Parallel computing has entered the mainstream with increasingly large multicore processors and powerful accelerator devices. These compute engines, coupled with tighter integration of faster interconnection fabrics, are drivers for the next-generation high end computing (HEC) machines. However, the computing potential of HEC machines is delivered only through productive parallel program development and efficient parallel execution. This project enables application developers to improve performance on future HEC machines for their scientific and engineering processes. This project challenges the current model for parallel application development via "black box" tools and services. Instead, the project offers an open, transparent software infrastructure -- a Glass Box system -- for creating and tuning large-scale, parallel applications. `Opening up' the tools and services used to create and evaluate peta- and exa-scale codes involves developing interfaces and methods that make tool-internal information and available for new performance management services that improve developer productivity and code efficiency.
The project will explore the information that can be shared 'across the software stack'. Methods will be developed for analyzing program information, performance data and tool knowledge. The resulting Glass Box system will allow developers to better assess the performance of their parallel codes. Tool creators can use the performance data to create new analysis and optimization techniques. System developers can also better manage multicore and machine resources at runtime, using JIT compilation and binary code editing to exploit the evolving hardware. Working with the `Keeneland' NSF Track II machine and our industry partners, the project will create new performance monitoring tools, compiler methods and system-level resource management techniques. The effort is driven by the large-scale codes running on today's petascale machines. Its broader impact is derived from the interactions with technology developers and application scientists as well as from its base in three universities with diverse student populations.
