Design and Implementation of Multitask Scheduling for Embedded ARM GPU

doi:10.7652/xjtuxb201412014

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Design and Implementation of Multitask Scheduling for Embedded ARM GPU

更新时间：2025-07-09

- Design and Implementation of Multitask Scheduling for Embedded ARM GPU
- Vol. 48, Issue 12, Pages: 87-92(2014)
- 作者机构：
  
  西安交通大学电子与信息工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201412014
  CLC： TP316
- Online First：10 December 2014，
  
  Published：2014
- 稿件说明：
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Design and Implementation of Multitask Scheduling for Embedded ARM GPU[J]. 2014, 48(12): 87-92.
DOI：

Design and Implementation of Multitask Scheduling for Embedded ARM GPU[J]. 2014, 48(12): 87-92. DOI： 10.7652/xjtuxb201412014.

摘要

针对现有GPU任务调度系统在多任务环境下不能保证图形任务响应时间的问题

提出基于分类和多优先级队列(CPMQ)的调度方案

并在ARM的嵌入式GPU上实现验证。该方案中

将GPU的多任务划分为图形任务、通用计算任务和实时图形3类任务并分别建立队列排队

其中图形任务和通用计算任务按照优先级在各自队列中排队

实时图形按照任务截止时间排队。面向多队列的任务调度

优先从实时任务队列中选择任务

并按照加权公平算法分别在图形任务队列和通用计算队列中选择任务。实验结果表明:相比于ARM GPU的原有调度系统

CPMQ在不显著增加通用计算任务的执行时间和调度开销的情况下

将实时图形任务的帧率提升了5%～20%。

Abstract

A scheduling solution of class priority multiple queue(CPMQ)is proposed to solve the problem that the response time to graphic tasks is not ensured by existing task scheduling systems of GPU under multitask conditions

and the schedule is implemented on an embedded system. Multiple tasks on GPU are firstly classified into three classes of tasks

that is

graphic tasks

real-time graphic tasks and general purpose computing tasks. These three classes of tasks then queued respectively with different queuing policy. Graphic tasks and general purpose computing tasks are queued by their priorities

while real-time graphic tasks are queued by their deadlines. When the multi-class tasks are scheduled

real-time graphic tasks are selected at first

and then graphic tasks and general purpose computing tasks are selected out using a weighted fair queuing algorithm. Experimental results and comparisons with the original scheduling system of ARM's GPU show that CPMQ increases the frame rate of reel time graphic tasks by 5%-20% without significant increase in execution time of general purpose computing tasks and scheduling expense.

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references

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