On-Device CPU Scheduling for Sense-React Systems
On-Device CPU Scheduling for Sense-React Systems
复制标题
Sense-React 系统的设备内 CPU 调度
DOI：
10.48550/arxiv.2207.13280
复制
发表时间：
2022
期刊：
影响因子：
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通讯作者：
R. Mittal
中科院分区：
文献类型：
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作者：
Aditi Partap;Samuel Grayson;Muhammad Huzaifa;S. Adve;Brighten Godfrey;Saurabh Gupta;Kris K. Hauser;R. Mittal
感知-反应系统（例如机器人和AR/VR）必须采取高度响应的实时行动，由涉及感知、感知、规划和反应任务的复杂决策驱动。这些任务必须在资源受限的设备上进行调度，以便满足应用程序的性能目标和要求。这是一个困难的调度问题，需要处理多个调度维度，以及资源使用和可用性的变化。在实践中，系统设计人员手动调整其特定硬件和应用程序的参数，这导致泛化能力差，增加了开发负担。在这项工作中，我们强调了新出现的需要调度CPU资源在运行时的感知-反应系统。我们研究了三个典型的应用程序（人脸跟踪，机器人导航和VR），首先了解这些系统的关键调度要求。有了这样的理解，我们开发了一个调度框架，卡坦，动态调度跨应用程序的不同组件的计算资源，以满足指定的应用程序的要求。通过在广泛使用的机器人框架（ROS）和开源AR/VR平台上实现的原型实验，我们展示了系统调度对满足三个应用程序的性能目标的影响，Catan如何能够实现比手动调整配置更好的应用程序性能，以及它如何动态适应运行时的变化。
Sense-react systems (e.g. robotics and AR/VR) have to take highly responsive real-time actions, driven by complex decisions involving a pipeline of sensing, perception, planning, and reaction tasks. These tasks must be scheduled on resource-constrained devices such that the performance goals and the requirements of the application are met. This is a difficult scheduling problem that requires handling multiple scheduling dimensions, and variations in resource usage and availability. In practice, system designers manually tune parameters for their specific hardware and application, which results in poor generalization and increases the development burden. In this work, we highlight the emerging need for scheduling CPU resources at runtime in sense-react systems. We study three canonical applications (face tracking, robot navigation, and VR) to first understand the key scheduling requirements for such systems. Armed with this understanding, we develop a scheduling framework, Catan, that dynamically schedules compute resources across different components of an app so as to meet the specified application requirements. Through experiments with a prototype implemented on a widely-used robotics framework (ROS) and an open-source AR/VR platform, we show the impact of system scheduling on meeting the performance goals for the three applications, how Catan is able to achieve better application performance than hand-tuned configurations, and how it dynamically adapts to runtime variations.
PiCAS：ROS2 优先级驱动链感知调度的新设计
DOI：
10.1109/rtas52030.2021.00028
发表时间：
2021
期刊：
2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium (RTAS
影响因子：
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作者：
Choi, Hyunjong;Xiang, Yecheng;Kim, Hyoseung
通讯作者：
Kim, Hyoseung
DOI：
10.1109/icra.2019.8793690
发表时间：
2019-03
期刊：
2019 International Conference on Robotics and Automation (ICRA)
影响因子：
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作者：
A. Tanwani;Nitesh Mor;J. Kubiatowicz;Joseph E. Gonzalez;Ken Goldberg
通讯作者：
A. Tanwani;Nitesh Mor;J. Kubiatowicz;Joseph E. Gonzalez;Ken Goldberg
DOI：
10.1109/rtss.2018.00018
发表时间：
2018-12
期刊：
2018 IEEE Real-Time Systems Symposium (RTSS)
影响因子：
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作者：
Ming Yang;Tanya Amert;Kecheng Yang;Nathan Otterness;James H. Anderson;F. D. Smith;Shige Wang
通讯作者：
Ming Yang;Tanya Amert;Kecheng Yang;Nathan Otterness;James H. Anderson;F. D. Smith;Shige Wang