CSR: Medium: Pythia: An Application Analysis and Online Modeling Based Prediction Framework for Scalable Resource Management

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Computer applications that process large amounts of information are becoming common in a variety of science domains, such as High-Speed Physics, Economics, Genomics, Astronomy, and Meteorology. The overall goal of this project is to design software tools and technologies to support such applications efficiently on advanced computing systems. Moreover, the hardware that is used to implement such advanced systems often boasts of different types of resources, e.g., a conventional computer processor running alongside specialized graphic processing units, and this heterogeneity presents a major challenge when running the applications at the needed large scale. Having a better understanding of the applications behavior on the emerging hardware is key to sustaining these systems. To this end, the project designs and develops Pythia, software that models and predicts how applications would behave on given hardware. This information is then used to better utilize the resources, and achieve scalable and high performance computing systems.The intellectual value of this research involves three intermediate research goals. 1) Design an accurate application classifier using compile-time program analysis that captures workflow behavior and application characteristics, and provides detailed insights into expected runtime application interactions. 2) Design and develop an accurate simulation model that incorporates workflow and application characteristics into a heuristics engine to predict how the application will perform under given conditions and resources. 3) Design a distributed, flexible, efficient, and easy-to-use online oracle framework that captures the infrastructure heterogeneity and integrates with live systems to predict application behavior, which in turn can help guide application-attuned resource scheduling and management. Completion of the project will create tools and technologies for realization of more efficient and scalable computing systems. This work impacts a broad range of disciplines that regularly employ high-performance large-scale computing systems, especially for data-driven discovery. Consequently, use of Pythia will reduce the time-to-solution for modern and emerging applications, and therefore directly affect our way of life. The educational activities, which include recruiting and mentoring women and minority students, will help produce graduates with highly marketable skill sets. The integration of the research discoveries and software tools, which will be open source and made public, into the educational curriculum will help capture the interest of the next generation of computer scientists.