Scalable Scientific Interactive Research Computing With Project Scinco

Abstract

Interactive computing with Jupyter notebooks has transformed the state-of-the-art of scientific research computing. Users can perform a multitude of computational tasks in real time, including data cleansing, analysis, visualization, and post-processing, with Jupyter notebooks. Additionally, the ability to write and execute code and include supporting text and images in the same document has made it popular for use in scholarly articles and teaching. These capabilities complement the batch computing services provided by HPC centers exposed through traditional science gateways. However, integrating Jupyter into science gateways and other advanced computing ecosystems introduces new challenges related to scalability, collaboration, and reproducibility. In this paper, we discuss Project Scinco (Scalable Interactive Computing), an open-source platform for scalable, reproducible, interactive scientific computing, designed to be run in academic computing centers and incorporated into science gateways. We describe the prime features, architecture, deployment choices, and challenges of project Scinco.