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Iterative static task list scheduling algorithm for multi-processor system

A multi-processor system and scheduling algorithm technology, applied in electrical digital data processing, instrumentation, computing, etc., can solve problems such as poor scheduling results, large scheduling length, and low application execution efficiency, and achieve easy implementation and high flexibility. The effect of simple, static task scheduling algorithm

Active Publication Date: 2016-02-17
HEFEI UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, a static list scheduling algorithm that only considers a task priority sequence is prone to poor scheduling results, that is, a large scheduling length, resulting in low application execution efficiency

Method used

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  • Iterative static task list scheduling algorithm for multi-processor system
  • Iterative static task list scheduling algorithm for multi-processor system
  • Iterative static task list scheduling algorithm for multi-processor system

Examples

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Embodiment Construction

[0027] In this embodiment, on a multiprocessor system with four processors, the execution process of the iterative static task list scheduling algorithm is roughly as follows:

[0028] 1. Set the initial value of the current optimal task priority sequence, and the corresponding static list scheduling length as the initial value of the current optimal scheduling length;

[0029] 2 Generate a new task priority sequence from the current optimal task priority sequence, and if the corresponding static list scheduling length is less than the current optimal scheduling length, update the current optimal scheduling length and the current optimal task priority sequence;

[0030] 3 Repeat step 2 until the number of executions reaches the specified upper limit;

[0031] 4 Execute steps 1 to 3 for each optimal task priority sequence;

[0032] 5 Select the minimum value from all optimal scheduling lengths as the final scheduling result.

[0033] Specifically, if figure 2 shown, yes fi...

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Abstract

The invention discloses an iterative static task list scheduling algorithm for a multi-processor system. The algorithm is characterized by being executed by the following steps: 1, setting an initial value of a current optimal task priority sequence, and taking a corresponding static list scheduling length as an initial value of a current optimal scheduling length; 2, obtaining a new task priority sequence from the current optimal task priority sequence, and if the corresponding static list scheduling length is less than the current optimal scheduling length, updating the current optimal scheduling length and the current optimal task priority sequence; 3, repeatedly executing the step 2 until the frequency of execution reaches a specified upper limit; 4, executing the steps 1 to 3 for each optimal task priority sequence; and 4, selecting a minimum value from all optimal scheduling lengths as a final scheduling result. According to the algorithm, the scheduling length is further reduced on the basis of a conventional static task list scheduling algorithm, so that the application execution efficiency is effectively improved.

Description

technical field [0001] The invention relates to the field of task scheduling, in particular to an iterative static task list scheduling algorithm based on a multiprocessor system. Background technique [0002] In the prior art, multi-processor systems can meet the requirements of applications for concurrent execution of multi-tasks to a greater extent, but how to more effectively implement task scheduling on multi-processor systems still needs to be further explored. At present, the mainstream static task scheduling algorithm mostly adopts the list scheduling technology based on the task graph model. In the task graph model, the application program is represented by a directed acyclic graph G=(V, E, W, C), a point represents a task, and the directed edge E between points a,b Represents the predecessor-successor constraint relationship between the predecessor task a and the successor task b, point weight W a Indicates the time required to execute task a, the directed edge E...

Claims

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Application Information

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IPC IPC(8): G06F9/48
CPCG06F9/4881
Inventor 宋宇鲲杨俊张多利
Owner HEFEI UNIV OF TECH
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