Collaborative Research: CSR---AES: A Framework for Optimizing Scientific Applications

标题：合作研究：CSR-AES：优化科学应用的框架科学应用的设计优化器（DOSA）框架允许程序员或编译器作者探索替代设计并优化速度（或电源），并使用其运行时优化器作为自动应用程序组合系统（ACS），该系统构建了一个高效的应用程序，该应用程序基于内核模型，体系结构，系统功能、可用资源和性能反馈。 DOSA允许使用持续性能优化（CPO）进行设计时探索和自动运行时优化，从而使应用程序员和编译器编写人员从优化计算以实现高性能的挑战性任务中解脱出来。 作为DOSA框架的扩展，一个复杂的完整应用程序针对IBM Cell进行了优化。 存储器层次结构的创新性能优化技术使用新技术来降低I/O复杂性、数据布局、数据重映射和内存处理，并得到DOSA、半自动设计框架和动态运行时系统的支持。该框架允许快速，高层次的性能估计和详细的低层次的模拟，将高层次的性能模型到模型集成的计算框架。 运行时系统使用组件库、模型和运行时优化器动态地提高应用程序的性能。 选择应用研究是因为它们对传统和新兴科学领域（如生物信息学、计算生物学和医学应用）以及对国家安全的广泛影响。该项目特别鼓励妇女、少数民族和代表性不足的群体参与。

Title:Collaborative Research: CSR---AES: A Framework for Optimizing Scientific ApplicationsThe Design Optimizer for Scientific Applications (DOSA) frameworkallows the programmer or compiler writer to explore alternativedesigns and optimize for speed (or power) at design-time and use itsrun-time optimizer as an automatic application composition system(ACS) that constructs an efficient application that dynamically adaptsto changes in the underlying execution environment based on the kernelmodel, architecture, system features, available resources, andperformance feedback. DOSA allows design-time exploration andautomatic run-time optimizations using continuous performanceoptimizations (CPO) so that application programmers and compilerwriters are relieved from the challenging task of optimizing thecomputation in order to achieve high performance. As an illustrationof the DOSA framework, one complex, full application is optimized forIBM Cell. The innovative performance optimization techniques for thememory hierarchy use new techniques for reducing I/O complexity, datalayout, data remapping, and in-memory processing, and are supported byDOSA, the semi-automatic design framework and dynamic run-timesystem. This framework allows rapid, high-level performance estimationand detailed low-level simulation by incorporating high-levelperformance models into the model-integrated computing framework. Therun-time system dynamically improves application performance using thecomponent library, the models, and the run-time optimizer. Theapplication studies are chosen for their broad impact to traditionaland emerging scientific areas such as bioinformatics, computationalbiology, and medical applications, as well as for national security.The project especially encourages the participation by women,minorities, and underrepresented groups.