This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).
The burgeoning revolution in high-end computer architecture has far reaching implications for the software infrastructure of tools for performance measurement, modeling, and optimization, which has been indispensable to improved productivity in computational science over the past decade. The heart of the problem is that new multicore processors are the foundation of next generation systems, ranging from workgroup clusters to petascale supercomputers. The main motivation by chip manufacturers for the movement to multicore processors is better performance per watt than the traditional single core processor. Hence, multicore processors are not equivalent to multiple CPUs that traditional tools addressed. While significant work is underway on understanding performance tradeoffs with multicores, much of this work is ad hoc and needs a unifying framework to which the community can contribute in a systematic manner. Furthermore, little work has been done on understanding performance-power tradeoffs in supercomputer systems for large-scale applications. It is important to understand performance and performance-power tradeoffs in the context of the significant resource sharing that occurs in multicore systems.
This proposal is focused on developing the Multicore Application Modeling Infrastructure (MAMI) that will facilitate systematic measurement, modeling, and prediction of performance, power consumption and performance-power tradeoffs in multicore systems. In addition to developing MAMI, the proposed work will use MAMI to model, analyze and optimize performance and power consumption of key benchmarks and applications on multicore systems.