Graphics Processing Units (GPU) are increasingly deployed on Cyber-physical Systems (CPSs), frequently used to perform real-time safety-critical functions, such as object detection on autonomous vehicles. As a result, availability is important for GPU tasks in CPS platforms. However, existing Trusted Execution Environments (TEE) solutions with availability guarantees focus only on CPU computing.To bridge this gap, we propose AvaGPU, a TEE that guarantees real-time availability for CPU tasks involving GPU execution under compromised OS. There are three technical challenges. First, to prevent malicious resource contention due to separate scheduling of CPU and GPU tasks, we proposed a CPU-GPU co-scheduling framework that couples the priority of CPU and GPU tasks. Second, we propose software-based secure preemption on GPU tasks to bound the degree of priority inversion on GPU. Third, we propose a new split design of GPU driver with minimized Trusted Computing Base (TCB) to achieve secure and efficient GPU management for CPS. We implement a prototype of AvaGPU on the Jetson AGX Orin platform. The system is evaluated on benchmark, synthetic tasks, and real-world applications with 15.87% runtime overhead on average.
more »
« less
This content will become publicly available on January 1, 2025
GCAPS: GPU Context-Aware Preemptive Priority-Based Scheduling for Real-Time Tasks
Scheduling real-time tasks that utilize GPUs with analyzable guarantees poses a significant challenge due to the intricate interaction between CPU and GPU resources, as well as the complex GPU hardware and software stack. While much research has been conducted in the real-time research community, several limitations persist, including the absence or limited availability of GPU-level preemption, extended blocking times, and/or the need for extensive modifications to program code. In this paper, we propose GCAPS, a GPU Context-Aware Preemptive Scheduling approach for real-time GPU tasks. Our approach exerts control over GPU context scheduling at the device driver level and enables preemption of GPU execution based on task priorities by simply adding one-line macros to GPU segment boundaries. In addition, we provide a comprehensive response time analysis of GPU-using tasks for both our proposed approach as well as the default Nvidia GPU driver scheduling that follows a work-conserving round-robin policy. Through empirical evaluations and case studies, we demonstrate the effectiveness of the proposed approaches in improving taskset schedulability and response time. The results highlight significant improvements over prior work as well as the default scheduling approach, with up to 40% higher schedulability, while also achieving predictable worst-case behavior on Nvidia Jetson embedded platforms.
more »
« less
- NSF-PAR ID:
- 10527894
- Editor(s):
- Pellizzoni, Rodolfo
- Publisher / Repository:
- Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- Date Published:
- Volume:
- 298
- ISSN:
- 1868-8969
- ISBN:
- 978-3-95977-324-9
- Page Range / eLocation ID:
- 298-298
- Subject(s) / Keyword(s):
- Real-time systems GPU scheduling Computer systems organization → Real-time systems Computer systems organization → Embedded and cyber-physical systems
- Format(s):
- Medium: X Size: 25 pages; 1914695 bytes Other: application/pdf
- Size(s):
- 25 pages 1914695 bytes
- Right(s):
- Creative Commons Attribution 4.0 International license; info:eu-repo/semantics/openAccess
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
The BUNDLE and BUNDLEP scheduling algorithms are cache-cognizant thread-level scheduling algorithms and associated worst case execution time and cache overhead (WCETO) techniques for hard real-time multi-threaded tasks. The BUNDLE-based approaches utilize the inter-thread cache benefit to reduce WCETO values for jobs. Currently, the BUNDLE-based approaches are limited to scheduling a single task. This work aims to expand the applicability of BUNDLE-based scheduling to multiple task multi-threaded task sets. BUNDLE-based scheduling leverages knowledge of potential cache conflicts to selectively preempt one thread in favor of another from the same job. This thread-level preemption is a requirement for the run-time behavior and WCETO calculation to receive the benefit of BUNDLE-based approaches. This work proposes scheduling BUNDLE-based jobs non-preemptively according to the earliest deadline first (EDF) policy. Jobs are forbidden from preempting one another, while threads within a job are allowed to preempt other threads. An accompanying schedulability test is provided, named Threads Per Job (TPJ). TPJ is a novel schedulability test, input is a task set specification which may be transformed (under certain restrictions); dividing threads among tasks in an effort to find a feasible task set. Enhanced by the flexibility to transform task sets and taking advantage of the inter-thread cache benefit, the evaluation shows TPJ scheduling task sets fully preemptive EDF cannot.more » « less
-
null (Ed.)Intermittently-powered devices have gained much interest in recent years. However, scheduling real-time tasks while supporting data consistency, timekeeping, and schedulability guarantees on these devices still remains a challenge. Many sensing tasks need long indivisible sensor reading operations, but most prior work has limited their focus to the forward progress of computation-only tasks. In this paper, we propose a scheduling framework to execute real-time periodic tasks with atomic sensing operations. Our proposed method keeps track of time progress and ensures the periodic execution of sensing tasks while efficiently utilizing intermittent power sources. We provide schedulability analysis to determine if a taskset is schedulable under a given charging condition. As a proof-of-concept, we design a custom programmable RFID tag device, called R’tag, and demonstrate the effectiveness of our framework in a realistic sensing application. Evaluation results show that the proposed method satisfies the real-time task execution requirements on IPDs in terms of task scheduling, timekeeping, and periodic sensing while significantly outperforming prior work.more » « less
-
null (Ed.)In ROS (Robot Operating System), most applications in time- and safety-critical domain are constructed in the form of callback chains with data dependencies. Due to the shortcomings in its real-time support, ROS does not provide a strong timing guarantee and may lead to disastrous results. Although ROS2 claims to enhance the real-time capability, ensuring predictable end-to-end chain latency still remains a challenging problem. In this paper, we propose a new priority-driven chain-aware scheduler for the ROS2 framework and present end-to-end latency analysis for the proposed scheduler. With our scheduler, callbacks are prioritized based on the given timing requirements of the corresponding chains so that the end-to-end latency of critical chains can be improved with a predictable bound. The proposed scheduling design includes priority assignment and resource allocation considering all ROS2 scheduling-related abstractions, e.g., callbacks, nodes, and executors. To the best of our knowledge, this is the first work to address the inherent limitations of ROS2 in end-to-end latency by proposing a new scheduler design. We have implemented our scheduler in ROS2 running on NVIDIA Xavier NX. We have conducted case studies and schedulability experiments. The results show that the proposed scheduler yields a substantial improvement in end-to-end latency over the default ROS2 scheduler and the latest work in real-world scenarios.more » « less
-
Many cyber-physical systems are offloading computation-heavy programs to hardware accelerators (e.g., GPU and TPU) to reduce execution time. These applications will self-suspend between offloading data to the accelerators and obtaining the returned results. Previous efforts have shown that self-suspending tasks can cause scheduling anomalies, but none has examined inter-task communication. This paper aims to explore self-suspending tasks' data chain latency with periodic activation and asynchronous message passing. We first present the cause for suspension-induced delays and worst-case latency analysis. We then propose a rule for utilizing the hardware co-processors to reduce data chain latency and schedulability analysis. Simulation results show that the proposed strategy can improve overall latency while preserving system schedulability.more » « less
