CAPA: Collaborative Research: Lightweight Abstract Memory Features

CAPA：协作研究：轻量级抽象内存功能

• 批准号: 1723624
• 负责人: Michael Spear
• 金额: $ 50万
• 依托单位: Lehigh University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1723624&HistoricalAwards=false
• 关键词: CAPA; Collaborative; Research; Lightweight; Abstract

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.

现代计算系统的内存子系统已经看到了巨大的创新，并结合了新功能，以帮助程序员创建快速，安全，正确和发电的软件。 不幸的是，利用这些功能是一个挑战，因为编程语言并未将内存子系统的高级能力展示到程序员。 该项目着重于编程语言和内存硬件之间的接口。智力优点包括为记忆特征创建严格的语义，以便程序员可以推荐个人特征及其组成；以及创建编译工具和运行时系统，允许程序员隔离或组合使用新的内存功能，以获得最大的增益。 通过促进新的内存功能的快速采用，该项目对软件和硬件行业的影响更大。研究生的教育和培训；并创建了一个教程，以帮助传播和采用开发的工具和技术。内存功能的硬件实现通常是快速但受物理能力的限制，并且功能的精确语义通常是特定于供应商的。 工作的理论部分将为内存功能创建严格的语义，从而超越了单个实现，并允许程序员和静态分析工具来推理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，以克服硬件约束，并在不存在的功能时效仿。 它的实现将采用运行时适应性，以将自己调整为给定系统的功能可用性，对功能组成的支持以及硬件/工作负载特征。 在LLVM系统上构建的自定义编译器基础架构将提供一种轻巧的语法，程序员可以通过该语法可以轻松地为其现有代码添加对内存功能的支持。

项目成果

Understanding and Improving Persistent Transactions on Optane™ DC Memory

• DOI: 10.1109/ipdps47924.2020.00044
• 发表时间: 2020-05
• 期刊: 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
• 作者: P. Zardoshti;Michael F. Spear;A. Vosoughi;G. Swart

Optimizing Persistent Memory Transactions

• DOI: 10.1109/pact.2019.00025
• 发表时间: 2019-09
• 期刊: 2019 28th International Conference on Parallel Architectures and Compilation Techniques (PACT)
• 作者: P. Zardoshti;Tingzhe Zhou;Yujie Liu;Michael F. Spear

Simplifying Transactional Memory Support in C++

• DOI: 10.1145/3328796
• 发表时间: 2019-07
• 期刊: ACM Transactions on Architecture and Code Optimization (TACO)
• 作者: P. Zardoshti;Tingzhe Zhou;Pavithra Balaji;M. Scott;Michael F. Spear

RnR: A Software-Assisted Record-and-Replay Hardware Prefetcher

• DOI: 10.1109/micro50266.2020.00057
• 发表时间: 2020-10
• 期刊: 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)
• 作者: Chao Zhang;Yuan Zeng;J. Shalf;Xiaochen Guo

ClusCross: a new topology for silicon interposer-based network-on-chip

• DOI: 10.1145/3313231.3352363
• 发表时间: 2019-10
• 期刊: Proceedings of the 13th IEEE/ACM International Symposium on Networks-on-Chip
• 作者: Hesam Shabani;Xiaochen Guo