自适应隔离可预测的MPSoC流处理

J. Teich
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引用次数: 0

摘要

资源共享和一个多线程的干扰,甚至更糟糕的是在多处理器单片系统(MPSoC)上并发运行的多个应用程序之间,使得很难为任何定时或吞吐量关键应用程序提供时间限制。额外的干扰来自于操作系统功能的交互,比如线程多路复用和调度,以及目前大量使用的复杂资源(例如缓存)保留协议。最后,芯片上的动态电源和温度管理也可能在任意时间降低处理器速度,从而导致执行时间的额外变化和抖动。对于医疗成像或汽车驾驶辅助系统等许多安全关键应用来说,这可能是无法忍受的。静态解决方案通过为安全关键型应用程序分配不同的资源来提供所需的隔离,但由于成本和缺乏效率和灵活性的原因,这种解决方案可能不可行。此外,关闭或限制温度和电源管理可能是不可容忍的。在本主题演讲中,我们提出了基于侵入式计算范式的MPSoC上资源自适应隔离的新技术,包括处理器,I/O,内存以及按需通信资源。在侵入式计算中,程序员可以指定程序的执行质量界限,甚至可以指定程序的单个片段,后跟一个入侵命令。该系统返回一组称为声明的独占资源,这些资源随后以默认的非共享方式使用,直到入侵者再次释放它们。通过这一原则,可以按需自动隔离应用程序。在侵入式计算中,所有级别的硬件和软件(包括侵入式操作系统)都支持隔离。在今天MPSoC上可用的大量内核的情况下,问题仍然是如何找到合适的声明,以保证在可忽略不计的时间内达到性能界限?对于一类广泛的流应用程序,我们提出了一种基于静态设计空间探索阶段的静态/动态组合方法,以提取一组令人满意的索赔特征,保证程序执行保持在期望的性能范围内。对于一类组合和异构的MPSoC系统,只有很少的信息必须以所谓的ccg(索赔约束图)的形式传递给操作系统进行运行时索赔搜索。在这里,一个特殊的角色是组成片上网络(NoC)架构,它允许独立于其他应用程序侵入处理器、内存和I/O块之间的保证带宽。我们演示了上述概念,用于从机器人视觉中提取的复杂对象检测应用程序算法链,以显示最小化抖动的实现是可能的,即使对于其他并发应用程序的静态未知到达也是如此。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Isolation for Predictable MPSoC Stream Processing
Resource sharing and interferences of multiple threads of one, but even worse between multiple application programs running concurrently on a Multi-Processor System-on-a-Chip (MPSoC) today make it very hard to provide any timing or throughput-critical applications with time bounds. Additional interferences result from the interaction of OS functions such as thread multiplexing and scheduling as well as complex resource (e.g., cache) reservation protocols used heavily today. Finally, dynamic power and temperature management on a chip might also throttle down processor speed at arbitrary times leading to additional variations and jitter in execution time. This may be intolerable for many safety-critical applications such as medical imaging or automotive driver assistance systems. Static solutions to provide the required isolation by allocating distinct resources to safety-critical applications may not be feasible for reasons of cost and due to the lack of efficiency and inflexibility. Also, shutting off or restricting temperature and power management might not be tolerable. In this keynote, we propose new techniques for adaptive isolation of resources including processor, I/O, memory as well as communication resources on demand on an MPSoC based on the paradigm of Invasive Computing. In Invasive Computing, a programmer may specify bounds on the execution quality of a program or even single segments of a program followed by an invade command. This system returns a constellation of exclusive resources called a claim that is subsequently used in a by-default non-shared way until being released again by the invader. Through this principle, it becomes possible to isolate applications automatically and in an on-demand manner. In invasive computing, isolation is supported on all levels of hardware and software including an invasive OS. In case of an abundant number of cores available on an MPSoC today, the problem still becomes how to find suitable claims that will guarantee a performance bound in a negligible amount of time? For a broad class of streaming applications, we propose a combined static/dynamic approach based on a static design space exploration phase to extract a set of satisfying claim characteristics for which program execution is guaranteed to stay within the desired performance bounds. For a class of compositional and heterogeneous MPSoC systems, only very little information must then be passed to the OS for run-time claim search in the form of so-called CCGs (claim constraint graphs). A special role here plays a compositional Network-on-a-Chip (NoC) architecture that allows to invade guaranteed bandwith between processor, memory and I/O tiles independently from other applications. We demonstrate the above concepts for a complex object detection application algorithm chain taken from robot vision to show jitter-minimized implementations become possible, even for statically unknown arrivals of other concurrent applications.
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