SHF: Small: Collaborative Research: Hybrid Static-Dynamic Analyses for RegionSerializability

SHF：小型：协作研究：区域可串行性的混合静态动态分析

• 批准号: 1422178
• 负责人: Milind Kulkarni
• 金额: $ 7.37万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1422178&HistoricalAwards=false
• 关键词: SHF; Small; Collaborative; Research; Hybrid

Title: SHF: Small: Collaborative Research: Hybrid Static-Dynamic Analyses for Region SerializabilityComputer systems' performance has grown exponentially for decades, enabling advances in science, health, engineering, and other areas. However, due to power, heat, and wire-length limitations, chip manufacturers are now producing microprocessors that have more, instead of faster, computing cores. To scale with this increasingly parallel hardware, software systems must become more parallel. However, writing correct, scalable shared-memory programs is notoriously difficult. A key challenge is that modern programming languages and software and hardware systems provide virtually no guarantees for programs that have a common, hard-to-eliminate behavior called data races -- because no one knows how to provide better guarantees while retaining high performance. As a result, software is difficult to reason about and fails unexpectedly, leading to high development and testing costs, and imperiling reliability and security of mission- and safety-critical systems. This project provides stronger guarantees for software, achieving reasonable performance on contemporary systems. The intellectual merits are novel program analyses and runtime support that provide strong behavioral guarantees for programs. The project's broader significance and importance are making software systems automatically more reliable; eliminating whole classes of errors; reducing development and testing costs by simplifying programming; and simplifying and reducing costs of program analyses and software system support. Furthermore, the PIs' educational, mentoring, and outreach activities enhance the project by helping educate a diverse workforce of computer scientists trained in the project's work.A key contribution is a novel hybrid static-dynamic analysis that enforces a memory model called statically bounded region serializability (SBRS) entirely in software. This memory model is strictly stronger than sequential consistency (SC) and has the potential to be more efficient than SC to enforce, since it allows compilers and hardware to reorder instructions within regions. The project involves designing, implementing, and evaluating (1) three compiler transformations for enforcing SBRS, (2) enhancements to the static-dynamic analysis for performance and flexibility, (3) a novel asynchronous protocol for overlapping concurrency control with program execution while enforcing SBRS, and (4) enhancements to a software transactional memory (STM) system to use the asynchronous protocol to improve scalability. The work provides, for the first time, support for always-on, end-to-end SBRS that is practical, and it makes further advancements in providing high-performance runtime support for atomicity.

标题：SHF：小：协作研究：区域序列化的混合静态动力分析数十年来成倍增长，从而在科学，健康，工程和其他领域取得了进步。但是，由于功率，热量和电线限制，芯片制造商现在正在生产具有更多（而不是更快计算核心）的微处理器。为了通过越来越平行的硬件进行扩展，软件系统必须变得更加平行。但是，众所周知，编写正确的可扩展共享内存程序是很困难的。一个关键的挑战是，现代编程语言，软件和硬件系统几乎没有保证具有常见，难以阐明的行为称为数据竞赛的程序 - 因为没人知道如何在保持高性能的同时提供更好的保证。结果，软件很难理解和意外失败，从而导致高昂的开发和测试成本，并使任务和关键安全系统的可靠性以及安全性和安全性。该项目为软件提供了更强的保证，从而在当代系统上实现了合理的性能。智力优点是新颖的计划分析和运行时支持，可为程序提供强大的行为保证。该项目更广泛的意义和重要性使软件系统自动更加可靠。消除整个错误；通过简化编程来降低开发和测试成本；并简化和降低程序分析和软件系统支持的成本。此外，PIS的教育，指导和推广活动通过帮助教育在项目工作中培训的计算机科学家的多样化劳动力来增强项目。一个关键的贡献是一种新型的混合静态分析，可以在软件中实施一种称为统计上有限的区域串行性（SBRS）的记忆模型。该内存模型严格比顺序一致性（SC）强，并且具有比SC更有效的潜力来执行，因为它允许编译器和硬件可以在区域内重新排序指令。 The project involves designing, implementing, and evaluating (1) three compiler transformations for enforcing SBRS, (2) enhancements to the static-dynamic analysis for performance and flexibility, (3) a novel asynchronous protocol for overlapping concurrency control with program execution while enforcing SBRS, and (4) enhancements to a software transactional memory (STM) system to use the asynchronous protocol to improve scalability.这项工作首次为实用的始终端到端SBR提供了支持，并在提供高性能的原子能支持方面取得了进一步的进步。