2022 IEEE Real-Time Systems Symposium (RTSS)最新文献_第5页

Enabling GPU Memory Oversubscription via Transparent Paging to an NVMe SSD 通过透明分页向NVMe SSD启用GPU内存超额订阅

2022 IEEE Real-Time Systems Symposium (RTSS) Pub Date : 2022-12-01 DOI: 10.1109/RTSS55097.2022.00039

Joshua Bakita, James H. Anderson

引用次数: 0

On Batching Task Scheduling 批处理任务调度

2022 IEEE Real-Time Systems Symposium (RTSS) Pub Date : 2022-12-01 DOI: 10.1109/RTSS55097.2022.00017

Hehuan Shi, Lin Chen

引用次数: 0

Job Scheduling with Battery Recharging Constraints: Applications to UAV Flight Planning 具有电池充电约束的作业调度:在无人机飞行规划中的应用

2022 IEEE Real-Time Systems Symposium (RTSS) Pub Date : 2022-12-01 DOI: 10.1109/RTSS55097.2022.00043

S. Gopalakrishnan, N. Nasiri, Jared Paul

{"title":"Job Scheduling with Battery Recharging Constraints: Applications to UAV Flight Planning","authors":"S. Gopalakrishnan, N. Nasiri, Jared Paul","doi":"10.1109/RTSS55097.2022.00043","DOIUrl":"https://doi.org/10.1109/RTSS55097.2022.00043","url":null,"abstract":"The need to understand job scheduling on devices with intermittent availability is of significant interest today because of the use of battery-powered devices - including electric vehicles - that rely on recharging intervals or energy harvesting. In some recent work by Islam and Nirjon, effective heuristics were proposed for scheduling recurring tasks with deadlines on such intermittently available devices. The broader computational complexity of job scheduling has not been explored in this setting where there is a relationship between job durations and energy consumption. We provide a richer understanding of this problem space. We consider two recharging approaches, one where the battery has to be fully charged during a recharging interval (sometimes considered better for extending battery lifetime) and another where the battery can be partially charged, and we study different scheduling objectives: minimizing the sum of completion times, minimizing the maximum tardiness, and minimizing the number of tardy jobs. We also consider four different relationships between job duration and energy consumption: (i) energy consumption is equal for all jobs irrespective of job length; (ii) job length is equal for all jobs irrespective of energy consumption; (iii) energy consumption is directly proportional to job length; and (iv) there is an arbitrary relationship between job length and energy consumption. In effect, we consider 24 different scheduling problems, and establish that most problems subject to a complete recharging requirement are NP-Hard but that most problems can be solved in polynomial time when partial recharging is permitted. Interestingly, we have been unable to resolve the computational complexity for the one case of minimizing the sum of completion times subject to partial recharging.","PeriodicalId":202402,"journal":{"name":"2022 IEEE Real-Time Systems Symposium (RTSS)","volume":"308 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115936500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-Time Scheduling and Analysis of Processing Chains on Multi-threaded Executor in ROS 2 ROS中多线程执行器处理链的实时调度与分析[j]

2022 IEEE Real-Time Systems Symposium (RTSS) Pub Date : 2022-12-01 DOI: 10.1109/RTSS55097.2022.00013

Xu Jiang, Dong Ji, Nan Guan, Ruoxiang Li, Yue Tang, Wang Yi

引用次数: 6

Towards Energy-Efficient Real-Time Scheduling of Heterogeneous Multi-GPU Systems 异构多gpu系统的节能实时调度研究

