Improving Modern Programming Language Performance: A Memory-Conscious Approach

提高现代编程语言的性能：内存意识方法

• 批准号: DP0452011
• 负责人: Prof Stephen Blackburn
• 金额: $ 8.96万
• 依托单位: The Australian National University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2004
• 资助国家: 澳大利亚
• 起止时间: 2004-01-01 至 2006-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0452011
• 关键词: Improving; Modern; Programming; Language; Performance

The performance of modern programming languages such as Java and C# lags that of imperative languages such as C and Fortran. A significant source of the performance gap is poor memory behavior, which future computer architectures will exacerbate. This project addresses the problem of poor memory behavior in modern programming languages such as Java and C# through an integrated attack that incorporates new garbage collection algorithms, run-time techniques that optimize running programs, and new compiler analyses with both static and dynamic optimizations. The project will give Australia an international presence in a research area of great academic and commercial importance.

现代编程语言（如Java和c#）的性能落后于命令式语言（如C和Fortran）。性能差距的一个重要来源是糟糕的内存行为，未来的计算机架构将加剧这一问题。该项目通过集成攻击解决了现代编程语言（如Java和c#）中糟糕的内存行为问题，该攻击结合了新的垃圾收集算法、优化运行程序的运行时技术，以及具有静态和动态优化的新编译器分析。该项目将给澳大利亚一个