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多核GPU为软件开发人员带来了巨大的机会以及严重的挑战。开发并发程序在本质上很难，因为多线程引入了一系列新的错误，这些错误在顺序程序中不存在。在开发和调试大规模，数据密集型和计算密集型程序时，此问题会加剧。传统的测试和调试技术不适合多线程程序，这些程序可能与一项运行的行为不同，因为线程是非确定性的，因此该项目开发了一个工具包，以通过以下技术在共享内存系统上检测共享内存系统的正确性和性能问题。 （1）在避免其缺点的同时，利用静态和动态分析的好处。具体而言，通过将静态分析扩展到系统地探索程序代码以进行错误检测和预防，扩展动态分析。 （2）研究不同的优化方法，以降低运行时开销并改善工具包的可扩展性。 （3）设计一个统一的框架，可以通过操纵访问订单来预测潜在错误并强制执行调度程序以避免错误。该项目的成功可能会增强并行计算系统的可靠性，并帮助设计更可靠的多线程程序。研究结果将纳入本科和研究生课程的教学，例如操作系统，并行编程和编译器设计。