2022 IEEE Real-Time Systems Symposium (RTSS) Pub Date : 2022-12-01 DOI: 10.1109/RTSS55097.2022.00042

Yidi Wang, Mohsen Karimi, Hyoseung Kim

{"title":"Towards Energy-Efficient Real-Time Scheduling of Heterogeneous Multi-GPU Systems","authors":"Yidi Wang, Mohsen Karimi, Hyoseung Kim","doi":"10.1109/RTSS55097.2022.00042","DOIUrl":"https://doi.org/10.1109/RTSS55097.2022.00042","url":null,"abstract":"With the increasing demand for computational power, research on general-purpose graphics processing units (GPUs) has been active for various real-time systems spanning from autonomous vehicles to real-time clouds. While the use of GPUs can significantly benefit compute-intensive tasks with timing constraints, their high power consumption becomes an important problem given that it is not rare to see multiple GPUs in today's systems. In this paper, we present our study towards energy-efficient real-time scheduling in heterogeneous multi-GPU systems. We first make observations using a custom power monitoring setup that, in a multi-GPU system, conventional task allocation approaches for multiprocessors do not lead to energy efficiency and there is no clear winner. Then we propose a multi-GPU real-time scheduling framework, sBEET-mg, that builds upon prior work on single-GPU systems and makes offline and runtime scheduling decisions to execute a given job on the energy-optimal GPU while exploiting spatial multitasking on each GPU for better concurrency and real-time performance. We implemented the proposed framework on a real multi-GPU system and evaluated it with randomly-generated task sets of benchmark programs. We also experimentally simulated our method in a system containing more GPUs. Experimental results show that sBEET-mg reduces deadline misses by up to 23% and 18% compared to the conventional load distribution and load concentration methods, respectively, while simultaneously achieving lower energy consumption than them.","PeriodicalId":202402,"journal":{"name":"2022 IEEE Real-Time Systems Symposium (RTSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131168349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Bounding the Response Time of DAG Tasks Using Long Paths 设置长路径DAG任务的响应时间

2022 IEEE Real-Time Systems Symposium (RTSS) Pub Date : 2022-11-16 DOI: 10.1109/RTSS55097.2022.00047

Qingqiang He, Nan Guan, Mingsong Lv, Xu Jiang, Wanli Chang

引用次数: 6

RT-MOT: Confidence-Aware Real-Time Scheduling Framework for Multi-Object Tracking Tasks RT-MOT:多目标跟踪任务的信任感知实时调度框架

2022 IEEE Real-Time Systems Symposium (RTSS) Pub Date : 2022-10-19 DOI: 10.1109/RTSS55097.2022.00035

D. Kang, Seunghoon Lee, H. Chwa, Seung-Hwan Bae, Chang Mook Kang, Jinkyu Lee, Hyeongboo Baek

{"title":"RT-MOT: Confidence-Aware Real-Time Scheduling Framework for Multi-Object Tracking Tasks","authors":"D. Kang, Seunghoon Lee, H. Chwa, Seung-Hwan Bae, Chang Mook Kang, Jinkyu Lee, Hyeongboo Baek","doi":"10.1109/RTSS55097.2022.00035","DOIUrl":"https://doi.org/10.1109/RTSS55097.2022.00035","url":null,"abstract":"Different from existing MOT (Multi-Object Tracking) techniques that usually aim at improving tracking accuracy and average FPS, real-time systems such as autonomous vehicles necessitate new requirements of MOT under limited computing resources: (R1) guarantee of timely execution and (R2) high tracking accuracy. In this paper, we propose RT-MOT, a novel system design for multiple MOT tasks, which addresses R1 and R2. Focusing on multiple choices of a workload pair of detection and association, which are two main components of the tracking-by-detection approach for MOT, we tailor a measure of object confidence for RT-MOT and develop how to estimate the measure for the next frame of each MOT task. By utilizing the estimation, we make it possible to predict tracking accuracy variation according to different workload pairs to be applied to the next frame of an MOT task. Next, we develop a novel confidence-aware real-time scheduling framework, which offers an offline timing guarantee for a set of MOT tasks based on non-preemptive fixed-priority scheduling with the smallest workload pair. At run-time, the framework checks the feasibility of a priority-inversion associated with a larger workload pair, which does not compromise the timing guarantee of every task, and then chooses a feasible scenario that yields the largest tracking accuracy improvement based on the proposed prediction. Our experiment results demonstrate that RT-MOT significantly improves overall tracking accuracy by up to 1.5 ×, compared to existing popular tracking-by-detection approaches, while guaranteeing timely execution of all MOT tasks.","PeriodicalId":202402,"journal":{"name":"2022 IEEE Real-Time Systems Symposium (RTSS)","volume":"6 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120847679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Demand Layering for Real-Time DNN Inference with Minimized Memory Usage 基于最小内存使用的实时DNN推理的需求分层

