and sub-module, included in the algorithm module scheduling apparatus may be all disposed in the server, or may be disposed in the server and the terminal device, respectively.
Further, the server may be hardware or software. When the server is hardware, it may be implemented as a distributed server cluster formed by multiple servers, or may be implemented as a single server. When the server is software, it may be implemented as a plurality of software or software modules, for example, software or software modules for providing distributed servers, or as a single software or software module, and is not limited herein. In some possible implementations, the algorithm module scheduling method of the embodiments of the present application may be implemented by a processor calling a computer readable instruction stored in a memory.
Specifically, as shown in fig. 1, the algorithm module scheduling method in the embodiment of the present application specifically includes the following steps:
step S11: and acquiring a configuration file, wherein the configuration file comprises a plurality of algorithm modules with sequential dependency relationship of front and back results.
In the embodiment of the application, in the image processing algorithm scheme operating framework, each algorithm module is taken as a task to be scheduled and executed. The method comprises the steps that different algorithm schemes can correspondingly generate different configuration files, an algorithm module scheduling device marks priorities of all algorithm modules by analyzing the configuration files, the algorithm modules are automatically sequenced according to the marked priorities after being used as tasks and added into a task queue, and the algorithm module tasks with higher priorities are obtained from the queue and executed in preference to other executed threads.
Referring now to fig. 3, a possible configuration file format provided by the present application is described, and fig. 3 is a schematic diagram of an embodiment of a configuration file format provided by the present application.
As shown in fig. 3, the content in the configuration file can be understood as a complete Pipeline of image processing algorithm schemes, represented by Pipeline, i.e. algorithm scheme Pipeline.
The image processing scheme can be composed of different algorithm function modules, the algorithm function modules are represented by algorithm nodes in a configuration file, namely an algorithm scheme production line is composed of different algorithm nodes, namely the algorithm nodes.
The method comprises the steps that a sequential dependency relationship of front and back results exists among algorithm function modules, namely image processing results need to be transmitted and processed among different algorithm function modules according to a sequence, each algorithm node in a configuration file comprises an Input stream and an Output stream, and the sequential dependency relationship among the algorithm function modules is represented by a connecting line of the Input stream of one algorithm node and the Input stream of the next algorithm node, namely an algorithm scheme pipeline.
The algorithm scheme of the configuration file comprises that the whole information of the pipeline comprises an initial input stream and a tail-end output stream of the whole pipeline, wherein the initial input stream is used for inputting the input stream to the first algorithm node, and the tail-end output stream is used for receiving the output stream of the last algorithm node.
Step S12: and configuring the priorities of the algorithm modules by utilizing the sequential dependency relationship of the front and rear results in the configuration file.
In the embodiment of the present application, the algorithm module scheduling device obtains and analyzes the content of the configuration file, and converts the entire algorithm pipeline into a Directed Acyclic Graph (DAG) according to Input stream information and Output stream information configured by each algorithm node in the configuration file. The starting point of the directed acyclic graph is an initial input stream given by the overall information of the algorithm scheme pipeline in the configuration file, and the end point of the directed acyclic graph is a given final output stream.
Specifically, a frame of image data needs to be processed by all algorithm function modules in an algorithm scheme pipeline to obtain a final output result, and the analysis of the frame of image data is completed, so that the whole algorithm scheme pipeline needs to be regarded as a whole. In order to improve the efficiency of the image processing algorithm scheme, it is necessary to ensure that the algorithm node that outputs the final result can obtain enough resources to perform data processing, i.e., the priority of the result processing node is set to be the highest.
Similarly, the algorithm module scheduling device can make sure that the priority of the downstream algorithm node in the whole algorithm scheme pipeline is higher than the priority of the upstream node. Therefore, the algorithm module scheduling device can set the priority of the initial algorithm node to be 0 according to the directed acyclic graph generated by analysis, the subsequent downstream nodes are sequentially subjected to increasing processing according to the sequence priority, and the larger the priority value array is, the higher the priority is.
Step S13: and creating a task queue according to the priorities of the algorithm modules.
In the embodiment of the application, when the algorithm module scheduling device performs task scheduling, each algorithm node is used as a task to be processed, and after the condition preparation required by the algorithm node is completed, the algorithm node task is scheduled to be added into the task queue. After the task queue is added, the algorithm module scheduling device can adjust the queue position of the task according to the sequence of the task entering the queue and the priority of the task.
Referring to fig. 4 and fig. 5, fig. 4 is a schematic flowchart of another embodiment of an algorithm module scheduling method provided in the present application, and fig. 5 is a specific flowchart of the algorithm module scheduling method shown in fig. 4.
