Data Visualization in Cloud Service for Scientific Computations

Abstract

The saas.jinr.ru service is an attempt to simplify the usage of the JINR Multifunctional Information and Computing Complex (MICC) of the Joint Institute for Nuclear Research (JINR). It aims at providing a simple problem-oriented web-interface to help students and beginner researchers in the physics domain to abstract away the complexity of the computing infrastructure and to focus on the actual research. In this paper we show our approach to one of the problems within the scope of the project: interactive data visualization in a web-browser. When approaching this problem, we considered two major requirements to the system: first, users may not have any programming skills, so any interaction should be performed using simple visual components; second, the system must be horizontally scalable to cope with irregular user work-sessions. The paper describes how we used Bokeh and Dask for integrating our data visualization solution within the Django framework to deal with the first requirement, and the JINR cloud for service scaling. Application of cloud technologies facilitates dynamic distribution of workload across virtual machines, thus making it possible for us to control the balance between efficient hardware utilization and end-user experience. Shared in this work resulting software architecture and applied solutions, as well as some performance considerations, can be used as an example when designing other cloud-native scientific applications.

Keywords

• cloud computing
• data visualization
• load balancing
• virtualization