CSR: Medium: Performant Architecturally Diverse Systems via Aspect-oriented Programming

CSR：中：通过面向方面的编程实现高性能的架构多样化系统

• 批准号: 1763503
• 负责人: Roger Chamberlain
• 金额: $ 121.47万
• 依托单位: Washington University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1763503&HistoricalAwards=false
• 关键词: CSR; Medium; Performant; Architecturally; Diverse

Architecturally diverse computers are systems that incorporate hardware accelerators such as graphics engines, and reconfigurable logic to achieve some tangible benefits in terms improved performance, and decreased power are difficult to program. This project seeks to dramatically improve the programmability of architecturally diverse computers by enabling them to tune themselves, freeing the application developer to focus on correctness issues rather than performance issues.This will be accomplished by using aspect-oriented programming techniques to expose tuning knobs that have direct impact on the benefit of interest, notably, performance or power consumption. Understanding the impact of these tuning knobs will be achieved using queueing network models which are automatically derived from the application's specification. The queueing models will be used to guide an automated control process that seeks to maximize the benefit of interest by adjusting the tuning knobs.The project will utilize a number of computational science applications as test cases, providing benefits to both of the computational biology and data science communities. Both graduate and undergraduate students will be involved in the research, and several university-level programs will be used to help attract members of underrepresented populations.Relevant data, code, and other supplementary materials will be placed in the university library's permanent repository at https://openscholarship.wustl.edu/data/. This repository will provide persistent, curated access to both code and data, including support for DOIs.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.

架构多样化的计算机是结合了图形引擎等硬件加速器和可重构逻辑的系统，以在提高性能和降低功耗方面实现一些切实的好处，但很难进行编程。该项目旨在通过使不同架构的计算机能够自我调整，从而显着提高其可编程性，使应用程序开发人员能够专注于正确性问题而不是性能问题。这将通过使用面向方面的编程技术来公开对利益（尤其是性能或功耗）有直接影响的调整旋钮来实现。使用从应用程序规范自动派生的排队网络模型可以了解这些调节旋钮的影响。排队模型将用于指导自动控制过程，旨在通过调整调谐旋钮来最大化利益。该项目将利用许多计算科学应用程序作为测试用例，为计算生物学和数据科学界带来好处。 研究生和本科生都将参与这项研究，多个大学级别的项目将用于帮助吸引代表性不足的人群。相关数据、代码和其他补充材料将放置在大学图书馆的永久存储库中：https://openscholarship.wustl.edu/data/。该存储库将提供对代码和数据的持续、有组织的访问，包括对 DOI 的支持。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A Concurrency Framework for Priority-Aware Intercomponent Requests in CAmkES on seL4

SEL4 上 CAmkES 中优先级感知组件间请求的并发框架

• DOI: 10.1109/rtcsa55878.2022.00007
• 发表时间: 2022
• 期刊: Proc. of 28th International Conference on Embedded and Real-Time Computing Systems and Applications
• 作者: Sudvarg, Marion;Gill, Chris
• 通讯作者: Gill, Chris

Designing Domain Specific Computing Systems

设计特定领域的计算系统

• DOI: 10.1109/fccm48280.2020.00052
• 发表时间: 2020
• 期刊: IEEE 28th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM
• 作者: Cabrera, Anthony M.;Chamberlain, Roger D.
• 通讯作者: Chamberlain, Roger D.

Enabling Real-Time Irregular Data-Flow Pipelines on SIMD Devices

在 SIMD 设备上启用实时不规则数据流管道

• 发表时间: 2021
• 期刊: Proc. of International Conference on Parallel Processing Workshops
• 作者: Plano, Tom;Buhler, Jeremy
• 通讯作者: Buhler, Jeremy

Reducing Queuing Impact in Irregular Data Streaming Applications

减少不规则数据流应用程序中的排队影响

• DOI: 10.1109/ia351965.2020.00009
• 发表时间: 2020
• 期刊: Proc. of IEEE/ACM 10th Workshop on Irregular Applications: Architectures and Algorithms
• 作者: Timcheck, Stephen W.;Buhler, Jeremy D.
• 通讯作者: Buhler, Jeremy D.

Elastic Scheduling for Fixed-Priority Constrained-Deadline Tasks

• DOI: 10.1109/isorc58943.2023.00014
• 发表时间: 2023-05
• 期刊: 2023 IEEE 26th International Symposium on Real-Time Distributed Computing (ISORC)
• 作者: M. Sudvarg;Sanjoy Baruah;Chris Gill