Specifically, as shown in fig. 4, step S13 in the algorithm module scheduling method shown in fig. 1 specifically includes the following sub-steps:
step S131: and adding the current algorithm module into the tail part of a task queue, wherein the task queue comprises a plurality of algorithm modules.
In the embodiment of the present application, with reference to the specific flowchart shown in fig. 5, after the preparation of the algorithm node task execution condition is completed, the algorithm module scheduling device starts to schedule the algorithm modules in the task queue.
The algorithm module scheduling device adds the current algorithm module as a new task into the task queue and places the new task at the tail of the task queue.
Step S132: and comparing the priority of the current algorithm module with the priority of the previous algorithm module in the task queue.
In the embodiment of the application, the algorithm module scheduling device compares the priority of the new task with the priority of the previous task in the task queue. Here, the priority is determined by the scheme of step S12, and is not described in detail here.
Step S133: and when the priority of the current algorithm module is lower than that of the previous algorithm module, the position of the current algorithm module in the task queue is not adjusted.
In the embodiment of the application, if the priority of the new task is lower than that of the previous task, the algorithm module scheduling device keeps the positions of the two tasks in the task queue unchanged, and exits from the sorting operation of the task queue.
Step S134: and exchanging the queue positions of the current algorithm module and the previous algorithm module in the task queue when the priority of the current algorithm module is higher than that of the previous algorithm module, and updating the task queue.
In this embodiment, if the priority of the new task is higher than the priority of the previous task, the algorithm module scheduling device continues to perform step S135 after interchanging the positions of the two tasks in the task queue.
Step S135: and continuously comparing the priority of the current algorithm module with the priority of the previous algorithm module in the updated task queue until the priority of the current algorithm module in the updated task queue is lower than the priority of the previous algorithm module or the current algorithm module is positioned at the head of the updated task queue.
In the embodiment of the application, the algorithm module scheduling device completes the addition of the current algorithm module into the task queue and after the sequencing operation is completed, the algorithm module scheduling device releases the resource lock of the task queue, so that the insertion sequencing of the tasks can be normally performed during the next scheduling.
In other embodiments, the algorithm module scheduling device may also adopt another way of adding a new task into the task queue, which is specifically as follows:
the algorithm module scheduling device acquires the priority of the current algorithm module and the priorities of all queue algorithm modules in the task queue, and then compares the priority of the current algorithm module with the priorities of all queue algorithm modules.
And when the priority of the current algorithm module is higher than the priorities of all queue algorithm modules, adding the current algorithm module into the head of the task queue by the algorithm module scheduling device, and updating the task queue.
And when the priority of the current algorithm module is lower than the priority of one or more queue algorithm modules, the current algorithm module scheduling device adds the current algorithm module to the task queue at the next bit of the queue algorithm module with the lowest priority in the one or more queue algorithm modules. For example, the priority of the current algorithm module is 0.90, the priorities of a plurality of queue algorithm modules existing in the task queue are higher than the priority of the current algorithm module, and the specific priorities are 0.95, 0.98 and 0.92 respectively, at this time, the current algorithm module of the algorithm module scheduling device is added into the task queue, and the current algorithm module is placed at the next position of the queue algorithm module corresponding to the priority of 0.92.
Step S14: and processing data by a scheduling algorithm module based on the front-back relation of the queue positions in the task queue.
In the embodiment of the application, an algorithm module scheduling device acquires a configuration file, wherein the configuration file comprises a plurality of algorithm modules with a sequential dependency relationship between a front result and a rear result; configuring the priorities of the algorithm modules by utilizing the sequential dependency relationship of the front and rear results in the configuration file; creating a task queue according to the priorities of the algorithm modules; and processing data by a scheduling algorithm module based on the front-back relation of the queue positions in the task queue. By the method, the algorithm module scheduling method realizes self-adaptive task priority marking and queue sequencing, improves the overall processing efficiency of the algorithm scheme and prevents the algorithm scheme from being stuck.
Referring to fig. 6 and fig. 7, fig. 6 is a schematic flowchart of another embodiment of an algorithm module scheduling method provided in the present application, and fig. 7 is a specific flowchart of the algorithm module scheduling method shown in fig. 6.
The algorithm module scheduling method can automatically acquire the equipment information of the program running equipment, and can self-adaptively select a proper thread pool strategy to create and schedule by integrating the conditions of the number of the CPU cores and the complexity of the running algorithm scheme in the equipment information.
Specifically, as shown in fig. 6, the algorithm module scheduling method in the embodiment of the present application specifically includes the following steps:
step S21: acquiring device information, wherein the device information comprises a processor core number.
