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.