EAGER: Profile and Transformation Driven Automatic Parallelization with Interactive Reports

该研究探索了一种自动并行化顺序程序的新方法。与现有的并行化编译器不同，现有的并行化编译器使用静态分析来并行化使用仿射访问函数来操作密集矩阵的循环嵌套，这种方法应用了一组转换，类似于专家开发人员在手动开发并行程序时所应用的转换。这些转换引入了一个搜索空间，编译器将自动探索该空间以提供它所能找到的最佳并行化。编译器通过在代表性输入上运行转换后的程序来评估每个转换的成功，以观察1)转换对并行程序的性能的影响(如果有的话)以及2)转换后的程序是否产生可接受的准确结果。该技术将生成一份报告，开发人员可以查看该报告以了解并行化过程。这项研究将根据需要进行调整，以反映在研究过程中获得的知识。这项研究的意义在于，多核机器被认为是我们未来计算基础设施的基础，而且众所周知，这种机器很难编程。考虑到这种组合，研究新的和潜在更有效的技术可以帮助获得利用这类机器所需的并行软件。

The research investigates a new approach for automatically parallelizing sequential programs. In contrast to existing parallelizing compilers, which use static analysis to parallelize loop nests that use affine access functions to manipulate dense matrices, this approach applies a set of transformations similar to those that expert developers apply when manually developing parallel programs. These transformations induce a search space that the compiler will automatically explore to deliver the best parallelization it can find. The compiler evaluates the success of each transformation by running the transformed program on representative inputs to observe 1) the impact (if any) of the transformation on the performance of the parallel program and 2) if the transformed program produces an acceptably accurate result. The technique will produce a report that the developer can examine to understand the parallelization process. The research will adapt as necessary to reflect knowledge gained during the course of the research.The significance of this research is that multicore machines are believed to be the foundation of our future computing infrastructure, and that such machines are known to be difficult to program. Given this combination, investigating new and potentially more effective techniques can help make it possible to obtain the parallel software necessary to utilize this class of machines.