ST-CRTS: Search-Based Model-Driven Framework for Compiler Optimizations

背景使用现有的语言和工具开发高性能软件的困难被认为是当今有效使用高性能计算机的最重大挑战之一。随着计算机性能的不断提高，对更复杂的现象进行精确建模成为可能，开发软件所需的时间和精力已成为许多科学和工程领域的瓶颈。本提案旨在开发一个性能模型驱动的编译器优化框架，该框架将用于循环表示/转换的代数模型与用于循环融合的基于搜索的方法相结合，循环平铺和数据/工作分区。 该项目的结果将使科学应用，如量子化学计算，和其他并行建模和模拟，更容易编程，并将削减项目实施和开发时间。智力MeritThe目标的建议是开发一个框架，编译器优化，执行循环转换使用性能模型，如缓存未命中成本，磁盘I/O成本，和处理器间通信成本，可以预期与测量的性能直接相关。由于它通常是不可行的分析确定最佳参数，甚至创建成本模型，可表示为相关参数的代数函数，我们的方法是使用搜索策略在一个潜在的大参数空间。这种新颖的优化框架在生成高性能代码方面具有很高的回报潜力。更广泛的冲击器技术可以非常有效地减少在科学和工程的几个领域开发应用程序的时间，而不会牺牲性能。人们越来越需要自动化支持，以减轻用户在优化性能所需的低级细节方面的负担。我们建议建立的框架将适用于一些高级语言模型，如Matlab，全局数组，UPC，协阵Fortran，ZPL等的开发将在Open 64框架中完成，所产生的软件将提供给他人。预计开发的框架将对学术界和研究实验室的研究人员很有价值。最后，本建议包括新课程的开发和两名研究生的培养。

BackgroundThe difficulty of developing high-performance software using the available languages and tools is being recognized as one of the most significant challenges today in the effective use of high-performance computers. As computers have increased in achievable performance, making it feasible to accurately model more complex phenomena, the time and effort required to develop the software has become the bottleneck in many areas of science and engineering.This proposal seeks to develop a performance-model driven a compiler optimization framework that integrates the algebraic model for loop representation/transformation with a search-based approach for loop fusion, loop tiling and data/work partitioning. The result of the project will make scientific applications, such as quantum chemistry calculations, and other parallel modeling and simulations, easier programmable, and will cut project implementation and development time.Intellectual MeritThe goal of this proposal is to develop a framework for compiler optimization that performs loop transformations using performance models such as cache miss cost, disk I/O cost, and inter-processor communication cost, that can be expected to correlate directly with measured performance. Since it will generally be infeasible to analytically determine optimal parameters, or even create cost models that are expressible as algebraic functions of pertinent parameters, our approach is to use search strategies in a potentially large parameter space. This novel optimization framework has potential for high payoffs in generating high-performance code.Broader ImpactCompiler technology can be very effective in reducing the time for developing applications inseveral areas of science and engineering without sacrificing performance. There is an increasing need for automated support that can relieve the burden from users, of low-level details needed to optimize performance. The framework we propose to build will be applicable to a number of high-level language models such as Matlab, Global Arrays, UPC, Co-Array Fortran, ZPL etc. The development will be done in the Open64 framework and the resulting software will be made available to others. It is anticipated that the developed framework will be valuable to researchers in academia and research laboratories. Finally, this proposal includes the development of new courses and the training of two graduate students.