CRII: OAC: Building Explainable Computer Architecture with Simulation and Visualization Techniques

CRII：OAC：利用模拟和可视化技术构建可解释的计算机架构

• 批准号: 2246035
• 负责人: Yifan Sun
• 金额: $ 17.5万
• 依托单位: College of William and Mary
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2246035&HistoricalAwards=false
• 关键词: CRII; OAC; Building; Explainable; Computer

Computing systems are getting more and more complex to achieve high performance. On the one hand, different devices are combined in one heterogeneous platform so that specialized applications (e.g., artificial intelligence) can execute more efficiently. On the other hand, the scale of devices and systems is getting much larger. The heterogeneity and the massive scale of computing systems make it challenging for researchers to understand, interpret, and explain the behavior of each hardware component that participates in application execution. The lack of explainability of existing computer architectures can potentially lead to functional bugs, performance drawbacks, security vulnerabilities, and reliability problems. This project advocates the importance of building Explainable Computer Architecture by enhancing computer architecture simulators and developing visualization tools that help analyze performance issues. The research outcome of this project reduces the barriers for students, especially students from underrepresented groups, to participate in computer architecture design, development, and research.This project initiates the Explainable Computer Architecture research direction, which can accelerate innovation in computer architecture research and design. This project contributes to a universal data format and instrumentation library for computer architecture simulators to collect execution traces for visualization purposes. Additionally, this project develops a novel data visualization tool for network-on-chips system performance analysis, facilitating the identification of performance issues in large-scale and highly-coupled computing systems. Moreover, this project delivers an educational game, based on the simulator and the visualization tool developed in this project, to support K-12 computer science education. Finally, using a research-through-design approach, the experiences learned from this project guide the community to design future ``easier-to-explain'' computer architectures.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.

为了实现高性能，计算系统变得越来越复杂。一方面，不同的设备被组合在一个异构平台中，以便专业应用程序（例如人工智能）可以更有效地执行。另一方面，设备和系统的规模变得越来越大。计算系统的异构性和大规模使得研究人员很难理解、解释和解释参与应用程序执行的每个硬件组件的行为。现有计算机架构缺乏可解释性可能会导致功能错误、性能缺陷、安全漏洞和可靠性问题。该项目提倡通过增强计算机体系结构模拟器和开发有助于分析性能问题的可视化工具来构建可解释的计算机体系结构的重要性。该项目的研究成果降低了学生，特别是来自弱势群体的学生参与计算机体系结构设计、开发和研究的障碍。该项目首创了可解释计算机体系结构研究方向，可以加速计算机体系结构研究和设计的创新。该项目为计算机体系结构模拟器提供了通用数据格式和仪器库，以收集用于可视化目的的执行跟踪。此外，该项目开发了一种用于片上网络系统性能分析的新型数据可视化工具，有助于识别大规模和高度耦合的计算系统中的性能问题。 此外，该项目还提供了一款基于该项目开发的模拟器和可视化工具的教育游戏，以支持 K-12 计算机科学教育。最后，采用从研究到设计的方法，从该项目中汲取的经验指导社区设计未来“更容易解释”的计算机架构。该奖项反映了 NSF 的法定使命，并通过评估认为值得支持利用基金会的智力优势和更广泛的影响审查标准。

项目成果

Visual Exploratory Analysis for Designing Large-Scale Network-on-Chip Architectures: A Domain Expert-Led Design Study

设计大规模片上网络架构的可视化探索性分析：领域专家主导的设计研究

• DOI: 10.1109/tvcg.2023.3337173
• 发表时间: 2024-04
• 期刊: IEEE Transactions on Visualization and Computer Graphics
• 影响因子: 5.2
• 作者: Wang, Shaoyu;Yan, Hang;Isaacs, Katherine E.;Sun, Yifan
• 通讯作者: Sun, Yifan