In this embodiment of the present application, the algorithm module scheduling device obtains device information of the program running device, where the device information may include a CPU core number, a GPU core number, and the like. In addition, the algorithm module scheduling device can also obtain the number of algorithm nodes in the configuration file and the like.
Step S22: and judging whether the number of the processor cores in the equipment information is larger than a first preset threshold value.
In this embodiment, the algorithm module scheduling device may set the first preset threshold to be 32, or other specific values, for evaluating the processing resources of the program running device. When the processor core number of the program execution device is larger than 32, the flow proceeds to step S23; when the number of processor cores of the program execution device is equal to or less than 32, the process proceeds to step S24.
Step S23: and creating a corresponding number of thread pools based on the number of the processor cores, and executing the tasks in the task queue through the execution threads in the corresponding number of thread pools.
In the embodiment of the application, when the number of processor cores of the program running device is greater than a preset threshold value, the algorithm module scheduling device executes the multithreading pool strategy.
Specifically, in the initialization stage in the operation process of the whole algorithm scheme, thread pools with corresponding number are created according to the number of the CPU cores of the program operation equipment, and the one-to-one correspondence relationship between each thread pool and each CPU core is set.
The algorithm module scheduling device creates a plurality of execution threads in each thread pool, the execution threads are set with the affinity with the CPU core corresponding to the thread pool, each execution thread can be ensured to monopolize one CPU core resource, and resource consumption caused by thread switching is avoided.
For example, a work stealing algorithm is adopted in the thread scheduling policy, that is, each execution thread has a corresponding thread execution queue, in the actual running process, the task priority queue can equally distribute all tasks in the queue to the thread execution queue corresponding to each execution thread, and after the execution thread completes the tasks in the queue corresponding to the execution thread, another execution thread can randomly steal the tasks until the tasks are completed.
It should be noted that, when the execution thread randomly goes to another execution thread stealing task, the execution thread is not limited by the thread pool.
When the algorithm scheme is operated on program operation equipment with a large number of CPU cores, namely program operation equipment with the number of CPU cores larger than 32 in the obtained equipment information is mainly suitable for server equipment, and the number of algorithm nodes in the pipeline of the algorithm scheme is large, for example, the number of the algorithm nodes is larger than 32, the algorithm module scheduling device selects the multithreading pool strategy to establish and schedule the thread pool. Under the condition, the multithreading pool strategy can maximally utilize hardware resources of the equipment and accelerate the analysis processing efficiency of the algorithm scheme.
Step S24: and creating a plurality of execution threads, putting the execution threads into one thread pool, and executing the tasks in the task queue through the execution threads in the thread pool.
In the embodiment of the application, when the number of the processor cores of the program running equipment is less than or equal to the preset threshold value, the algorithm module scheduling device executes the single thread pool strategy.
Specifically, in the initialization stage during the operation of the whole algorithm scheme, a plurality of execution threads are created at one time and put into a thread pool, and when a task comes, one execution thread is waken up from the thread pool for the execution processing of the task. And when the execution thread completes the current task, the priority task queue is inquired, if any task exists, the execution is continued after the task is acquired, and the task does not enter the dormancy. Therefore, the processes of creating, scheduling execution, destroying and the like of each thread are managed in a unified mode, the system time is saved, and the overall stability of the program is improved.
When the algorithm scheme is operated in the program operation equipment with less CPU core number, namely the obtained equipment information is in the program operation equipment with less CPU core number than 32, the algorithm module scheduling device is mainly suitable for embedded equipment, and the single thread pool strategy is selected by the algorithm module scheduling device to establish and schedule the thread pool. Under the condition, the single thread pool strategy uses equipment resources as much as possible to meet the processing requirement of the algorithm scheme under the condition that the equipment condition allows, and the requirement that the scheme processing cannot be met due to the fact that the number of executed threads is small under the multi-thread pool strategy.
In other embodiments, as shown in fig. 7, the algorithm module scheduling device may further consider the number of algorithm nodes in the configuration file as a reference factor for selecting the single-thread pool policy or the multi-thread pool policy.
Specifically, the algorithm module scheduling device determines whether the number of processor cores in the device information is greater than a first preset threshold, and whether an algorithm node in the configuration file is greater than a second preset threshold. For example, the algorithm module scheduling device determines whether the number of CPU cores of the program running device is greater than 32 and whether the algorithm node in the configuration file is greater than 32.
And if the number of CPU cores of the program running equipment is more than 32 and the number of algorithm nodes in the configuration file is more than 32, the algorithm module scheduling device executes the multithreading strategy. And if the number of CPU cores of the program running equipment is less than or equal to 32 and/or the number of algorithm nodes in the configuration file is less than or equal to 32, the algorithm module scheduling device executes the single-thread strategy.
