Below is a short abstract of my thesis. I plan on uploading the full PDF once the graduate school approves it.
UPDATE: Graduate school has approved it! HERE is the link in case you are interested.
Abstract: Remote visualization has emerged as a necessary tool in the analysis of big data. High-performance computing clusters can provide several benefits in scaling to larger data sizes, from parallel file systems to larger RAM profiles to parallel computation among many CPUs and GPUs. For scalable data visualization, remote visualization tools and infrastructure is critical where only pixels and interaction events are sent over the network instead of the data. In this paper, we present our pipeline using VirtualGL, TurboVNC, and ParaView to render over 40 million points using remote HPC clusters and project over 26 million pixels in a CAVE-style system. We benchmark the system by varying the video stream compression parameters supported by TurboVNC and establish some best practices for typical usage scenarios. This work will help research scientists and academicians in scaling their big data visualizations for real time interaction.
While deciding my thesis topic, I also briefly studied three classes of parallel rendering algorithms: sort-first, sort-middle, and sort-last. Each of the three rendering algorithms suffers from performance issues like load imbalance, high processing and communication costs, and transport delays. I was trying to measure the performance of the rendering algorithms by running and evaluating them on a cluster of PCs and on supercomputer architecture using different data types.
I have been interested in several areas over the last few years including virtual reality, information visualization, information retrieval, systems, low-level OS stuff, docker containers, cloud computing, machine learning, etc. Based on all this, I think I can categorize myself as a generalist who has an inclination towards systems and the applications of cloud computing. I sincerely believe that given enough time and enthusiasm, one can learn and get decently good at a new technology in a few months time.
My Google Scholar profile can be found HERE.