SHF: Small: Automated Analysis and User Feedback on Data Movement Bottlenecks in Programs

在当前的计算机系统中，相对于执行算术运算的成本，在时间和能量方面，通过存储器层次结构的数据移动的成本非常高。 预计它将在未来的计算机系统中变得更加主导。因此，优化数据访问成本在未来几年将变得越来越重要。这对此类系统的算法设计和实现有很大的影响。 数据访问复杂性的表征今天只为少数几类算法所知，如稠密线性代数，并且需要使用特定于问题的分析技术。 该建议提出了新的想法，开发自动化的工具和技术来表征固有的数据访问复杂性的任意算法。一种可自动化的程序数据访问复杂性的通用方法将对导出高效算法及其实现，理解未来体系结构对算法设计的影响，以及旨在改善程序数据访问成本的编译器的进展。该提案提出了新的想法，以解决日益重要的基本问题--开发用于表征算法的固有数据访问复杂性的工具和技术。该工作开发了以下内容：（i）第一个统一的方法，用于在一个共同的基础理论模型下开发CDAG固有数据访问复杂性的上限和下限;（ii）一种方法，用于消除当前使用流行的重用距离分析度量的基本限制;（iii）应用程序开发人员、编译器编写人员和架构设计人员使用的可伸缩和通用的动态分析基础设施。

The cost of data movement through the memory hierarchy is very high in current computer systems, relative to the cost of performing arithmetic operations, both in terms of time and energy. It is expected to become even more dominant in future computer systems. Therefore optimizing data access costs will become increasingly critical in the coming years. This has great impact on algorithm design and implementation on such systems. A characterization of data access complexity is only known today for a few classes of algorithms, such as dense linear algebra, and has required the use of problem-specific analysis techniques. This proposal presents novel ideas for developing automated tools and techniques to characterize the inherent data access complexity of arbitrary algorithms. An automatable general approach for data access complexity of programs will have significant impact on deriving highly effective algorithms and their implementations, understanding the impact of future architectures on algorithm design, and on advances in compilers aimed at improving data access costs of programs.The proposal develops novel ideas to address a fundamental problem of increasing importance -- developing tools and techniques for characterization of the inherent data access complexity of algorithms. The work develops the following: (i) the first unifying approach for developing both upper and lower bounds for the inherent data access complexity of a CDAG under a common underlying theoretical model; (ii) an approach to remove a fundamental current limitation in the use of the popular reuse distance analysis metric; (iii) a scalable and versatile dynamic analysis infrastructure of use to application developers, compiler writers and architecture designers.