Design and experimental evaluation of algorithms for optimizing the throughput of dispersed computing

Abstract

We introduce three optimized scheduling algorithms for dispersed computing and present JupiterTP, a real-world system built on k8s and the prior Jupiter system, enabling end-to-end computation on distributed clusters. Distinguishing itself from traditional throughput optimization approaches that focus on theory and simulations, our work is the first implementation of such an end-to-end system capable of handling arbitrary DAGs across diverse computing networks, including public clouds, IoT systems, and edge networks. Beyond mere scheduling, JupiterTP integrates profilers, execution, and orchestration engines, offering unified interfaces for additional scheduling algorithm integrations. The system's performance is tested on real clusters and real applications, compared to prior work that relied on simulations alone. We make JupiterTP available to the community as open-source software at https://github.com/ANRGUSC/JupiterTP.