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

背景使用可用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。随着计算机性能的提高，可以准确地模拟更复杂的现象，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。该提案旨在开发一种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、循环平铺和数据/工作分区的基于搜索的方法集成在一起。 该项目的结果将使科学应用（例如量子化学计算和其他并行建模和模拟）更容易编程，并将缩短项目实施和开发时间。 智力优点该提案的目标是开发一个编译器优化框架，该框架使用性能模型（例如缓存未命中成本、磁盘 I/O 成本和处理器间通信成本）执行循环转换，这些模型预计与测量的性能直接相关。由于分析确定最佳参数通常是不可行的，甚至创建可表示为相关参数的代数函数的成本模型也是不可行的，因此我们的方法是在潜在的大参数空间中使用搜索策略。这种新颖的优化框架在生成高性能代码方面具有潜在的高回报。Broader ImpactCompiler 技术可以非常有效地减少科学和工程多个领域的应用程序开发时间，而无需牺牲性能。人们越来越需要自动化支持来减轻用户的负担，以及优化性能所需的低级细节。我们建议构建的框架将适用于多种高级语言模型，例如Matlab、Global Arrays、UPC、Co-Array Fortran、ZPL等。开发将在Open64框架中完成，所得软件将可供其他人使用。预计所开发的框架将对学术界和研究实验室的研究人员有价值。最后，该提案包括开发新课程和培养两名研究生。

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.