CAREER: Green Functions as a Service: Towards Sustainable and Efficient Distributed Computing Infrastructure

Cloud computing's importance is rapidly growing with the rise of large artificial intelligence (AI) and internet of things (IoT) applications. The proposed work will lay the scientific and technical foundations of a distributed computing infrastructure which is both efficient and economical. It will enable the seamless deployment and use of efficient applications such as web services, AI, IoT, and data analytics. The models, software, and datasets produced through the research will be open-sourced and integrated into undergraduate curriculum and research. The project will develop a new abstraction for efficient, latency-sensitive applications on the edge-cloud continuum. Our approach will be grounded in fundamental principles of efficiency and economics, and use modern AI techniques such as surrogate models for modeling and optimization. We will extend serverless computing with new capabilities such as polymorphic functions for efficient execution on heterogeneous CPU and GPU architectures. Our distributed resource management algorithms will use spatio-temporal workload modeling and optimization. The geographical load balancing will combine machine learning and economics to provide performance management for distributed cyberinfrastructure. Our multi-faceted research and education plan will introduce key principles to both system design and pedagogy, and contribute to a sustainable digital world. 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.