Using High-Speed WANs and Network Data Caches to Enable Remote and Distributed Visualization

TL;DR

This paper presents Visapult, a remote visualization framework that leverages high-speed WANs and network data caches to enable efficient visualization of large scientific datasets across distributed resources.

Contribution

It introduces a novel architecture combining high-speed WANs and data caches for scalable, distributed visualization of tera-scale datasets.

Findings

Achieved high data throughput and network utilization.

Decoupled graphics interactivity from network latency.

Improved performance through field-test analysis.

Abstract

Visapult is a prototype application and framework for remote visualization of large scientific datasets. We approach the technical challenges of tera-scale visualization with a unique architecture that employs high speed WANs and network data caches for data staging and transmission. This architecture allows for the use of available cache and compute resources at arbitrary locations on the network. High data throughput rates and network utilization are achieved by parallelizing I/O at each stage in the application, and by pipelining the visualization process. On the desktop, the graphics interactivity is effectively decoupled from the latency inherent in network applications. We present a detailed performance analysis of the application, and improvements resulting from field-test analysis conducted as part of the DOE Combustion Corridor project.