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

体系结构多样化的计算机是包含硬件加速器（如图形引擎）和可重构逻辑的系统，这些系统在提高性能方面实现了一些切实的好处，而降低的功耗很难编程。该项目旨在通过使不同架构的计算机能够自我调优，从而极大地提高它们的可编程性，从而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实现，以公开对利益（特别是性能或功耗）有直接影响的调优旋钮。要理解这些调优旋钮的影响，可以使用从应用程序规范自动派生的排队网络模型。排队模型将用于指导自动控制过程，该过程寻求通过调整调优旋钮来最大化利益。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社区提供好处。研究生和本科生都将参与这项研究，几个大学水平的项目将被用来帮助吸引代表性不足的群体的成员。相关数据、代码和其他补充材料将放在大学图书馆的永久存储库https://openscholarship.wustl.edu/data/。该存储库将提供对代码和数据的持久、精心策划的访问，包括对doi的支持。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.