CSR:Small: Towards Reliable Concurrent Computing Using Hybrid Program Analysis

CSR：小：使用混合程序分析实现可靠的并发计算

• 批准号: 1118059
• 负责人: Liqiang Wang
• 金额: $ 35.46万
• 依托单位: University of Wyoming
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-15 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1118059&HistoricalAwards=false
• 关键词: CSR; Small; Towards; Reliable; Concurrent

Inexpensive multi-core processors and many-core GPUs present tremendous opportunities as well as serious challenges for software developers. Developing concurrent programs is intrinsically difficult because multi-threading introduces a whole new class of errors that do not exist in sequential programs. This problem is exacerbated when developing and debugging large-scale, data-intensive, and computation-intensive programs. Traditional testing and debugging techniques are not appropriate for multi-threaded programs which may behave differently from one run to another because threads are scheduled non-deterministically.This project develops a toolkit to detect correctness and performance problems on shared memory systems with the following techniques. (1) Exploit the benefits of static and dynamic analyses while avoiding their shortcomings. Specifically, extend dynamic analysis by augmenting it with static analysis to systematically explore program code for error detection and prevention. (2) Investigate different optimization approaches to lower runtime overhead and improve the toolkit's scalability. (3) Design a unified framework that can predict potential errors and enforce the scheduler to avoid the errors by manipulating accessing orders.The success of this project may enhance the dependability of parallel computing systems and help design more reliable multi-threaded programs. Research results will be integrated into the teaching of undergraduate and graduate courses such as operating systems, parallel programming, and compiler design.

廉价的多核处理器和众核GPU为软件开发人员带来了巨大的机遇和严峻的挑战。开发并发程序本质上是困难的，因为多线程引入了一种全新的错误类型，而这些错误在顺序程序中是不存在的。当开发和调试大规模、数据密集型和计算密集型程序时，这个问题会加剧。传统的测试和调试技术不适用于多线程程序，因为线程的调度是不确定的，这些程序在不同的运行中可能会有不同的行为。本项目开发了一个工具包，用于检测共享内存系统上的正确性和性能问题。(1)利用静态和动态分析的优点，同时避免其缺点。具体来说，通过静态分析来扩展动态分析，从而系统地探索用于错误检测和预防的程序代码。(2)研究不同的优化方法，以降低运行时开销并提高工具包的可伸缩性。(3)设计一个统一的框架，可以预测潜在的错误，并通过操纵访问顺序来执行调度器以避免错误，该项目的成功将有助于提高并行计算系统的可靠性，并有助于设计更可靠的多线程程序。研究成果将被整合到本科和研究生课程的教学中，如操作系统，并行编程和编译器设计。