Date of Award

5-2019

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Computer Science

Major Professor

Jian Huang

Committee Members

Jens Gregor, Mark Dean, Russell Zaretzki, Bradley Vander Zanden

Abstract

Traditional HPC visualization applications provide scientists with scalable solutions to work with large datasets. However, computation today is moving towards cloud-hosted systems, as they present key advantages over traditional HPC cluster systems, primarily that of high availability. Computation on a cloud-hosted system can be accessed on demand without long queue times and without long resource acquisition times. Existing applications cannot be ported to the cloud as they rely on a monolithic application structure that does not flexibly distribute among virtual cloud instances.In this dissertation, I study the architectural decisions required to transition scientific data analysis and visualization into the cloud. In particular, I focus on a microservice-based architecture model, designed to use loosely couple modular components using a limited communication model. This general scheme allows scalability and flexibility on cloud-hosted systems, and provides Visualization as a Service that can be deployed on-demand. I present working prototype solutions to the challenges of large data storage and working set management, loosely-coupled rendering and analysis services, and visualization records keeping and reproducibility.

Orcid ID

http://orcid.org/0000-0002-3595-3253

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