RAMSES: A new project in data-driven analytical modeling of distributed systems
RAMSES is a new DOE-funded project on the end-to-end analytical performance modeling of science workflows in extreme-scale science environments. It aims to link multiple threads of inquiry that have not, until now, been adequately connected: namely, first-principles performance modeling within individual sub-disciplines (e.g., networks, storage systems, applications), and data-driven methods for evaluating, calibrating, and synthesizing models of complex phenomena. What makes this fusion necessary is the drive to explain, predict, and optimize not just individual system components but complex end-to-end workflows. In this talk, I will introduce the goals of the project and some aspects of our technical approach.