CNS Core: Small: Rethinking High-Performance Persistent Transactions

CNS 核心：小型：重新思考高性能持久事务

• 批准号: 2106117
• 负责人: Michael Bond
• 金额: $ 50万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2106117&HistoricalAwards=false
• 关键词: CNS; Core; Small; Rethinking; Performance

Persistent memory is an exciting new technology that bridges the gap between two well-established technologies: main memory, which is fast to access but loses its contents in the event of power loss or hardware failure, and the disk, which is slow to access but retains its contents if the power goes off or the hardware fails. To help programmers write correct programs using persistent memory, programming languages provide a construct called persistent transactions, which help ensure that persistent memory can recover to an understandable state after a power or hardware failure. However, existing algorithms for persistent transactions slow programs significantly because they rely on techniques called crash-consistency mechanisms that are inefficient. The project develops two novel crash-consistency mechanisms that overcome the limitations of prior crash-consistency mechanisms. The project applies these new mechanisms to develop new persistent transaction algorithms. The project evaluates these algorithms empirically in comparison to prior persistent transaction algorithms, on real-world persistent memory programs and platforms. A key insight of the new crash-consistency mechanisms lies in the novel way they leverage technology called hardware transactional memory that is included in Intel processors. The work aims to contribute efficient crash-consistency mechanisms and persistent transaction algorithms that are more efficient than prior approaches and to influence future research in this rapidly developing area.The project aims to improve the performance of a key construct for achieving reliable persistent memory programs. This improvement can help make persistent memory widely practical, by achieving both main memory's performance and the disk's retention of contents in the event of failure. Practical persistent memory will improve programmer productivity and make computing systems faster and more reliable. These benefits in turn will impact society across domains that rely on computing, including science, engineering, transportation, and medicine. To increase impact, the implementations resulting from the project will be made publicly available in addition to published research papers. Undergraduate and graduate courses taught by the PI will incorporate the project's research topics. Workshops organized by the PI will expose undergraduate students, especially students who are members of underrepresented groups, to computing research and grad school. These activities will help to educate a diverse workforce of computer scientists trained in the project's topics and research.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.

持续记忆是一项令人兴奋的新技术，它弥合了两种完善的技术之间的差距：主内存，它可以迅速访问，但在发生功率损耗或硬件故障的情况下会丢失其内容，而磁盘却很慢，该磁盘访问速度很慢，但如果电源熄灭或硬件失败，则保留其内容。为了帮助程序员使用持续内存编写正确的程序，编程语言提供了一种称为持续交易的构造，这有助于确保持续的内存可以在功率或硬件故障后恢复到可理解的状态。但是，持续交易的现有算法大大缓慢，因为它们依赖于称为崩溃一致性机制的技术，这些技术效率低下。该项目开发了两种新型的碰撞一致性机制，这些机制克服了先前的碰撞一致性机制的局限性。该项目应用了这些新机制来开发新的持久交易算法。与先前的持久交易算法，现实世界持续的内存程序和平台相比，该项目从经验上评估了这些算法。对新碰撞抗性机制的关键见解是他们利用英特尔处理器中包含的称为硬件交易记忆的新型技术。该作品旨在促进有效的碰撞矛盾机制和持续的交易算法，这些算法比以前的方法更有效，并影响了这个迅速发展的领域的未来研究。该项目旨在提高实现可靠的持久记忆计划的关键构造的性能。这种改进可以通过在失败时实现Main Memory的性能和磁盘的保留，从而有助于使持续的内存变得广泛实用。实用的持续记忆将提高程序员的生产率，并使计算系统更快，更可靠。这些好处反过来会影响跨计算领域的社会，包括科学，工程，运输和医学。为了增加影响，除已发表的研究论文外，还将公开提供该项目的实施。 PI教授的本科和研究生课程将纳入该项目的研究主题。由PI组织的研讨会将揭露本科生，尤其是代表性群体不足的学生，以计算研究和研究生院。这些活动将有助于教育在该项目主题和研究中培训的计算机科学家的多样化劳动力。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响评估标准，认为值得通过评估来获得支持。

项目成果

Cape: compiler-aided program transformation for HTM-based cache side-channel defense

Cape：基于 HTM 的缓存侧通道防御的编译器辅助程序转换

• DOI: 10.1145/3497776.3517778
• 发表时间: 2022
• 期刊: ACM SIGPLAN International Conference on Compiler Construction (CC
• 作者: Zhang, Rui;Bond, Michael D.;Zhang, Yinqian
• 通讯作者: Zhang, Yinqian

Distilling the Real Cost of Production Garbage Collectors

提取垃圾收集器的实际生产成本

• DOI: 10.1109/ispass55109.2022.00005
• 发表时间: 2022
• 期刊: IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS
• 作者: Cai, Zixian;Blackburn, Stephen M.;Bond, Michael D.;Maas, Martin
• 通讯作者: Maas, Martin

Mako: a low-pause, high-throughput evacuating collector for memory-disaggregated datacenters

• DOI: 10.1145/3519939.3523441
• 发表时间: 2022-06
• 期刊: Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation
• 作者: Haoran Ma;Chenxi Wang;Yifan Qiao;Miryung Kim