In the embodiment of the application, the algorithm module scheduling device combines the adaptive priority task queue with the adaptive thread pool creation scheduling, so that unnecessary thread switching and destruction are reduced when the image processing algorithm scheme runs on equipment, and the overall execution efficiency of the algorithm scheme can be effectively improved. In the aspect of resource utilization of equipment, hardware resources of the equipment are greatly utilized to accelerate analysis processing of an image processing algorithm, and the overall utilization rate of the equipment resources is improved.
It will be understood by those skilled in the art that in the method of the present invention, the order of writing the steps does not imply a strict order of execution and any limitations on the implementation, and the specific order of execution of the steps should be determined by their function and possible inherent logic.
To implement the algorithm module scheduling method of the foregoing embodiment, the present application further provides an algorithm module scheduling apparatus, and please refer to fig. 8 specifically, where fig. 8 is a schematic structural diagram of an embodiment of the algorithm module scheduling apparatus provided in the present application.
The algorithm module scheduling apparatus 300 of the embodiment of the present application includes an obtaining module 31, a configuring module 32, a creating module 33, and a scheduling module 34.
The obtaining module 31 is configured to obtain a configuration file, where the configuration file includes a plurality of algorithm modules having a sequential dependency relationship between previous and next results.
The configuration module 32 is configured to configure the priorities of the algorithm modules by using the dependency relationship between the sequence of the previous and next results in the configuration file.
The creating module 33 is configured to create a task queue according to the priorities of the algorithm modules.
The scheduling module 34 is configured to schedule the algorithm module to process data based on the front-back relationship of the queue positions in the task queue.
To implement the algorithm module scheduling method of the foregoing embodiment, the present application further provides another algorithm module scheduling apparatus, and please refer to fig. 9 specifically, where fig. 9 is a schematic structural diagram of another embodiment of the algorithm module scheduling apparatus provided in the present application.
The algorithm module scheduling apparatus 400 of the embodiment of the present application includes a memory 41 and a processor 42, wherein the memory 41 and the processor 42 are coupled.
The memory 41 is used for storing program data and the processor 42 is used for executing the program data to implement the algorithm module scheduling method described in the above embodiments.
In the present embodiment, the processor 42 may also be referred to as a CPU (Central Processing Unit). The processor 42 may be an integrated circuit chip having signal processing capabilities. The processor 42 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 42 may be any conventional processor or the like.
To implement the algorithm module scheduling method of the above embodiment, the present application further provides a computer-readable storage medium, as shown in fig. 10, the computer-readable storage medium 500 is used for storing program data 51, and when being executed by a processor, the program data 51 is used for implementing the algorithm module scheduling method of the above embodiment.
The present application also provides a computer program product, wherein the computer program product comprises a computer program operable to cause a computer to execute the algorithm module scheduling method according to the embodiment of the present application. The computer program product may be a software installation package.
The algorithm module scheduling method according to the above embodiment of the present application may be stored in a device, for example, a computer readable storage medium, when the algorithm module scheduling method is implemented in the form of a software functional unit and sold or used as an independent product. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the purpose of illustrating embodiments of the present application and is not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application or are directly or indirectly applied to other related technical fields, are also included in the scope of the present application.
Claims (13)
1. An algorithm module scheduling method, characterized in that the algorithm module scheduling method comprises:
acquiring a configuration file, wherein the configuration file comprises a plurality of algorithm modules with sequential dependency relationship of front and back results;
configuring the priorities of the algorithm modules by utilizing the sequential dependency relationship of the front and rear results in the configuration file;
creating a task queue according to the priorities of the algorithm modules;
and processing data by a scheduling algorithm module based on the front-back relation of the queue positions in the task queue.
2. The algorithmic module scheduling method of claim 1,
the configuring the priorities of the algorithm modules by using the sequential dependency relationship of the front and rear results in the configuration file comprises:
generating a data flow graph of the plurality of algorithm modules by utilizing the sequential dependency relationship of the front and back results in the configuration file;
and configuring the priorities of a plurality of algorithm modules in the data flow diagram from small to large according to the input and output directions of the data flow diagram.
3. The algorithmic module scheduling method of claim 2,
the creating of the task queue according to the priorities of the algorithm modules comprises the following steps:
adding a current algorithm module into the tail part of a task queue, wherein the task queue comprises a plurality of algorithm modules;
comparing the priority of the current algorithm module with the priority of the previous algorithm module in the task queue;
and when the priority of the current algorithm module is lower than that of the previous algorithm module, the position of the current algorithm module in the task queue is not adjusted.
