CDS&E: Optimization of Advanced Cyberinfrastructure through Data-Driven Computational Modeling

University Of New Mexico, Albuquerque NM

Investigators

Abstract

Modern scientific and big-data computing systems must balance multiple system attributes such as power, performance, and reliability to meet application science demands. These systems and their designers are, however, constrained by the lack of clear and well-defined methods to guide system design and tuning. This reduces the overall effectiveness of modern strategic computing systems. This project is developing new techniques for quantitatively characterizing and optimizing system tradeoffs in a wide range of modern strategic computing systems. The short term goal of this project is to develop models, analyses, and optimizations that will enable system software, applications, and system architects to make effective end-to-end performance tradeoffs. The desired long-term impact of this research is to increase the overall efficiency and effectiveness of current and emerging strategic computing systems. The techniques developed as part of this project will also be integrated with large-scale computing educational programs at the University of New Mexico and across the country. This research is grounded in stochastic inter-collective-interval model for characterizing the performance of application/system-software configurations. To this end, the project is investigating techniques for estimating how different system software and applications mechanisms change application model parameters, providing a general means for understanding application/system software performance tradeoffs. In addition, the project is examining optimization techniques that leverage these models to improve resource allocation decisions in system schedulers and runtime systems. These techniques are being evaluated based on their ability to improve the overall performance of modern strategic computing systems in areas such as scheduling, power management, and data locality. The techniques developed as part of this project will also be integrated with large-scale computing educational programs at the University of New Mexico and across the country. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.