CAPA: Collaborative Research: Lightweight Abstract Memory Features

现代计算系统的存储器子系统已经经历了巨大的创新，结合了新的功能来帮助程序员创建快速，安全，正确和节能的软件。 不幸的是，利用这些功能是一个挑战，因为编程语言不向程序员展示内存子系统的高级功能。 这个项目的重点是编程语言和存储器硬件之间的接口。其智力优势包括为内存特性创建了严格的语义，这样程序员就可以对各个特性及其组成进行推理;以及创建编译工具和运行时系统，允许程序员单独或组合使用新的内存特性，以获得最大收益。 该项目的更广泛的意义和重要性是它对软件和硬件行业的影响，通过促进新的内存功能的快速采用;研究生的教育和培训;以及创建一个教程，以帮助传播和采用所开发的工具和技术。存储器功能的硬件实现通常很快，但受到物理容量的限制，并且特征的精确语义通常是厂商特定的。 理论部分的工作将创建严格的语义内存功能，超越个人的实现，并允许程序员和静态分析工具的原因程序与内存的相互作用。 该研究将构建虚拟化的运行时系统，以克服硬件的限制，并模拟功能时，他们不存在。 它的实现将采用运行时自适应性来微调自己以适应给定系统的功能可用性、对功能组合的支持以及硬件/工作负载特性。 构建在LLVM系统之上的自定义编译器基础设施将提供轻量级语法，通过该语法，程序员可以轻松地将对内存特性的支持添加到现有代码中。

The memory subsystem of modern computing systems has seen tremendous innovations, incorporating new features to aid programmers in creating fast, secure, correct, and power-efficient software. Unfortunately, harnessing these features is a challenge, as programming languages do not expose advanced abilities of the memory subsystem to programmers. This project focuses on the interface between programming languages and memory hardware. The intellectual merits include the creation of a rigorous semantics for memory features, so that programmers can reason about individual features and their composition; and the creation of compilation tools and run-time systems that allow programmers to use new memory features, in isolation or combination, for maximum gain. The project's broader significance and importance are its impact on the software and hardware industry, by facilitating rapid adoption of new memory features; the education and training of graduate students; and the creation of a tutorial to aid in dissemination and adoption of the developed tools and techniques.Hardware implementations of memory features are typically fast but limited by physical capacity, and the precise semantics of features are often vendor-specific. The theoretical portion of the work will create rigorous semantics for memory features, which transcend individual implementation and allow programmers and static analysis tools to reason about a program's interaction with memory. The research will construct virtualized run-time systems to overcome hardware constraints, and to emulate features when they are not present. Its implementations will employ run-time adaptivity to fine-tune themselves to a given system's feature availability, support for composition of features, and hardware/workload characteristics. A custom compiler infrastructure, built atop the LLVM system, will provide a lightweight syntax through which programmers can easily add support for memory features to their existing codes.