4. The algorithmic module scheduling method of claim 3,
after comparing the priority of the current algorithm module with the priority of the previous algorithm module in the task queue, the algorithm module scheduling method further comprises:
when the priority of the current algorithm module is higher than that of the previous algorithm module, exchanging the queue positions of the current algorithm module and the previous algorithm module in the task queue, and updating the task queue;
and continuously comparing the priority of the current algorithm module with the priority of the previous algorithm module in the updated task queue until the priority of the current algorithm module in the updated task queue is lower than the priority of the previous algorithm module, or the current algorithm module is positioned at the head of the updated task queue.
5. The algorithmic module scheduling method of claim 2,
the creating of the task queue according to the priorities of the algorithm modules comprises the following steps:
acquiring the priority of the current algorithm module and the priorities of all queue algorithm modules in a task queue;
comparing the priority of the current algorithm module with the priorities of all queue algorithm modules;
when the priority of the current algorithm module is higher than the priorities of all queue algorithm modules, adding the current algorithm module into the head of the task queue, and updating the task queue;
and when the priority of the current algorithm module is lower than the priority of one or more queue algorithm modules, adding the current algorithm module to the task queue at the next bit of the queue algorithm module with the lowest priority in the one or more queue algorithm modules.
6. The algorithmic module scheduling method of claim 1,
the data processing based on the queue position front-back relation scheduling algorithm module in the task queue comprises the following steps:
acquiring a resource lock of the task queue, and starting to schedule an algorithm module in the task queue to process data;
acquiring a new algorithm module, and adding the new algorithm module into the task queue according to the priority;
and releasing the resource lock of the task queue after the task queue is updated.
7. The algorithmic module scheduling method of claim 1,
the data processing based on the queue position front-back relation scheduling algorithm module in the task queue comprises the following steps:
acquiring equipment information, wherein the equipment information comprises a processor core number;
judging whether the number of processor cores in the equipment information is larger than a first preset threshold value or not;
if yes, creating a corresponding number of thread pools based on the processor cores, and executing the tasks in the task queue through executing threads in the corresponding number of thread pools;
and if not, creating a plurality of execution threads, putting the execution threads into one thread pool, and executing the tasks in the task queue through the execution threads in the thread pool.
8. The algorithmic module scheduling method of claim 7,
the creating a corresponding number of thread pools based on the processor cores comprises:
setting a one-to-one corresponding relation between the thread pool and the processor;
and setting a plurality of execution threads in each thread pool, and setting the affinity of each execution thread and the processor corresponding to the thread pool.
9. The algorithmic module scheduling method of claim 7,
after the device information is obtained, the algorithm module scheduling method further includes:
judging whether the number of processor cores in the equipment information is greater than a first preset threshold value or not, and whether an algorithm module node in the configuration file is greater than a second preset threshold value or not;
if yes, creating a corresponding number of thread pools based on the processor cores, and executing the tasks in the task queue through executing threads in the corresponding number of thread pools;
and if not, creating a plurality of execution threads, putting the execution threads into one thread pool, and executing the tasks in the task queue through the execution threads in the thread pool.
10. The algorithmic module scheduling method of claim 1,
the algorithm module scheduling method further comprises the following steps:
analyzing the configuration file to obtain a plurality of algorithm nodes in the configuration file, wherein each algorithm node corresponds to at least one algorithm module;
obtaining a node input stream and a node output stream of each algorithm node;
determining the pipeline sequence of the algorithm nodes according to the node input streams and the node output streams of the algorithm nodes;
and determining the sequential dependency relationship of the front and rear results of the corresponding algorithm modules by using the pipeline sequence of the algorithm nodes.
11. An algorithm module scheduling device is characterized by comprising an acquisition module, a configuration module, a creation module and a scheduling module; wherein the content of the first and second substances,
the acquisition module is used for acquiring a configuration file, wherein the configuration file comprises a plurality of algorithm modules with sequential dependency relationship of front and back results;
the configuration module is used for configuring the priorities of the algorithm modules by utilizing the sequential dependency relationship of the front and rear results in the configuration file;
the creating module is used for creating a task queue according to the priorities of the algorithm modules;
and the scheduling module is used for processing data based on the queue position front-back relation scheduling algorithm module in the task queue.
12. An algorithmic module scheduling means comprising a processor and a memory, the memory having stored therein program data, the processor being adapted to execute the program data to perform the algorithmic module scheduling method of any of claims 1 to 10.
13. A computer-readable storage medium for storing program data which, when executed by a processor, is adapted to implement the algorithm module scheduling method of any of claims 1-10.
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