Scheduling Tasks with Mixed Timing Constraints in GPU-Powered Real-Time Systems
Scheduling Tasks with Mixed Timing Constraints in GPU-Powered Real-Time Systems
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DOI：
10.1145/2925426.2926265
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发表时间：
2016-06
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影响因子：
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通讯作者：
Yunlong Xu;Rui Wang;Tao Li;Mingcong Song;Lan Gao;Zhongzhi Luan;D. Qian
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文献类型：
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作者：
Yunlong Xu;Rui Wang;Tao Li;Mingcong Song;Lan Gao;Zhongzhi Luan;D. Qian
由于图形处理单元（GPU）的成本效益高、计算能力大，在实时系统中利用GPU的兴趣越来越大。例如，GPU已被应用于汽车系统，以实现新的先进和智能驾驶辅助技术，加速自动驾驶汽车的道路。在这样的系统中，GPU在具有混合时间约束的任务之间共享：必须在指定截止日期之前完成的实时（RT）任务，以及非实时、尽力而为（BE）任务。在本文中，（1）我们提出了资源感知的非均匀松弛分布，以提高在GPU支持的系统中的RT任务的可调度性（RT任务的总工作量，其截止日期可以在给定的资源量上得到满足）;（2）我们提出了截止日期感知的动态GPU分区，以允许RT和BE任务同时在GPU上运行，使得BE任务不会长时间阻塞。我们通过使用合成基准和由一组新兴汽车任务组成的现实世界工作负载来评估所提出方法的有效性。实验结果表明，所提出的方法产生了显着的可扩展性改善RT任务和周转时间减少BE任务。此外，两个驾驶场景的分析表明，这种可扩展性的改善和周转时间的减少可以显着提高驾驶安全性和体验。例如，当使用资源感知的非均匀松弛分布方法时，汽车在交通标志与交通标志之间的时间期间行驶的距离可以是（行人）被“看到和识别”的距离从44.4米减少到22.2米（从4.4米到2.2米）;当使用期限感知的动态GPU分区方法时，汽车在昏昏欲睡的驾驶员被唤醒之前已经行驶的距离从56.2m减少到29.2m。
Due to the cost-effective, massive computational power of graphics processing units (GPUs), there is a growing interest of utilizing GPUs in real-time systems. For example GPUs have been applied to automotive systems to enable new advanced and intelligent driver assistance technologies, accelerating the path to self-driving cars. In such systems, GPUs are shared among tasks with mixed timing constraints: real-time (RT) tasks that have to be accomplished before specified deadlines, and non-real-time, best-effort (BE) tasks. In this paper, (1) we propose resource-aware non-uniform slack distribution to enhance the schedulability of RT tasks (the total amount of work of RT tasks whose deadlines can be satisfied on a given amount of resources) in GPU-enabled systems; (2) we propose deadline-aware dynamic GPU partitioning to allow RT and BE tasks to run on a GPU simultaneously, such that BE tasks are not blocked for a long time. We evaluate the effectiveness of the proposed approaches by using both synthetic benchmarks and a real-world workload that consists of a set of emerging automotive tasks. Experimental results show that the proposed approaches yield significant schedulability improvement for RT tasks and turnaround time decrement for BE tasks. Moreover, the analysis of two driving scenarios shows that such schedulability improvement and turnaround time decrement can significantly enhance the driving safety and experience. For example, when the resource-aware non-uniform slack distribution approach is used, the distance that a car travels during the time between a traffic sign (pedestrian) is "seen and recognized" is decreased from 44.4m to 22.2m (from 4.4m to 2.2m); when the deadline-aware dynamic GPU partitioning approach is used, the distance that the car has traveled before a drowsy driver is woken up is reduced from 56.2m to 29.2m.