Re-presenting Large Image Collections for Data Mining and Analysis

Presenter(s): Paul Rodriguez (SDSC)

Principal Investigator(s): Elizabeth Wuerffel (Valparaiso University) Alison Langmead (University of Pittsburgh)

Presentation Slides

I will discuss two NIP/ECSS projects that both involve primarily image analysis in the context of digital humanities. (Image Analysis of Rural Photography, PI Wuerffel; Decomposing Bodies, [aka Image Analysis of Bertillon Prison Cards], PI Langmead). Both of them are superficially about taking old B&W photograph collections and 'digitizing' them. In a general sense, the goal is to re-represent the data so that the digital humanist can perform particular socio/historical/artistic/cultural analysees. In a more practical sense, the goal is to extract feature from the images and metadata and provide infrastructure support for analysis. Part of our challenge is to line up these two goals.

I will also discuss the technical and programmatic aspects, mostly for my own pieces of the projects. Although the processes, project logistics, and infrastructure are very similar between projects, the actual feature extraction code and data products have little overlap - which is due to the nature of the image data themselves. Feature extraction for both projects primarily involve an assembly of techniques/tools that are in open source packages, where the trickier aspects require coming up with good strategies for applying techniques, evaluating how well they work on this data, and exploring possible methods that might be useful to the user.

Experiences running Dynamic Traffic Assignment Simulations at scale using HPC Infrastructure

Presenter(s): Amit Gupta (TACC)

Principal Investigator(s): Natalia Ruiz Juri (UT)

Presentation Slides

Dynamic Traffic Assignment (DTA) simulations form an important analysis tool for Transportation researchers in attempting to model complex interactions between travelers and transportation infrastructure. These simulation frameworks are complex to develop, maintain and extend. VISTA is a widely used Transportation Simulation framework providing Dynamic Traffic Assignment. I discuss our experiences in scaling VISTA on the Stampede system as an exemplar of how HPC infrastructure and tools can augment analysis workflows in transportation research by significantly speeding up simulation experiments. I also discuss some challenges and tradeoffs in enabling DTA frameworks for use in HPC environments and also directions for continuing/future work under ECSS support.