2022 IEEE Real-Time Systems Symposium (RTSS) Pub Date : 2022-10-08 DOI: 10.1109/RTSS55097.2022.00033

Min-Zhi Ji, Saehanseul Yi, Chang-Mo Koo, Sol Ahn, Dongjoo Seo, N. Dutt, Jong-Chan Kim

{"title":"Demand Layering for Real-Time DNN Inference with Minimized Memory Usage","authors":"Min-Zhi Ji, Saehanseul Yi, Chang-Mo Koo, Sol Ahn, Dongjoo Seo, N. Dutt, Jong-Chan Kim","doi":"10.1109/RTSS55097.2022.00033","DOIUrl":"https://doi.org/10.1109/RTSS55097.2022.00033","url":null,"abstract":"When executing a deep neural network (DNN), its model parameters are loaded into GPU memory before execution, incurring a significant GPU memory burden. There are studies that reduce GPU memory usage by exploiting CPU memory as a swap device. However, this approach is not applicable in most embedded systems with integrated GPUs where CPU and GPU share a common memory. In this regard, we present Demand Layering, which employs a fast solid-state drive (SSD) as a co-running partner of a GPU and exploits the layer-by-layer execution of DNNs. In our approach, a DNN is loaded and executed in a layer-by-layer manner, minimizing the memory usage to the order of a single layer. Also, we developed a pipeline architecture that hides most additional delays caused by the interleaved parameter loadings alongside layer executions. Our implementation shows a 96.5% memory reduction with just 14.8% delay overhead on average for representative DNNs. Furthermore, by exploiting the memory-delay tradeoff, near-zero delay overhead (under 1 ms) can be achieved with a slightly increased memory usage (still an 88.4% reduction), showing the great potential of Demand Layering.","PeriodicalId":202402,"journal":{"name":"2022 IEEE Real-Time Systems Symposium (RTSS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125520135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

EDF-Like Scheduling for Self-Suspending Real-Time Tasks 自挂起实时任务的类edf调度

2022 IEEE Real-Time Systems Symposium (RTSS) Pub Date : 2021-11-18 DOI: 10.1109/RTSS55097.2022.00024

Mario Günzel, Kuan-Hsun Chen, Jian-Jia Chen

{"title":"EDF-Like Scheduling for Self-Suspending Real-Time Tasks","authors":"Mario Günzel, Kuan-Hsun Chen, Jian-Jia Chen","doi":"10.1109/RTSS55097.2022.00024","DOIUrl":"https://doi.org/10.1109/RTSS55097.2022.00024","url":null,"abstract":"In real-time systems, schedulability analyses provide the required timing guarantees. However, current suspension-aware analyses are limited to Task-Level Fixed-Priority (TFP) scheduling or Earliest-Deadline-First (EDF) scheduling of constrained-deadline self-suspending task systems. In this work, we provide a unifying schedulability analysis for uniprocessor Global EDF-Like (GEL) schedulers of arbitrary-deadline task sets. While analyses for EDF-Like schedulers are rare, many widely used scheduling algorithms can be considered as EDF-Like, for example, EDF, First-In-First-Out (FIFO), Earliest-Quasi-Deadline-First (EQDF), and Suspension-Aware EDF (SAEDF). Therefore, the provided analysis is applicable to those algorithms. It can be applied to TFP scheduling as well. Our analysis is the first suspension-aware schedulability analysis for arbitrary-deadline sporadic real-time task systems under Job-Level Fixed-Priority (JFP) scheduling, such as EDF, and the first unifying suspension-aware schedulability analysis framework that covers a wide range of scheduling algorithms. Through numerical simulations, we show that our analysis improves the state of the art for constrained-deadline EDF scenarios.","PeriodicalId":202402,"journal":{"name":"2022 IEEE Real-Time Systems Symposium (RTSS)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122162116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2