CAREER: Scalable Compiler Optimizations for New Software

本研究计划的目标是为新兴的软件应用开发编译器优化技术。 与当前的实践状态相比，新的软件应用程序将用类型安全语言编写（例如，Java）将包含数百万行代码，通常由分布在多台机器上的组件构建，并将在具有多个控制线程的处理器上运行，但需要数百个周期才能访问主存。 现代软件将需要现代优化，需要在三个方面可扩展：程序的大小，分布式组件的数量以及不断增长的内存延迟。 这项研究提出了实现可扩展性，利用从根本上新颖的形式的投机，剖析，需求驱动的分析，运行时检查，和硬件支持。 为了开发这些技术，将进行三项具体的工作：消除数组边界检查，需求驱动的指针分析，以及基于指针的数据结构的预取。

The goal of this research program is to develop compiler optimization technology for emerging software applications. Compared to the current state-of-the-practice, the new software applications will be written in type-safe languages (e.g., Java), will contain millions of lines of code, will often be built from components distributed across multiple machines, and will run on processors that will have multiple threads of control, but will take hundreds of cycles to access the main memory. Modern software will require modern optimizations that will need to be scalable in three ways: with the size of the program, with the number of distributed components, and with the growing memory latency. This research proposes to achieve scalability by exploiting radically novel forms of speculation, profiling, demand-driven analysis, run-time checks, and hardware support. To develop these technologies, three specific efforts will be undertaken: elimination of array-bounds checks, demand-driven pointer analysis, and prefetching for pointer-based data structures.