Collaborative Research: CNS Core: Medium: Parallel and Real-Time Multicore Scheduling for an Efficiently-Used Cache (PARSEC)

合作研究：CNS 核心：中：高效使用缓存的并行实时多核调度 (PARSEC)

• 批准号: 2306745
• 负责人: Abusayeed Saifullah
• 金额: $ 27.5万
• 依托单位: Wayne State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2306745&HistoricalAwards=false
• 关键词: Collaborative; Research; CNS; Core; Medium

Safety-critical systems that have strict “real-time” requirements are becoming increasingly ubiquitous and complex. Epitomizing this recent trend toward sophisticated real-time systems are autonomous vehicles, which must perform image recognition, machine learning, routing, and planning tasks, simultaneously and with minimal delay. Furthermore, these real-time computational tasks must execute upon shared hardware (e.g., processors, memory, storage) due to the severe constraints on the size, weight, and power of the entire system; however, the sharing of computer resources creates tremendous contention and competition between tasks. This project addresses a fundamental challenge of how multiple real-time, safety-critical tasks can effectively share the underlying memory architecture and still meet timing constraints. In particular, this project will develop a novel system design and analysis framework called PARSEC (Parallel and Real-Time Multicore Scheduling for an Efficiently-Used Cache). PARSEC contributes to the state-of-the-art with (a) new multicore scheduling algorithms that explicitly manage how contending tasks share memory resources; (b) new formal analysis techniques that verify that a system’s timing constraints are satisfied with existing memory resources; and (c) a set of open-source automated tools that will enable system designers to utilize the framework on commercial off-the-shelf processing architectures. PARSEC will be implemented and evaluated upon the popular RISC V architecture to facilitate wide dissemination to the public.This project will result in safer, more efficient designs of time-sensitive systems, including autonomous vehicles and robotics. Furthermore, the resulting research and system design techniques in this project can be applied to any real-time, safety-critical systems executing concurrent computational tasks upon a shared processor and memory. The reduction in contention in the memory hierarchy obtained from project artifacts will potentially lessen demands on power and fuel in safety-critical systems, decreasing their carbon footprint. The project will benefit the educational missions of University of Nevada Las Vegas and Wayne State University by providing a unique training, education, and experiential learning opportunity for undergraduate and graduate students via course projects related to safety-critical system design. To aid other researchers, this project will also disseminate research results through publications, public talks, tutorials, project websites, and online videos.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

具有严格“实时”要求的安全至关重要系统变得越来越普遍且复杂。体现了朝着复杂的实时系统的最新趋势的攻击是自动驾驶汽车，它必须简单地延迟执行图像识别，机器学习，路由和计划任务。此外，由于对整个系统的尺寸，重量和功率的严重约束，这些实时计算任务必须在共享硬件（例如处理器，内存，存储）时执行；但是，计算机资源的共享产生了巨大的争夺和任务之间的竞争。该项目解决了多个实时，安全至关重要的任务如何有效地共享基本记忆体系结构并仍然达到时正常约束的基本挑战。特别是，该项目将开发一个新型的系统设计和分析框架，称为PARSEC（有效使用的高速缓存的并行和实时多项调度）。 PARSEC通过（a）新的多核算计划算法有助于最新的，这些算法明确管理了争夺任务如何共享内存资源的方式； （b）新的正式分析技术验证系统的正时限制是否对现有内存资源满意； （c）一组开源自动化工具，这些工具将使系统设计人员能够在商业现成的处理体系结构上利用该框架。 PARSEC将在受欢迎的RISC V架构上实施和评估，以促进向公众传播。该项目将导致更安全，更有效的时间敏感系统，包括自动驾驶汽车和机器人技术。此外，该项目中所得的研究和系统设计技术可以应用于在共享处理器和内存上执行并发计算任务的任何实时，安全关键的系统。从项目伪像获得的记忆层次结构中的争论降低可能会降低对安全至关重要系统中对功率和燃料的需求，从而减少其碳足迹。该项目将通过与安全关键系统设计有关的课程项目为本科和研究生提供独特的培训，教育和经验丰富的学习机会，从而使内华达大学拉斯维加斯大学和韦恩州立大学的教育任务受益。为了帮助其他研究人员，该项目还将通过出版物，公开谈判，教程，项目网站和在线视频来传播研究结果。该奖项反映了NSF的法定任务，并通过使用该基金会的知识分子优点和更广泛的影响来评估NSF的法定任务。

项目成果

Precise Scheduling of DAG Tasks with Dynamic Power Management

通过动态电源管理精确调度 DAG 任务

• 发表时间: 2023
• 期刊: Leibniz international proceedings in informatics
• 作者: Bhuiyan, Ashikahmed and

Energy- and Temperature-aware Scheduling: From Theory to an Implementation on Intel Processor

能源和温度感知调度：从理论到英特尔处理器上的实现

• DOI: 10.1109/hpcc-dss-smartcity-dependsys57074.2022.00288
• 发表时间: 2022
• 期刊: ICESS 2022 (the 18th IEEE International Conference on Embedded Software and Systems
• 作者: Bashir, Qaisar;Pivezhandi, Mohammad;Saifullah, Abusayeed
• 通讯作者: Saifullah, Abusayeed