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

Title: Collaborative Research: CSR---AES: A Framework for Optimizing Scientific Applications The Design Optimizer for Scientific Applications (DOSA) framework allows the programmer or compiler writer to explore alternative designs and optimize for speed (or power) at design-time and use its run-time optimizer as an automatic application composition system (ACS) that constructs an efficient application that dynamically adapts to changes in the underlying execution environment based on the kernel model, architecture, system features, available resources, and performance feedback. DOSA allows design-time exploration and automatic run-time optimizations using continuous performance optimizations (CPO) so that application programmers and compiler writers are relieved from the challenging task of optimizing the computation in order to achieve high performance. As an illustration of the DOSA framework, one complex, full application is optimized for IBM Cell. The innovative performance optimization techniques for the memory hierarchy use new techniques for reducing I/O complexity, data layout, data remapping, and in-memory processing, and are supported by DOSA, the semi-automatic design framework and dynamic run-time system. This framework allows rapid, high-level performance estimation and detailed low-level simulation by incorporating high-level performance models into the model-integrated computing framework. The run-time system dynamically improves application performance using the component library, the models, and the run-time optimizer. The application studies are chosen for their broad impact to traditional and emerging scientific areas such as bioinformatics, computational biology, and medical applications, as well as for national security. The project especially encourages the participation by women, minorities, and underrepresented groups.